How do Durkheimian variables impact variation in national suicide rates when proxies for depression and alcoholism are controlled?

PubMed

Fernquist, Robert M

2007-01-01

Sociological research on Durkheim's theories of egoistic and anomic suicide has given Durkheim continued support more than a century after Durkheim published his work. Recent criticism by Breault (1994), though, argues that Durkheim's theories of suicide actually have not been empirically supported given the lack of psychological variables included in sociological research on suicide rates. Using proxy measures of depression and alcoholism, two known psychological variables to impact suicide, as well as classic Durkheimian variables, suicide rates in eight European countries from 1973-1997 were examined. Results indicate that Durkheim's theories of egoism and anomie, while not completely supported in statistical analysis of suicide rates, received moderate support. Results suggest the continued usefulness of Durkheim's work in aggregate analyses of suicide.

Photospheric Magnetic Field Properties of Flaring versus Flare-quiet Active Regions. II. Discriminant Analysis

NASA Astrophysics Data System (ADS)

Leka, K. D.; Barnes, G.

2003-10-01

We apply statistical tests based on discriminant analysis to the wide range of photospheric magnetic parameters described in a companion paper by Leka & Barnes, with the goal of identifying those properties that are important for the production of energetic events such as solar flares. The photospheric vector magnetic field data from the University of Hawai'i Imaging Vector Magnetograph are well sampled both temporally and spatially, and we include here data covering 24 flare-event and flare-quiet epochs taken from seven active regions. The mean value and rate of change of each magnetic parameter are treated as separate variables, thus evaluating both the parameter's state and its evolution, to determine which properties are associated with flaring. Considering single variables first, Hotelling's T2-tests show small statistical differences between flare-producing and flare-quiet epochs. Even pairs of variables considered simultaneously, which do show a statistical difference for a number of properties, have high error rates, implying a large degree of overlap of the samples. To better distinguish between flare-producing and flare-quiet populations, larger numbers of variables are simultaneously considered; lower error rates result, but no unique combination of variables is clearly the best discriminator. The sample size is too small to directly compare the predictive power of large numbers of variables simultaneously. Instead, we rank all possible four-variable permutations based on Hotelling's T2-test and look for the most frequently appearing variables in the best permutations, with the interpretation that they are most likely to be associated with flaring. These variables include an increasing kurtosis of the twist parameter and a larger standard deviation of the twist parameter, but a smaller standard deviation of the distribution of the horizontal shear angle and a horizontal field that has a smaller standard deviation but a larger kurtosis. To support the ``sorting all permutations'' method of selecting the most frequently occurring variables, we show that the results of a single 10-variable discriminant analysis are consistent with the ranking. We demonstrate that individually, the variables considered here have little ability to differentiate between flaring and flare-quiet populations, but with multivariable combinations, the populations may be distinguished.

Results of Propellant Mixing Variable Study Using Precise Pressure-Based Burn Rate Calculations

NASA Technical Reports Server (NTRS)

Stefanski, Philip L.

2014-01-01

A designed experiment was conducted in which three mix processing variables (pre-curative addition mix temperature, pre-curative addition mixing time, and mixer speed) were varied to estimate their effects on within-mix propellant burn rate variability. The chosen discriminator for the experiment was the 2-inch diameter by 4-inch long (2x4) Center-Perforated (CP) ballistic evaluation motor. Motor nozzle throat diameters were sized to produce a common targeted chamber pressure. Initial data analysis did not show a statistically significant effect. Because propellant burn rate must be directly related to chamber pressure, a method was developed that showed statistically significant effects on chamber pressure (either maximum or average) by adjustments to the process settings. Burn rates were calculated from chamber pressures and these were then normalized to a common pressure for comparative purposes. The pressure-based method of burn rate determination showed significant reduction in error when compared to results obtained from the Brooks' modification of the propellant web-bisector burn rate determination method. Analysis of effects using burn rates calculated by the pressure-based method showed a significant correlation of within-mix burn rate dispersion to mixing duration and the quadratic of mixing duration. The findings were confirmed in a series of mixes that examined the effects of mixing time on burn rate variation, which yielded the same results.

Social Inequality and Labor Force Participation.

ERIC Educational Resources Information Center

King, Jonathan

The labor force participation rates of whites, blacks, and Spanish-Americans, grouped by sex, are explained in a linear regression model fitted with 1970 U. S. Census data on Standard Metropolitan Statistical Area (SMSA). The explanatory variables are: average age, average years of education, vocational training rate, disabled rate, unemployment…

Gender Inequality and Rates of Female Homicide Victimization across U.S. Cities.

ERIC Educational Resources Information Center

Brewer, Victoria E.; Smith, M. Dwayne

1995-01-01

Explores the possibility that female victimization rates are influenced by conditions of sex-based inequality. No single inequality variable was found to be a statistically significant predictor of female homicide rates when controlling for social structural effects. Found little support for gender inequality/female homicide connection. (JBJ)

Gaussian Mixture Model of Heart Rate Variability

PubMed Central

Costa, Tommaso; Boccignone, Giuseppe; Ferraro, Mario

2012-01-01

Heart rate variability (HRV) is an important measure of sympathetic and parasympathetic functions of the autonomic nervous system and a key indicator of cardiovascular condition. This paper proposes a novel method to investigate HRV, namely by modelling it as a linear combination of Gaussians. Results show that three Gaussians are enough to describe the stationary statistics of heart variability and to provide a straightforward interpretation of the HRV power spectrum. Comparisons have been made also with synthetic data generated from different physiologically based models showing the plausibility of the Gaussian mixture parameters. PMID:22666386

Computerized system for assessing heart rate variability.

PubMed

Frigy, A; Incze, A; Brânzaniuc, E; Cotoi, S

1996-01-01

The principal theoretical, methodological and clinical aspects of heart rate variability (HRV) analysis are reviewed. This method has been developed over the last 10 years as a useful noninvasive method of measuring the activity of the autonomic nervous system. The main components and the functioning of the computerized rhythm-analyzer system developed by our team are presented. The system is able to perform short-term (maximum 20 minutes) time domain HRV analysis and statistical analysis of the ventricular rate in any rhythm, particularly in atrial fibrillation. The performances of our system are demonstrated by using the graphics (RR histograms, delta RR histograms, RR scattergrams) and the statistical parameters resulted from the processing of three ECG recordings. These recordings are obtained from a normal subject, from a patient with advanced heart failure, and from a patient with atrial fibrillation.

Data Analysis & Statistical Methods for Command File Errors

NASA Technical Reports Server (NTRS)

Meshkat, Leila; Waggoner, Bruce; Bryant, Larry

2014-01-01

This paper explains current work on modeling for managing the risk of command file errors. It is focused on analyzing actual data from a JPL spaceflight mission to build models for evaluating and predicting error rates as a function of several key variables. We constructed a rich dataset by considering the number of errors, the number of files radiated, including the number commands and blocks in each file, as well as subjective estimates of workload and operational novelty. We have assessed these data using different curve fitting and distribution fitting techniques, such as multiple regression analysis, and maximum likelihood estimation to see how much of the variability in the error rates can be explained with these. We have also used goodness of fit testing strategies and principal component analysis to further assess our data. Finally, we constructed a model of expected error rates based on the what these statistics bore out as critical drivers to the error rate. This model allows project management to evaluate the error rate against a theoretically expected rate as well as anticipate future error rates.

Rates of profit as correlated sums of random variables

NASA Astrophysics Data System (ADS)

Greenblatt, R. E.

2013-10-01

Profit realization is the dominant feature of market-based economic systems, determining their dynamics to a large extent. Rather than attaining an equilibrium, profit rates vary widely across firms, and the variation persists over time. Differing definitions of profit result in differing empirical distributions. To study the statistical properties of profit rates, I used data from a publicly available database for the US Economy for 2009-2010 (Risk Management Association). For each of three profit rate measures, the sample space consists of 771 points. Each point represents aggregate data from a small number of US manufacturing firms of similar size and type (NAICS code of principal product). When comparing the empirical distributions of profit rates, significant ‘heavy tails’ were observed, corresponding principally to a number of firms with larger profit rates than would be expected from simple models. An apparently novel correlated sum of random variables statistical model was used to model the data. In the case of operating and net profit rates, a number of firms show negative profits (losses), ruling out simple gamma or lognormal distributions as complete models for these data.

Recurrence of attic cholesteatoma: different methods of estimating recurrence rates.

PubMed

Stangerup, S E; Drozdziewicz, D; Tos, M; Hougaard-Jensen, A

2000-09-01

One problem in cholesteatoma surgery is recurrence of cholesteatoma, which is reported to vary from 5% to 71%. This great variability can be explained by issues such as the type of cholesteatoma, surgical technique, follow-up rate, length of the postoperative observation period, and statistical method applied. The aim of this study was to illustrate the impact of applying different statistical methods to the same material. Thirty-three children underwent single-stage surgery for attic cholesteatoma during a 15-year period. Thirty patients (94%) attended a re-evaluation. During the observation period of 15 years, recurrence of cholesteatoma occurred in 10 ears. The cumulative total recurrence rate varied from 30% to 67%, depending on the statistical method applied. In conclusion, the choice of statistical method should depend on the number of patients, follow-up rates, length of the postoperative observation period and presence of censored data.

Effect of Different Phases of Menstrual Cycle on Heart Rate Variability (HRV).

PubMed

Brar, Tejinder Kaur; Singh, K D; Kumar, Avnish

2015-10-01

Heart Rate Variability (HRV), which is a measure of the cardiac autonomic tone, displays physiological changes throughout the menstrual cycle. The functions of the ANS in various phases of the menstrual cycle were examined in some studies. The aim of our study was to observe the effect of menstrual cycle on cardiac autonomic function parameters in healthy females. A cross-sectional (observational) study was conducted on 50 healthy females, in the age group of 18-25 years. Heart Rate Variability (HRV) was recorded by Physio Pac (PC-2004). The data consisted of Time Domain Analysis and Frequency Domain Analysis in menstrual, proliferative and secretory phase of menstrual cycle. Data collected was analysed statistically using student's pair t-test. The difference in mean heart rate, LF power%, LFnu and HFnu in menstrual and proliferative phase was found to be statistically significant. The difference in mean RR, Mean HR, RMSSD (the square root of the mean of the squares of the successive differences between adjacent NNs.), NN50 (the number of pairs of successive NNs that differ by more than 50 ms), pNN50 (the proportion of NN50 divided by total number of NNs.), VLF (very low frequency) power, LF (low frequency) power, LF power%, HF power %, LF/HF ratio, LFnu and HFnu was found to be statistically significant in proliferative and secretory phase. The difference in Mean RR, Mean HR, LFnu and HFnu was found to be statistically significant in secretory and menstrual phases. From the study it can be concluded that sympathetic nervous activity in secretory phase is greater than in the proliferative phase, whereas parasympathetic nervous activity is predominant in proliferative phase.

Effect of Different Phases of Menstrual Cycle on Heart Rate Variability (HRV)

PubMed Central

Singh, K. D.; Kumar, Avnish

2015-01-01

Background Heart Rate Variability (HRV), which is a measure of the cardiac autonomic tone, displays physiological changes throughout the menstrual cycle. The functions of the ANS in various phases of the menstrual cycle were examined in some studies. Aims and Objectives The aim of our study was to observe the effect of menstrual cycle on cardiac autonomic function parameters in healthy females. Materials and Methods A cross-sectional (observational) study was conducted on 50 healthy females, in the age group of 18-25 years. Heart Rate Variability (HRV) was recorded by Physio Pac (PC-2004). The data consisted of Time Domain Analysis and Frequency Domain Analysis in menstrual, proliferative and secretory phase of menstrual cycle. Data collected was analysed statistically using student’s pair t-test. Results The difference in mean heart rate, LF power%, LFnu and HFnu in menstrual and proliferative phase was found to be statistically significant. The difference in mean RR, Mean HR, RMSSD (the square root of the mean of the squares of the successive differences between adjacent NNs.), NN50 (the number of pairs of successive NNs that differ by more than 50 ms), pNN50 (the proportion of NN50 divided by total number of NNs.), VLF (very low frequency) power, LF (low frequency) power, LF power%, HF power %, LF/HF ratio, LFnu and HFnu was found to be statistically significant in proliferative and secretory phase. The difference in Mean RR, Mean HR, LFnu and HFnu was found to be statistically significant in secretory and menstrual phases. Conclusion From the study it can be concluded that sympathetic nervous activity in secretory phase is greater than in the proliferative phase, whereas parasympathetic nervous activity is predominant in proliferative phase. PMID:26557512

What Response Rates Are Needed to Make Reliable Inferences from Student Evaluations of Teaching?

ERIC Educational Resources Information Center

Zumrawi, Abdel Azim; Bates, Simon P.; Schroeder, Marianne

2014-01-01

This paper addresses the determination of statistically desirable response rates in students' surveys, with emphasis on assessing the effect of underlying variability in the student evaluation of teaching (SET). We discuss factors affecting the determination of adequate response rates and highlight challenges caused by non-response and lack of…

Descriptive Analysis of Student Ratings

ERIC Educational Resources Information Center

Marasini, Donata; Quatto, Piero

2011-01-01

Let X be a statistical variable representing student ratings of University teaching. It is natural to assume for X an ordinal scale consisting of k categories (in ascending order of satisfaction). At first glance, student ratings can be summarized by a location index (such as the mode or the median of X) associated with a convenient measure of…

Information trimming: Sufficient statistics, mutual information, and predictability from effective channel states

NASA Astrophysics Data System (ADS)

James, Ryan G.; Mahoney, John R.; Crutchfield, James P.

2017-06-01

One of the most basic characterizations of the relationship between two random variables, X and Y , is the value of their mutual information. Unfortunately, calculating it analytically and estimating it empirically are often stymied by the extremely large dimension of the variables. One might hope to replace such a high-dimensional variable by a smaller one that preserves its relationship with the other. It is well known that either X (or Y ) can be replaced by its minimal sufficient statistic about Y (or X ) while preserving the mutual information. While intuitively reasonable, it is not obvious or straightforward that both variables can be replaced simultaneously. We demonstrate that this is in fact possible: the information X 's minimal sufficient statistic preserves about Y is exactly the information that Y 's minimal sufficient statistic preserves about X . We call this procedure information trimming. As an important corollary, we consider the case where one variable is a stochastic process' past and the other its future. In this case, the mutual information is the channel transmission rate between the channel's effective states. That is, the past-future mutual information (the excess entropy) is the amount of information about the future that can be predicted using the past. Translating our result about minimal sufficient statistics, this is equivalent to the mutual information between the forward- and reverse-time causal states of computational mechanics. We close by discussing multivariate extensions to this use of minimal sufficient statistics.

Bone grafts utilized in dentistry: an analysis of patients' preferences.

PubMed

Fernández, Ramón Fuentes; Bucchi, Cristina; Navarro, Pablo; Beltrán, Víctor; Borie, Eduardo

2015-10-20

Many procedures currently require the use of bone grafts to replace or recover bone volume that has been resorbed. However, the patient's opinion and preferences must be taken into account before implementing any treatment. Researchers have focused primarily on assessing the effectiveness of bone grafts rather than on patients' perceptions. Thus, the aim of this study was to explore patients' opinions regarding the different types of bone grafts used in dental treatments. One hundred patients were randomly chosen participated in the study. A standardized survey of 10 questions was used to investigate their opinions regarding the different types of bone grafts used in dental treatments. Descriptive statistics were calculated for the different variables, and absolute frequencies and percentages were used as summary measures. A value of p <0.05 was selected as the threshold for statistical significance. The highest rate of refusal was observed for allografts and xenografts. The grafts with the lowest rates of refusal were autologous grafts (3 %) and alloplastics (2 %). No significant differences were found between the various types of bone grafts in the sociodemographic variables or the refusal/acceptance variable. Similarly, no significant relations were observed between a specific religious affiliation and the acceptance/refusal rates of the various types of graft. Allografts and xenografts elicited the highest refusal rates among the surveyed patients, and autologous bone and alloplastics were the most accepted bone grafts. Moreover, no differences were found in the sociodemographic variables or religious affiliations in terms of the acceptance/refusal rates of the different bone grafts.

Variability in Non-Target Terrestrial Plant Studies Should Inform Endpoint Selection.

PubMed

Staveley, J P; Green, J W; Nusz, J; Edwards, D; Henry, K; Kern, M; Deines, A M; Brain, R; Glenn, B; Ehresman, N; Kung, T; Ralston-Hooper, K; Kee, F; McMaster, S

2018-05-04

Inherent variability in Non-Target Terrestrial Plant (NTTP) testing of pesticides creates challenges for using and interpreting these data for risk assessment. Standardized NTTP testing protocols were initially designed to calculate the application rate causing a 25% effect (ER25, used in the U.S.) or a 50% effect (ER50, used in Europe) for various measures based on the observed dose-response. More recently, the requirement to generate a no-observed-effect rate (NOER), or, in the absence of a NOER, the rate causing a 5% effect (ER05), has raised questions about the inherent variability in, and statistical detectability of, these tests. Statistically significant differences observed between test and control groups may be a product of this inherent variability and may not represent biological relevance. Attempting to derive an ER05 and the associated risk assessment conclusions drawn from these values can overestimate risk. To address these concerns, we evaluated historical data from approximately 100 seedling emergence and vegetative vigor guideline studies on pesticides to assess the variability of control results across studies for each plant species, examined potential causes for the variation in control results, and defined the minimum percent effect that can be reliably detected. The results indicate that with current test design and implementation, the ER05 cannot be reliably estimated. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Does raising type 1 error rate improve power to detect interactions in linear regression models? A simulation study.

PubMed

Durand, Casey P

2013-01-01

Statistical interactions are a common component of data analysis across a broad range of scientific disciplines. However, the statistical power to detect interactions is often undesirably low. One solution is to elevate the Type 1 error rate so that important interactions are not missed in a low power situation. To date, no study has quantified the effects of this practice on power in a linear regression model. A Monte Carlo simulation study was performed. A continuous dependent variable was specified, along with three types of interactions: continuous variable by continuous variable; continuous by dichotomous; and dichotomous by dichotomous. For each of the three scenarios, the interaction effect sizes, sample sizes, and Type 1 error rate were varied, resulting in a total of 240 unique simulations. In general, power to detect the interaction effect was either so low or so high at α = 0.05 that raising the Type 1 error rate only served to increase the probability of including a spurious interaction in the model. A small number of scenarios were identified in which an elevated Type 1 error rate may be justified. Routinely elevating Type 1 error rate when testing interaction effects is not an advisable practice. Researchers are best served by positing interaction effects a priori and accounting for them when conducting sample size calculations.

Indian summer monsoon rainfall: Dancing with the tunes of the sun

NASA Astrophysics Data System (ADS)

Hiremath, K. M.; Manjunath, Hegde; Soon, Willie

2015-02-01

There is strong statistical evidence that solar activity influences the Indian summer monsoon rainfall. To search for a physical link between the two, we consider the coupled cloud hydrodynamic equations, and derive an equation for the rate of precipitation that is similar to the equation of a forced harmonic oscillator, with cloud and rain water mixing ratios as forcing variables. Those internal forcing variables are parameterized in terms of the combined effect of external forcing as measured by sunspot and coronal hole activities with several well known solar periods (9, 13 and 27 days; 1.3, 5, 11 and 22 years). The equation is then numerically solved and the results show that the variability of the simulated rate of precipitation captures very well the actual variability of the Indian monsoon rainfall, yielding vital clues for a physical understanding that has so far eluded analyses based on statistical correlations alone. We also solved the precipitation equation by allowing for the effects of long-term variation of aerosols. We tentatively conclude that the net effects of aerosols variation are small, when compared to the solar factors, in terms of explaining the observed rainfall variability covering the full Indian monsoonal geographical domains.

Strengthening the Validity of Population-Based Suicide Rate Comparisons: An Illustration Using U.S. Military and Civilian Data

ERIC Educational Resources Information Center

Eaton, Karen M.; Messer, Stephen C.; Garvey Wilson, Abigail L.; Hoge, Charles W.

2006-01-01

The objectives of this study were to generate precise estimates of suicide rates in the military while controlling for factors contributing to rate variability such as demographic differences and classification bias, and to develop a simple methodology for the determination of statistically derived thresholds for detecting significant rate…

Identifying the impact of social determinants of health on disease rates using correlation analysis of area-based summary information.

PubMed

Song, Ruiguang; Hall, H Irene; Harrison, Kathleen McDavid; Sharpe, Tanya Telfair; Lin, Lillian S; Dean, Hazel D

2011-01-01

We developed a statistical tool that brings together standard, accessible, and well-understood analytic approaches and uses area-based information and other publicly available data to identify social determinants of health (SDH) that significantly affect the morbidity of a specific disease. We specified AIDS as the disease of interest and used data from the American Community Survey and the National HIV Surveillance System. Morbidity and socioeconomic variables in the two data systems were linked through geographic areas that can be identified in both systems. Correlation and partial correlation coefficients were used to measure the impact of socioeconomic factors on AIDS diagnosis rates in certain geographic areas. We developed an easily explained approach that can be used by a data analyst with access to publicly available datasets and standard statistical software to identify the impact of SDH. We found that the AIDS diagnosis rate was highly correlated with the distribution of race/ethnicity, population density, and marital status in an area. The impact of poverty, education level, and unemployment depended on other SDH variables. Area-based measures of socioeconomic variables can be used to identify risk factors associated with a disease of interest. When correlation analysis is used to identify risk factors, potential confounding from other variables must be taken into account.

Fluency variation in adolescents.

PubMed

Furquim de Andrade, Claudia Regina; de Oliveira Martins, Vanessa

2007-10-01

The Speech Fluency Profile of fluent adolescent speakers of Brazilian Portuguese, were examined with respect to gender and neurolinguistic variations. Speech samples of 130 male and female adolescents, aged between 12;0 and 17;11 years were gathered. They were analysed according to type of speech disruption; speech rate; and frequency of speech disruptions. Statistical analysis did not find significant differences between genders for the variables studied. However, regarding the phases of adolescence (early: 12;0-14;11 years; late: 15;0-17;11 years), statistical differences were observed for all of the variables. As for neurolinguistic maturation, a decrease in the number of speech disruptions and an increase in speech rate occurred during the final phase of adolescence, indicating that the maturation of the motor and linguistic processes exerted an influence over the fluency profile of speech.

Ordinal pattern statistics for the assessment of heart rate variability

NASA Astrophysics Data System (ADS)

Graff, G.; Graff, B.; Kaczkowska, A.; Makowiec, D.; Amigó, J. M.; Piskorski, J.; Narkiewicz, K.; Guzik, P.

2013-06-01

The recognition of all main features of a healthy heart rhythm (the so-called sinus rhythm) is still one of the biggest challenges in contemporary cardiology. Recently the interesting physiological phenomenon of heart rate asymmetry has been observed. This phenomenon is related to unbalanced contributions of heart rate decelerations and accelerations to heart rate variability. In this paper we apply methods based on the concept of ordinal pattern to the analysis of electrocardiograms (inter-peak intervals) of healthy subjects in the supine position. This way we observe new regularities of the heart rhythm related to the distribution of ordinal patterns of lengths 3 and 4.

Socio-Economic Factors Influencing on Total Fertility Rate in Iran: A Panel Data Analysis for the Period of 2002–2012

PubMed Central

Jafari, Hasan; Jaafaripooyan, Ebrahim; Vedadhir, Abou Ali; Foroushani, Abbas Rahimi; Ahadinejad, Bahman; Pourreza, Abolghasem

2016-01-01

Introduction Over the last few decades, total fertility rate (TFR) has followed a downward trend in Iran. The consequences of this trend from the perspectives of some are negative. Considering the macro-population policies in recent years, this study aimed to examine the effect of some macro socio-economic variables, including divorce, marriage, urbanization, and unemployment rate on TFR in Iran from 2002 to 2012. Methods This time series research was conducted in 2015 using the databases of the National Organization for Civil Registration (NOCR) and the Statistical Center of Iran. The study population was the related data of provinces in the selected variables. The main methods used in the research were the common unit root test, Pedroni Cointegration test, redundant fixed effects tests, correlated random effects-Hausman test, and panel least squares of fixed effects. In order to determine the suitable model for estimating panel data, likelihood ratio and Huasman tests were done using Eviews software, and the fixed effects regression model was chosen as the dominant model. Results The results indicated that the divorce rate had a negative and significant effect on TFR (p < 0.05). A positive and significant relationship between marriage rate and TFR variables also was observed (p < 0.05). Urbanization rate (p = 0.24) and unemployment rate (p = 0.36) had no significant relationship with TFR. According to F statistic, significance of the overall model also was confirmed (p < 0.001). Conclusion Due to the lower effect of the studied factors on the reduction of TFR, it seems that variables other than the ones studied, as well as cultural factors and values, might be fundamental factors for this change in the country. PMID:27504172

A Statistical Analysis of Reviewer Agreement and Bias in Evaluating Medical Abstracts 1

PubMed Central

Cicchetti, Domenic V.; Conn, Harold O.

1976-01-01

Observer variability affects virtually all aspects of clinical medicine and investigation. One important aspect, not previously examined, is the selection of abstracts for presentation at national medical meetings. In the present study, 109 abstracts, submitted to the American Association for the Study of Liver Disease, were evaluated by three “blind” reviewers for originality, design-execution, importance, and overall scientific merit. Of the 77 abstracts rated for all parameters by all observers, interobserver agreement ranged between 81 and 88%. However, corresponding intraclass correlations varied between 0.16 (approaching statistical significance) and 0.37 (p < 0.01). Specific tests of systematic differences in scoring revealed statistically significant levels of observer bias on most of the abstract components. Moreover, the mean differences in interobserver ratings were quite small compared to the standard deviations of these differences. These results emphasize the importance of evaluating the simple percentage of rater agreement within the broader context of observer variability and systematic bias. PMID:997596

Wavelet and receiver operating characteristic analysis of heart rate variability

NASA Astrophysics Data System (ADS)

McCaffery, G.; Griffith, T. M.; Naka, K.; Frennaux, M. P.; Matthai, C. C.

2002-02-01

Multiresolution wavelet analysis has been used to study the heart rate variability in two classes of patients with different pathological conditions. The scale dependent measure of Thurner et al. was found to be statistically significant in discriminating patients suffering from hypercardiomyopathy from a control set of normal subjects. We have performed Receiver Operating Characteristc (ROC) analysis and found the ROC area to be a useful measure by which to label the significance of the discrimination, as well as to describe the severity of heart dysfunction.

US Intergroup Anal Carcinoma Trial: Tumor Diameter Predicts for Colostomy

PubMed Central

Ajani, Jaffer A.; Winter, Kathryn A.; Gunderson, Leonard L.; Pedersen, John; Benson, Al B.; Thomas, Charles R.; Mayer, Robert J.; Haddock, Michael G.; Rich, Tyvin A.; Willett, Christopher G.

2009-01-01

Purpose The US Gastrointestinal Intergroup Radiation Therapy Oncology Group 98-11 anal carcinoma trial showed that cisplatin-based concurrent chemoradiotherapy resulted in a significantly higher rate of colostomy compared with mitomycin-based therapy. Established prognostic variables for patients with anal carcinoma include tumor diameter, clinical nodal status, and sex, but pretreatment variables that would predict the likelihood of colostomy are unknown. Methods A secondary analysis was performed by combining patients in the two treatment arms to evaluate whether new predictive and prognostic variables would emerge. Univariate and multivariate analyses were carried out to correlate overall survival (OS), disease-free survival, and time to colostomy (TTC) with pretreatment and treatment variables. Results Of 682 patients enrolled, 644 patients were assessable and analyzed. In the multivariate analysis, tumor-related prognosticators for poorer OS included node-positive cancer (P ≤ .0001), large (> 5 cm) tumor diameter (P = .01), and male sex (P = .016). In the treatment-related categories, cisplatin-based therapy was statistically significantly associated with a higher rate of colostomy (P = .03) than was mitomycin-based therapy. In the pretreatment variables category, only large tumor diameter independently predicted for TTC (P = .008). Similarly, the cumulative 5-year colostomy rate was statistically significantly higher for large tumor diameter than for small tumor diameter (Gray's test; P = .0074). Clinical nodal status and sex were not predictive of TTC. Conclusion The combined analysis of the two arms of RTOG 98-11, representing the largest prospective database, reveals that tumor diameter (irrespective of the nodal status) is the only independent pretreatment variable that predicts TTC and 5-year colostomy rate in patients with anal carcinoma. PMID:19139424

[Reproductive variables and gynaecological service use in delusional disorder outpatients].

PubMed

González-Rodríguez, Alexandre; Molina-Andreu, Oriol; Penadés Rubio, Rafael; Catalán Campos, Rosa; Bernardo Arroyo, Miguel

2015-01-01

Oestrogens have been hypothesized to have a protective effect in psychotic disorders. Women with schizophrenia have a later age of menarche, fewer pregnancies and earlier age of menopause. However, little information is available focusing on delusional disorder (DD). We aimed to evaluate gynaecological variables and psychopathology, and rates of gynaecological service use in female DD outpatients. Fourty-six outpatients with DD (DSM-IV-TR) were attended at the Hospital Clinic of Barcelona, from 2008 to 2013. Demographic and clinical variables, as well as gynaecological features were recorded in twenty-five women with DD. Hamilton Rating Scale for Depression-17 for depression, Positive and Negative Syndrome Scale for psychopathology, Personal and Social Performance for functionality, and Columbia Suicide Severity Rating Scale were assessed. Mean age of menarche (SD) was 12.83(1.54) years, mean age of menopause 48.73(2.69), mean age at onset of DD was 48.70(13.03). 48% of the sample did not receive gynaecological attention in the last 2-3 years. No statistically significant correlations were found between age at menopause and age at onset of DD. Age at menopause showed a tendency to be negatively correlated with Personal and Social Performance total scores (r = -0.431; P = .074), and was positively associated with suicidal ideation intensity (r = 0.541; P = .038). However, after controlling for social support variables, this relationship was no longer significant. Although a small sample size, this is the first study to specifically examine gynaecological variables in DD. Low compliance rates in gynaecological service use were found. No correlations between age at menopause and clinical variables were statistically significant. Copyright © 2013 SEP y SEPB. Published by Elsevier España. All rights reserved.

Estimating degradation in real time and accelerated stability tests with random lot-to-lot variation: a simulation study.

PubMed

Magari, Robert T

2002-03-01

The effect of different lot-to-lot variability levels on the prediction of stability are studied based on two statistical models for estimating degradation in real time and accelerated stability tests. Lot-to-lot variability is considered as random in both models, and is attributed to two sources-variability at time zero, and variability of degradation rate. Real-time stability tests are modeled as a function of time while accelerated stability tests as a function of time and temperatures. Several data sets were simulated, and a maximum likelihood approach was used for estimation. The 95% confidence intervals for the degradation rate depend on the amount of lot-to-lot variability. When lot-to-lot degradation rate variability is relatively large (CV > or = 8%) the estimated confidence intervals do not represent the trend for individual lots. In such cases it is recommended to analyze each lot individually. Copyright 2002 Wiley-Liss, Inc. and the American Pharmaceutical Association J Pharm Sci 91: 893-899, 2002

Changing maternity leave policy: short-term effects on fertility rates and demographic variables in Germany.

PubMed

Thyrian, Jochen René; Fendrich, Konstanze; Lange, Anja; Haas, Johannes-Peter; Zygmunt, Marek; Hoffmann, Wolfgang

2010-08-01

Changes in reproductive behaviour and decreasing fertility rates have recently led to policy actions that attempt to counteract these developments. Evidence on the efficacy of such policy interventions, however, is limited. The present analysis examines fertility rates and demographic variables of a population in Germany in response to new maternity leave regulations, which were introduced in January 2007. As part of a population-based survey of neonates in Pomerania (SNiP), all births in the study region from the period 23 months prior to January 1st, 2007 until 23 months afterwards were examined. Crude Birth Rates (CBR) per month, General Fertility Rates (GFR) per month, parity and sociodemographic variables were compared using bivariate techniques. Logistic regression analysis was performed. No statistically significant difference in the CBR or GFR after Jan. 1st, 2007 was found. There were statistically significant differences in other demographic variables, however. The proportion of mothers who (a) were employed full-time before pregnancy; (b) came from a higher socioeconomic status; and (c) had higher income levels all increased after January 1st, 2007. The magnitude of these effects was higher in multigravid women. Forward stepwise logistic regression found an odds ratio of 1.79 for women with a family income of more than 3000 euro to give birth after the new law was introduced. This is the first analysis of population-based data that examines fertility rates and sociodemographic variables in response to new legal regulations. No short-term effects on birth rates were detected, but there was a differential effect on the subgroup of multigravidae. The focus of this policy was to provide financial support, which is certainly important, but the complexity of having a child suggests that attitudinal and motivational aspects also need to be taken into account. Furthermore, these analyses were only able to evaluate the short-term consequences of the policy; further studies are needed to assess for different, long-term effects. (c) 2010 Elsevier Ltd. All rights reserved.

Modelling seasonal effects of temperature and precipitation on honey bee winter mortality in a temperate climate.

PubMed

Switanek, Matthew; Crailsheim, Karl; Truhetz, Heimo; Brodschneider, Robert

2017-02-01

Insect pollinators are essential to global food production. For this reason, it is alarming that honey bee (Apis mellifera) populations across the world have recently seen increased rates of mortality. These changes in colony mortality are often ascribed to one or more factors including parasites, diseases, pesticides, nutrition, habitat dynamics, weather and/or climate. However, the effect of climate on colony mortality has never been demonstrated. Therefore, in this study, we focus on longer-term weather conditions and/or climate's influence on honey bee winter mortality rates across Austria. Statistical correlations between monthly climate variables and winter mortality rates were investigated. Our results indicate that warmer and drier weather conditions in the preceding year were accompanied by increased winter mortality. We subsequently built a statistical model to predict colony mortality using temperature and precipitation data as predictors. Our model reduces the mean absolute error between predicted and observed colony mortalities by 9% and is statistically significant at the 99.9% confidence level. This is the first study to show clear evidence of a link between climate variability and honey bee winter mortality. Copyright © 2016 British Geological Survey, NERC. Published by Elsevier B.V. All rights reserved.

Exposure to bisphenol A from drinking canned beverages increases blood pressure: randomized crossover trial.

PubMed

Bae, Sanghyuk; Hong, Yun-Chul

2015-02-01

Bisphenol A (BPA) is a chemical used in plastic bottles and inner coating of beverage cans, and its exposure is almost ubiquitous. BPA has been associated with hypertension and decreased heart rate variability in the previous studies. The aim of the present study was to determine whether increased BPA exposure from consumption of canned beverage actually affects blood pressure and heart rate variability. We conducted a randomized crossover trial with noninstitutionalized adults, who were aged ≥60 years and recruited from a local community center. A total of 60 participants visited the study site 3 times, and they were provided the same beverage in 2 glass bottles, 2 cans, or 1 can and 1 glass bottle at a time. The sequence of the beverage was randomized. We then measured urinary BPA concentration, blood pressure, and heart rate variability 2 hours after the consumption of each beverage. The paired t test and mixed model were used to compare the differences. The urinary BPA concentration increased after consuming canned beverages by >1600% compared with that after consuming glass bottled beverages. Systolic blood pressure adjusted for daily variance increased by ≈4.5 mm Hg after consuming 2 canned beverages compared with that after consuming 2 glass bottled beverages, and the difference was statistically significant. The parameters of the heart rate variability did not show statistically significant differences.The present study demonstrated that consuming canned beverage and consequent increase of BPA exposure increase blood pressure acutely. © 2014 American Heart Association, Inc.

Statistics of strain rates and surface density function in a flame-resolved high-fidelity simulation of a turbulent premixed bluff body burner

NASA Astrophysics Data System (ADS)

Sandeep, Anurag; Proch, Fabian; Kempf, Andreas M.; Chakraborty, Nilanjan

2018-06-01

The statistical behavior of the surface density function (SDF, the magnitude of the reaction progress variable gradient) and the strain rates, which govern the evolution of the SDF, have been analyzed using a three-dimensional flame-resolved simulation database of a turbulent lean premixed methane-air flame in a bluff-body configuration. It has been found that the turbulence intensity increases with the distance from the burner, changing the flame curvature distribution and increasing the probability of the negative curvature in the downstream direction. The curvature dependences of dilatation rate ∇ṡu → and displacement speed Sd give rise to variations of these quantities in the axial direction. These variations affect the nature of the alignment between the progress variable gradient and the local principal strain rates, which in turn affects the mean flame normal strain rate, which assumes positive values close to the burner but increasingly becomes negative as the effect of turbulence increases with the axial distance from the burner exit. The axial distance dependences of the curvature and displacement speed also induce a considerable variation in the mean value of the curvature stretch. The axial distance dependences of the dilatation rate and flame normal strain rate govern the behavior of the flame tangential strain rate, and its mean value increases in the downstream direction. The current analysis indicates that the statistical behaviors of different strain rates and displacement speed and their curvature dependences need to be included in the modeling of flame surface density and scalar dissipation rate in order to accurately capture their local behaviors.

Regression methods for spatially correlated data: an example using beetle attacks in a seed orchard

Treesearch

Preisler Haiganoush; Nancy G. Rappaport; David L. Wood

1997-01-01

We present a statistical procedure for studying the simultaneous effects of observed covariates and unmeasured spatial variables on responses of interest. The procedure uses regression type analyses that can be used with existing statistical software packages. An example using the rate of twig beetle attacks on Douglas-fir trees in a seed orchard illustrates the...

Heart Rate Variability Dynamics for the Prognosis of Cardiovascular Risk

PubMed Central

Ramirez-Villegas, Juan F.; Lam-Espinosa, Eric; Ramirez-Moreno, David F.; Calvo-Echeverry, Paulo C.; Agredo-Rodriguez, Wilfredo

2011-01-01

Statistical, spectral, multi-resolution and non-linear methods were applied to heart rate variability (HRV) series linked with classification schemes for the prognosis of cardiovascular risk. A total of 90 HRV records were analyzed: 45 from healthy subjects and 45 from cardiovascular risk patients. A total of 52 features from all the analysis methods were evaluated using standard two-sample Kolmogorov-Smirnov test (KS-test). The results of the statistical procedure provided input to multi-layer perceptron (MLP) neural networks, radial basis function (RBF) neural networks and support vector machines (SVM) for data classification. These schemes showed high performances with both training and test sets and many combinations of features (with a maximum accuracy of 96.67%). Additionally, there was a strong consideration for breathing frequency as a relevant feature in the HRV analysis. PMID:21386966

Spatio-temporal hierarchical modeling of rates and variability of Holocene sea-level changes in the western North Atlantic and the Caribbean

NASA Astrophysics Data System (ADS)

Ashe, E.; Kopp, R. E.; Khan, N.; Horton, B.; Engelhart, S. E.

2016-12-01

Sea level varies over of both space and time. Prior to the instrumental period, the sea-level record depends upon geological reconstructions that contain vertical and temporal uncertainty. Spatio-temporal statistical models enable the interpretation of RSL and rates of change as well as the reconstruction of the entire sea-level field from such noisy data. Hierarchical models explicitly distinguish between a process level, which characterizes the spatio-temporal field, and a data level, by which sparse proxy data and its noise is recorded. A hyperparameter level depicts prior expectations about the structure of variability in the spatio-temporal field. Spatio-temporal hierarchical models are amenable to several analysis approaches, with tradeoffs regarding computational efficiency and comprehensiveness of uncertainty characterization. A fully-Bayesian hierarchical model (BHM), which places prior probability distributions upon the hyperparameters, is more computationally intensive than an empirical hierarchical model (EHM), which uses point estimates of hyperparameters, derived from the data [1]. Here, we assess the sensitivity of posterior estimates of relative sea level (RSL) and rates to different statistical approaches by varying prior assumptions about the spatial and temporal structure of sea-level variability and applying multiple analytical approaches to Holocene sea-level proxies along the Atlantic coast of North American and the Caribbean [2]. References: 1. N Cressie, Wikle CK (2011) Statistics for spatio-temporal data (John Wiley & Sons). 2. Kahn N et al. (2016). Quaternary Science Reviews (in revision).

Counter-propagation network with variable degree variable step size LMS for single switch typing recognition.

PubMed

Yang, Cheng-Huei; Luo, Ching-Hsing; Yang, Cheng-Hong; Chuang, Li-Yeh

2004-01-01

Morse code is now being harnessed for use in rehabilitation applications of augmentative-alternative communication and assistive technology, including mobility, environmental control and adapted worksite access. In this paper, Morse code is selected as a communication adaptive device for disabled persons who suffer from muscle atrophy, cerebral palsy or other severe handicaps. A stable typing rate is strictly required for Morse code to be effective as a communication tool. This restriction is a major hindrance. Therefore, a switch adaptive automatic recognition method with a high recognition rate is needed. The proposed system combines counter-propagation networks with a variable degree variable step size LMS algorithm. It is divided into five stages: space recognition, tone recognition, learning process, adaptive processing, and character recognition. Statistical analyses demonstrated that the proposed method elicited a better recognition rate in comparison to alternative methods in the literature.

Effect of Brazil's conditional cash transfer programme on tuberculosis incidence.

PubMed

Nery, J S; Rodrigues, L C; Rasella, D; Aquino, R; Barreira, D; Torrens, A W; Boccia, D; Penna, G O; Penna, M L F; Barreto, M L; Pereira, S M

2017-07-01

To evaluate the impact of the Brazilian cash transfer programme (Bolsa Família Programme, BFP) on tuberculosis (TB) incidence in Brazil from 2004 to 2012. We studied tuberculosis surveillance data using a combination of an ecological multiple-group and time-trend design covering 2458 Brazilian municipalities. The main independent variable was BFP coverage and the outcome was the TB incidence rate. All study variables were obtained from national databases. We used fixed-effects negative binomial models for panel data adjusted for selected covariates and a variable representing time. After controlling for covariates, TB incidence rates were significantly reduced in municipalities with high BFP coverage compared with those with low and intermediate coverage (in a model with a time variable incidence rate ratio = 0.96, 95%CI 0.93-0.99). This was the first evidence of a statistically significant association between the increase in cash transfer programme coverage and a reduction in TB incidence rate. Our findings provide support for social protection interventions for tackling TB worldwide.

Solar radiation increases suicide rate after adjusting for other climate factors in South Korea.

PubMed

Jee, Hee-Jung; Cho, Chul-Hyun; Lee, Yu Jin; Choi, Nari; An, Hyonggin; Lee, Heon-Jeong

2017-03-01

Previous studies have indicated that suicide rates have significant seasonal variations. There is seasonal discordance between temperature and solar radiation due to the monsoon season in South Korea. We investigated the seasonality of suicide and assessed its association with climate variables in South Korea. Suicide rates were obtained from the National Statistical Office of South Korea, and climatic data were obtained from the Korea Meteorological Administration for the period of 1992-2010. We conducted analyses using a generalized additive model (GAM). First, we explored the seasonality of suicide and climate variables such as mean temperature, daily temperature range, solar radiation, and relative humidity. Next, we identified confounding climate variables associated with suicide rate. To estimate the adjusted effect of solar radiation on the suicide rate, we investigated the confounding variables using a multivariable GAM. Suicide rate showed seasonality with a pattern similar to that of solar radiation. We found that the suicide rate increased 1.008 times when solar radiation increased by 1 MJ/m 2 after adjusting for other confounding climate factors (P < 0.001). Solar radiation has a significant linear relationship with suicide after adjusting for region, other climate variables, and time trends. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Motor Variability Arises from a Slow Random Walk in Neural State

PubMed Central

Chaisanguanthum, Kris S.; Shen, Helen H.

2014-01-01

Even well practiced movements cannot be repeated without variability. This variability is thought to reflect “noise” in movement preparation or execution. However, we show that, for both professional baseball pitchers and macaque monkeys making reaching movements, motor variability can be decomposed into two statistical components, a slowly drifting mean and fast trial-by-trial fluctuations about the mean. The preparatory activity of dorsal premotor cortex/primary motor cortex neurons in monkey exhibits similar statistics. Although the neural and behavioral drifts appear to be correlated, neural activity does not account for trial-by-trial fluctuations in movement, which must arise elsewhere, likely downstream. The statistics of this drift are well modeled by a double-exponential autocorrelation function, with time constants similar across the neural and behavioral drifts in two monkeys, as well as the drifts observed in baseball pitching. These time constants can be explained by an error-corrective learning processes and agree with learning rates measured directly in previous experiments. Together, these results suggest that the central contributions to movement variability are not simply trial-by-trial fluctuations but are rather the result of longer-timescale processes that may arise from motor learning. PMID:25186752

Using complexity metrics with R-R intervals and BPM heart rate measures.

PubMed

Wallot, Sebastian; Fusaroli, Riccardo; Tylén, Kristian; Jegindø, Else-Marie

2013-01-01

Lately, growing attention in the health sciences has been paid to the dynamics of heart rate as indicator of impending failures and for prognoses. Likewise, in social and cognitive sciences, heart rate is increasingly employed as a measure of arousal, emotional engagement and as a marker of interpersonal coordination. However, there is no consensus about which measurements and analytical tools are most appropriate in mapping the temporal dynamics of heart rate and quite different metrics are reported in the literature. As complexity metrics of heart rate variability depend critically on variability of the data, different choices regarding the kind of measures can have a substantial impact on the results. In this article we compare linear and non-linear statistics on two prominent types of heart beat data, beat-to-beat intervals (R-R interval) and beats-per-min (BPM). As a proof-of-concept, we employ a simple rest-exercise-rest task and show that non-linear statistics-fractal (DFA) and recurrence (RQA) analyses-reveal information about heart beat activity above and beyond the simple level of heart rate. Non-linear statistics unveil sustained post-exercise effects on heart rate dynamics, but their power to do so critically depends on the type data that is employed: While R-R intervals are very susceptible to non-linear analyses, the success of non-linear methods for BPM data critically depends on their construction. Generally, "oversampled" BPM time-series can be recommended as they retain most of the information about non-linear aspects of heart beat dynamics.

Effects of head-down bed rest on complex heart rate variability: Response to LBNP testing

NASA Technical Reports Server (NTRS)

Goldberger, Ary L.; Mietus, Joseph E.; Rigney, David R.; Wood, Margie L.; Fortney, Suzanne M.

1994-01-01

Head-down bed rest is used to model physiological changes during spaceflight. We postulated that bed rest would decrease the degree of complex physiological heart rate variability. We analyzed continuous heart rate data from digitized Holter recordings in eight healthy female volunteers (age 28-34 yr) who underwent a 13-day 6 deg head-down bed rest study with serial lower body negative pressure (LBNP) trials. Heart rate variability was measured on a 4-min data sets using conventional time and frequency domain measures as well as with a new measure of signal 'complexity' (approximate entropy). Data were obtained pre-bed rest (control), during bed rest (day 4 and day 9 or 11), and 2 days post-bed rest (recovery). Tolerance to LBNP was significantly reduced on both bed rest days vs. pre-bed rest. Heart rate variability was assessed at peak LBNP. Heart rate approximate entropy was significantly decreased at day 4 and day 9 or 11, returning toward normal during recovery. Heart rate standard deviation and the ratio of high- to low-power frequency did not change significantly. We conclude that short-term bed rest is associated with a decrease in the complex variability of heart rate during LBNP testing in healthy young adult women. Measurement of heart rate complexity, using a method derived from nonlinear dynamics ('chaos theory'), may provide a sensitive marker of this loss of physiological variability, complementing conventional time and frequency domain statistical measures.

Statistical interpretation of machine learning-based feature importance scores for biomarker discovery.

PubMed

Huynh-Thu, Vân Anh; Saeys, Yvan; Wehenkel, Louis; Geurts, Pierre

2012-07-01

Univariate statistical tests are widely used for biomarker discovery in bioinformatics. These procedures are simple, fast and their output is easily interpretable by biologists but they can only identify variables that provide a significant amount of information in isolation from the other variables. As biological processes are expected to involve complex interactions between variables, univariate methods thus potentially miss some informative biomarkers. Variable relevance scores provided by machine learning techniques, however, are potentially able to highlight multivariate interacting effects, but unlike the p-values returned by univariate tests, these relevance scores are usually not statistically interpretable. This lack of interpretability hampers the determination of a relevance threshold for extracting a feature subset from the rankings and also prevents the wide adoption of these methods by practicians. We evaluated several, existing and novel, procedures that extract relevant features from rankings derived from machine learning approaches. These procedures replace the relevance scores with measures that can be interpreted in a statistical way, such as p-values, false discovery rates, or family wise error rates, for which it is easier to determine a significance level. Experiments were performed on several artificial problems as well as on real microarray datasets. Although the methods differ in terms of computing times and the tradeoff, they achieve in terms of false positives and false negatives, some of them greatly help in the extraction of truly relevant biomarkers and should thus be of great practical interest for biologists and physicians. As a side conclusion, our experiments also clearly highlight that using model performance as a criterion for feature selection is often counter-productive. Python source codes of all tested methods, as well as the MATLAB scripts used for data simulation, can be found in the Supplementary Material.

High Variability in Cellular Stoichiometry of Carbon, Nitrogen, and Phosphorus Within Classes of Marine Eukaryotic Phytoplankton Under Sufficient Nutrient Conditions.

PubMed

Garcia, Nathan S; Sexton, Julie; Riggins, Tracey; Brown, Jeff; Lomas, Michael W; Martiny, Adam C

2018-01-01

Current hypotheses suggest that cellular elemental stoichiometry of marine eukaryotic phytoplankton such as the ratios of cellular carbon:nitrogen:phosphorus (C:N:P) vary between phylogenetic groups. To investigate how phylogenetic structure, cell volume, growth rate, and temperature interact to affect the cellular elemental stoichiometry of marine eukaryotic phytoplankton, we examined the C:N:P composition in 30 isolates across 7 classes of marine phytoplankton that were grown with a sufficient supply of nutrients and nitrate as the nitrogen source. The isolates covered a wide range in cell volume (5 orders of magnitude), growth rate (<0.01-0.9 d -1 ), and habitat temperature (2-24°C). Our analysis indicates that C:N:P is highly variable, with statistical model residuals accounting for over half of the total variance and no relationship between phylogeny and elemental stoichiometry. Furthermore, our data indicated that variability in C:P, N:P, and C:N within Bacillariophyceae (diatoms) was as high as that among all of the isolates that we examined. In addition, a linear statistical model identified a positive relationship between diatom cell volume and C:P and N:P. Among all of the isolates that we examined, the statistical model identified temperature as a significant factor, consistent with the temperature-dependent translation efficiency model, but temperature only explained 5% of the total statistical model variance. While some of our results support data from previous field studies, the high variability of elemental ratios within Bacillariophyceae contradicts previous work that suggests that this cosmopolitan group of microalgae has consistently low C:P and N:P ratios in comparison with other groups.

Forecasting daily source air quality using multivariate statistical analysis and radial basis function networks.

PubMed

Sun, Gang; Hoff, Steven J; Zelle, Brian C; Nelson, Minda A

2008-12-01

It is vital to forecast gas and particle matter concentrations and emission rates (GPCER) from livestock production facilities to assess the impact of airborne pollutants on human health, ecological environment, and global warming. Modeling source air quality is a complex process because of abundant nonlinear interactions between GPCER and other factors. The objective of this study was to introduce statistical methods and radial basis function (RBF) neural network to predict daily source air quality in Iowa swine deep-pit finishing buildings. The results show that four variables (outdoor and indoor temperature, animal units, and ventilation rates) were identified as relative important model inputs using statistical methods. It can be further demonstrated that only two factors, the environment factor and the animal factor, were capable of explaining more than 94% of the total variability after performing principal component analysis. The introduction of fewer uncorrelated variables to the neural network would result in the reduction of the model structure complexity, minimize computation cost, and eliminate model overfitting problems. The obtained results of RBF network prediction were in good agreement with the actual measurements, with values of the correlation coefficient between 0.741 and 0.995 and very low values of systemic performance indexes for all the models. The good results indicated the RBF network could be trained to model these highly nonlinear relationships. Thus, the RBF neural network technology combined with multivariate statistical methods is a promising tool for air pollutant emissions modeling.

Access to health care and community social capital.

PubMed

Hendryx, Michael S; Ahern, Melissa M; Lovrich, Nicholas P; McCurdy, Arthur H

2002-02-01

To test the hypothesis that variation in reported access to health care is positively related to the level of social capital present in a community. The 1996 Household Survey of the Community Tracking Study, drawn from 22 metropolitan statistical areas across the United States (n = 19,672). Additional data for the 22 communities are from a 1996 multicity broadcast media marketing database, including key social capital indicators, the 1997 National Profile of Local Health Departments survey, and Interstudy, American Hospital Association, and American Medical Association sources. The design is cross-sectional. Self-reported access to care problems is the dependent variable. Independent variables include individual sociodemographic variables, community-level health sector variables, and social capital variables. Data are merged from the various sources and weighted to be population representative and are analyzed using hierarchical categorical modeling. Persons who live in metropolitan statistical areas featuring higher levels of social capital report fewer problems accessing health care. A higher HMO penetration rate in a metropolitan statistical area was also associated with fewer access problems. Other health sector variables were not related to health care access. The results observed for 22 major U.S. cities are consistent with the hypothesis that community social capital enables better access to care, perhaps through improving community accountability mechanisms.

Do HMO penetration and hospital competition impact quality of hospital care?

PubMed

Rivers, P A; Fottler, M D

2004-11-01

This study examines the impact of HMO penetration and competition on hospital markets. A modified structure-conduct-performance paradigm was applied to the health care industry in order to investigate the impact of HMO penetration and competition on risk-adjusted hospital mortality rates (i.e. quality of hospital care). Secondary data for 1957 acute care hospitals in the USA from the 1991 American Hospital Association's Annual Survey of Hospitals were used. The outcome variables were risk-adjusted mortality rates in 1991. Predictor variables were market characteristics (i.e. managed care penetration and hospital competition). Control variables were environmental, patient, and institutional characteristics. Associations between predictor and outcome variables were investigated using statistical regression techniques. Hospital competition had a negative relationship with risk-adjusted mortality rates (a negative indicator of quality of care). HMO penetration, hospital competition, and an interaction effect of HMO penetration and competition were not found to have significant effects on risk-adjusted mortality rates. These findings suggest that when faced with intense competition, hospitals may respond in ways associated with reducing their mortality rates.

Quantifying variation in speciation and extinction rates with clade data.

PubMed

Paradis, Emmanuel; Tedesco, Pablo A; Hugueny, Bernard

2013-12-01

High-level phylogenies are very common in evolutionary analyses, although they are often treated as incomplete data. Here, we provide statistical tools to analyze what we name "clade data," which are the ages of clades together with their numbers of species. We develop a general approach for the statistical modeling of variation in speciation and extinction rates, including temporal variation, unknown variation, and linear and nonlinear modeling. We show how this approach can be generalized to a wide range of situations, including testing the effects of life-history traits and environmental variables on diversification rates. We report the results of an extensive simulation study to assess the performance of some statistical tests presented here as well as of the estimators of speciation and extinction rates. These latter results suggest the possibility to estimate correctly extinction rate in the absence of fossils. An example with data on fish is presented. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.

Detection of outliers in the response and explanatory variables of the simple circular regression model

NASA Astrophysics Data System (ADS)

Mahmood, Ehab A.; Rana, Sohel; Hussin, Abdul Ghapor; Midi, Habshah

2016-06-01

The circular regression model may contain one or more data points which appear to be peculiar or inconsistent with the main part of the model. This may be occur due to recording errors, sudden short events, sampling under abnormal conditions etc. The existence of these data points "outliers" in the data set cause lot of problems in the research results and the conclusions. Therefore, we should identify them before applying statistical analysis. In this article, we aim to propose a statistic to identify outliers in the both of the response and explanatory variables of the simple circular regression model. Our proposed statistic is robust circular distance RCDxy and it is justified by the three robust measurements such as proportion of detection outliers, masking and swamping rates.

Microscopic saw mark analysis: an empirical approach.

PubMed

Love, Jennifer C; Derrick, Sharon M; Wiersema, Jason M; Peters, Charles

2015-01-01

Microscopic saw mark analysis is a well published and generally accepted qualitative analytical method. However, little research has focused on identifying and mitigating potential sources of error associated with the method. The presented study proposes the use of classification trees and random forest classifiers as an optimal, statistically sound approach to mitigate the potential for error of variability and outcome error in microscopic saw mark analysis. The statistical model was applied to 58 experimental saw marks created with four types of saws. The saw marks were made in fresh human femurs obtained through anatomical gift and were analyzed using a Keyence digital microscope. The statistical approach weighed the variables based on discriminatory value and produced decision trees with an associated outcome error rate of 8.62-17.82%. © 2014 American Academy of Forensic Sciences.

Statistical methods of estimating mining costs

USGS Publications Warehouse

Long, K.R.

2011-01-01

Until it was defunded in 1995, the U.S. Bureau of Mines maintained a Cost Estimating System (CES) for prefeasibility-type economic evaluations of mineral deposits and estimating costs at producing and non-producing mines. This system had a significant role in mineral resource assessments to estimate costs of developing and operating known mineral deposits and predicted undiscovered deposits. For legal reasons, the U.S. Geological Survey cannot update and maintain CES. Instead, statistical tools are under development to estimate mining costs from basic properties of mineral deposits such as tonnage, grade, mineralogy, depth, strip ratio, distance from infrastructure, rock strength, and work index. The first step was to reestimate "Taylor's Rule" which relates operating rate to available ore tonnage. The second step was to estimate statistical models of capital and operating costs for open pit porphyry copper mines with flotation concentrators. For a sample of 27 proposed porphyry copper projects, capital costs can be estimated from three variables: mineral processing rate, strip ratio, and distance from nearest railroad before mine construction began. Of all the variables tested, operating costs were found to be significantly correlated only with strip ratio.

[Instruments for quantitative methods of nursing research].

PubMed

Vellone, E

2000-01-01

Instruments for quantitative nursing research are a mean to objectify and measure a variable or a phenomenon in the scientific research. There are direct instruments to measure concrete variables and indirect instruments to measure abstract concepts (Burns, Grove, 1997). Indirect instruments measure the attributes by which a concept is made of. Furthermore, there are instruments for physiologic variables (e.g. for the weight), observational instruments (Check-lists e Rating Scales), interviews, questionnaires, diaries and the scales (Check-lists, Rating Scales, Likert Scales, Semantic Differential Scales e Visual Anologue Scales). The choice to select an instrument or another one depends on the research question and design. Instruments research are very useful in research both to describe the variables and to see statistical significant relationships. Very carefully should be their use in the clinical practice for diagnostic assessment.

Predictors of workplace violence among female sex workers in Tijuana, Mexico.

PubMed

Katsulis, Yasmina; Durfee, Alesha; Lopez, Vera; Robillard, Alyssa

2015-05-01

For sex workers, differences in rates of exposure to workplace violence are likely influenced by a variety of risk factors, including where one works and under what circumstances. Economic stressors, such as housing insecurity, may also increase the likelihood of exposure. Bivariate analyses demonstrate statistically significant associations between workplace violence and selected predictor variables, including age, drug use, exchanging sex for goods, soliciting clients outdoors, and experiencing housing insecurity. Multivariate regression analysis shows that after controlling for each of these variables in one model, only soliciting clients outdoors and housing insecurity emerge as statistically significant predictors for workplace violence. © The Author(s) 2014.

Optimization and formulation design of gels of Diclofenac and Curcumin for transdermal drug delivery by Box-Behnken statistical design.

PubMed

Chaudhary, Hema; Kohli, Kanchan; Amin, Saima; Rathee, Permender; Kumar, Vikash

2011-02-01

The aim of this study was to develop and optimize a transdermal gel formulation for Diclofenac diethylamine (DDEA) and Curcumin (CRM). A 3-factor, 3-level Box-Behnken design was used to derive a second-order polynomial equation to construct contour plots for prediction of responses. Independent variables studied were the polymer concentration (X(1)), ethanol (X(2)) and propylene glycol (X(3)) and the levels of each factor were low, medium, and high. The dependent variables studied were the skin permeation rate of DDEA (Y(1)), skin permeation rate of CRM (Y(2)), and viscosity of the gels (Y(3)). Response surface plots were drawn, statistical validity of the polynomials was established to find the compositions of optimized formulation which was evaluated using the Franz-type diffusion cell. The permeation rate of DDEA increased proportionally with ethanol concentration but decreased with polymer concentration, whereas the permeation rate of CRM increased proportionally with polymer concentration. Gels showed a non-Fickian super case II (typical zero order) and non-Fickian diffusion release mechanism for DDEA and CRM, respectively. The design demonstrated the role of the derived polynomial equation and contour plots in predicting the values of dependent variables for the preparation and optimization of gel formulation for transdermal drug release. Copyright © 2010 Wiley-Liss, Inc.

Chronic effects of workplace noise on blood pressure and heart rate.

PubMed

Lusk, Sally L; Hagerty, Bonnie M; Gillespie, Brenda; Caruso, Claire C

2002-01-01

Environmental noise levels in the United States are increasing, yet there are few studies in which the nonauditory effects of workplace noise are assessed. In the current study, the authors examined chronic effects of noise on blood pressure and heart rate in 374 workers at an automobile plant. Data were collected from subjects prior to the start of their workshift. Participants completed questionnaires about diet, alcohol use, lifestyle, noise annoyance, use of hearing protection, noise exposure outside of the work environment, personal and family health histories, and demographic information. Resting blood pressure, heart rate, and body mass index were obtained. Noise exposure levels were extracted retrospectively from company records for each participant for the past 5 yr. Summary statistics were generated for each variable, and the authors performed bivariate correlations to identify any unadjusted associations. The authors then completed statistical modeling to investigate the effects of noise on blood pressure and heart rate, after they controlled for other variables (e.g., gender, race, age). The authors controlled for confounding variables, after which use of hearing protection in high-noise areas was a significant predictor of a decrease in both systolic and diastolic blood pressures. The results suggested that the reduction of noise exposure by means of engineering controls or by consistent use of hearing protection by workers may positively affect health outcomes.

Role of Biofeedback in Optimizing Psychomotor Performance in Sports

PubMed Central

Paul, Maman; Garg, Kanupriya; Singh Sandhu, Jaspal

2012-01-01

Purpose Biofeedback is an emerging tool to acquire and facilitate physiological and psychological domains of the human body like response time and concentration. Thus, the present study aims at determining the reconstitution of psychomotor and performance skills in basketball players through biofeedback training. Methods Basketball players (N=30) with different levels of expertise (university, state and national) aged 18-28 years (both male and female) were randomly divided into 3 equal groups - Experimental group, Placebo group and Control group. The experimental group received Heart Rate Variability Biofeedback training for 10 consecutive days for 20 minutes that included breathing at individual's resonant frequency through a pacing stimulus; Placebo group was shown motivational video clips for 10 consecutive days for 10 minutes, whereas Control group was not given any intervention. At session 1, 10 and 1month follow up, heart rate variability, respiration rate, response time (reaction and movement time), concentration and shooting performance were assessed. Results Two way repeated measure ANOVA was used to simultaneously compare within and between group differences. Response time, concentration, heart rate variability, respiration rate and shooting differences were statistically significant in each group along with interaction of group and time (P<0.001). Also, all the measures showed statistically significant inter group difference (P<0.05). Conclusion The results of the study suggest that biofeedback training may help to train stressed athletes to acquire a control over their psychophysiological processes, thus helping an athlete to perform maximally. PMID:22461963

Hydrocortisone at stress-associated concentrations helps maintain human heart rate variability during subsequent endotoxin challenge.

PubMed

Rassias, Athos J; Guyre, Paul M; Yeager, Mark P

2011-12-01

We evaluated the differential impact of stress-associated vs high pharmacologic concentrations of hydrocortisone pretreatment on heart rate variability (HRV) during a subsequent systemic inflammatory stimulus. Healthy volunteers were randomized to receive placebo (Control) and hydrocortisone at 1.5 μg/kg per minute (STRESS) or at 3.0 μg/kg per minute (PHARM) as a 6-hour infusion. The STRESS dose was chosen to replicate the condition of physiologic adrenal cortical output during acute systemic stress. The PHARM dose was chosen to induce a supraphysiologic concentration of cortisol. The next day, all subjects received 2 ng/kg Escherichia coli endotoxin (lipopolysaccharide). Heart rate variability was analyzed with the statistic approximate entropy (ApEn). A lower ApEn correlates with decreased HRV. At the 3-hour nadir, the decrease in ApEn in the STRESS group was significantly less compared to placebo (P < .03), whereas ApEn in the PHARM group was not statistically different. We also found that the maximal decrease in ApEn preceded maximal increase in heart rate in all groups. The decrease in R-R interval was maximal at 4 hours, whereas the ApEn nadir was 1 hour earlier at 3 hours. Pretreatment with a stress dose of hydrocortisone but not a higher pharmacologic dose maintained a significantly higher ApEn after endotoxin exposure when compared to a placebo. In addition, decreases in ApEn preceded increases in heart rate. Copyright © 2011 Elsevier Inc. All rights reserved.

An Evaluation of the Euroncap Crash Test Safety Ratings in the Real World

PubMed Central

Segui-Gomez, Maria; Lopez-Valdes, Francisco J.; Frampton, Richard

2007-01-01

We investigated whether the rating obtained in the EuroNCAP test procedures correlates with injury protection to vehicle occupants in real crashes using data in the UK Cooperative Crash Injury Study (CCIS) database from 1996 to 2005. Multivariate Poisson regression models were developed, using the Abbreviated Injury Scale (AIS) score by body region as the dependent variable and the EuroNCAP score for that particular body region, seat belt use, mass ratio and Equivalent Test Speed (ETS) as independent variables. Our models identified statistically significant relationships between injury severity and safety belt use, mass ratio and ETS. We could not identify any statistically significant relationships between the EuroNCAP body region scores and real injury outcome except for the protection to pelvis-femur-knee in frontal impacts where scoring “green” is significantly better than scoring “yellow” or “red”.

Adaptive distributed source coding.

PubMed

Varodayan, David; Lin, Yao-Chung; Girod, Bernd

2012-05-01

We consider distributed source coding in the presence of hidden variables that parameterize the statistical dependence among sources. We derive the Slepian-Wolf bound and devise coding algorithms for a block-candidate model of this problem. The encoder sends, in addition to syndrome bits, a portion of the source to the decoder uncoded as doping bits. The decoder uses the sum-product algorithm to simultaneously recover the source symbols and the hidden statistical dependence variables. We also develop novel techniques based on density evolution (DE) to analyze the coding algorithms. We experimentally confirm that our DE analysis closely approximates practical performance. This result allows us to efficiently optimize parameters of the algorithms. In particular, we show that the system performs close to the Slepian-Wolf bound when an appropriate doping rate is selected. We then apply our coding and analysis techniques to a reduced-reference video quality monitoring system and show a bit rate saving of about 75% compared with fixed-length coding.

The Effects of Word Processing Software on User Satisfaction: An Empirical Study of Micro, Mini, and Mainframe Computers Using an Interactive Artificial Intelligence Expert-System.

ERIC Educational Resources Information Center

Rushinek, Avi; Rushinek, Sara

1984-01-01

Describes results of a system rating study in which users responded to WPS (word processing software) questions. Study objectives were data collection and evaluation of variables; statistical quantification of WPS's contribution (along with other variables) to user satisfaction; design of an expert system to evaluate WPS; and database update and…

The dynamic conditional relationship between stock market returns and implied volatility

NASA Astrophysics Data System (ADS)

Park, Sung Y.; Ryu, Doojin; Song, Jeongseok

2017-09-01

Using the dynamic conditional correlation multivariate generalized autoregressive conditional heteroskedasticity (DCC-MGARCH) model, we empirically examine the dynamic relationship between stock market returns (KOSPI200 returns) and implied volatility (VKOSPI), as well as their statistical mechanics, in the Korean market, a representative and leading emerging market. We consider four macroeconomic variables (exchange rates, risk-free rates, term spreads, and credit spreads) as potential determinants of the dynamic conditional correlation between returns and volatility. Of these macroeconomic variables, the change in exchange rates has a significant impact on the dynamic correlation between KOSPI200 returns and the VKOSPI, especially during the recent financial crisis. We also find that the risk-free rate has a marginal effect on this dynamic conditional relationship.

A Stochastic Model of Space-Time Variability of Mesoscale Rainfall: Statistics of Spatial Averages

NASA Technical Reports Server (NTRS)

Kundu, Prasun K.; Bell, Thomas L.

2003-01-01

A characteristic feature of rainfall statistics is that they depend on the space and time scales over which rain data are averaged. A previously developed spectral model of rain statistics that is designed to capture this property, predicts power law scaling behavior for the second moment statistics of area-averaged rain rate on the averaging length scale L as L right arrow 0. In the present work a more efficient method of estimating the model parameters is presented, and used to fit the model to the statistics of area-averaged rain rate derived from gridded radar precipitation data from TOGA COARE. Statistical properties of the data and the model predictions are compared over a wide range of averaging scales. An extension of the spectral model scaling relations to describe the dependence of the average fraction of grid boxes within an area containing nonzero rain (the "rainy area fraction") on the grid scale L is also explored.

gHRV: Heart rate variability analysis made easy.

PubMed

Rodríguez-Liñares, L; Lado, M J; Vila, X A; Méndez, A J; Cuesta, P

2014-08-01

In this paper, the gHRV software tool is presented. It is a simple, free and portable tool developed in python for analysing heart rate variability. It includes a graphical user interface and it can import files in multiple formats, analyse time intervals in the signal, test statistical significance and export the results. This paper also contains, as an example of use, a clinical analysis performed with the gHRV tool, namely to determine whether the heart rate variability indexes change across different stages of sleep. Results from tests completed by researchers who have tried gHRV are also explained: in general the application was positively valued and results reflect a high level of satisfaction. gHRV is in continuous development and new versions will include suggestions made by testers. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

The Acute Effects of Aerobic Exercise on Cognitive Flexibility and Task-Related Heart Rate Variability in Children With ADHD and Healthy Controls.

PubMed

Ludyga, Sebastian; Gerber, Markus; Mücke, Manuel; Brand, Serge; Weber, Peter; Brotzmann, Mark; Pühse, Uwe

2018-02-01

To investigate cognitive flexibility and task-related heart rate variability following moderately intense aerobic exercise and after watching a video in both children with ADHD and healthy controls. Using a cross-over design, participants completed cognitive assessments following exercise and a physically inactive control condition. Behavioral performance was assessed using the Alternate Uses task. Heart rate variability was recorded via electrocardiography during the cognitive task. The statistical analysis revealed that in comparison with the control condition, both groups showed higher cognitive flexibility following aerobic exercise. Moreover, decreased low frequency and high frequency power was observed in the exercise condition. The findings suggest that exercise elicits similar benefits for cognitive flexibility in children with ADHD and healthy controls, partly due to an increase in arousal induced by parasympathetic withdrawal.

Sports practice is related to parasympathetic activity in adolescents

PubMed Central

Cayres, Suziane Ungari; Vanderlei, Luiz Carlos Marques; Rodrigues, Aristides Machado; Coelho e Silva, Manuel João; Codogno, Jamile Sanches; Barbosa, Maurício Fregonesi; Fernandes, Rômulo Araújo

2015-01-01

OBJECTIVE: To analyze the relationship among sports practice, physical education class, habitual physical activity and cardiovascular risk in adolescents. METHODS: Cross-sectional study with 120 schoolchildren (mean: 11.7±0.7 years old), with no regular use of medicines. Sports practice and physical education classes were assessed through face-to-face interview, while habitual physical activity was assessed by pedometers. Bodyweight, height and height-cephalic trunk were used to estimate maturation. The following variables were measured: body fatness, blood pressure, resting heart rate, blood flow velocity, intima-media thickness (carotid and femoral) and heart rate variability (mean between consecutive heartbeats and statistical index in the time domain that show the autonomic parasympathetic nervous system activity root-mean by the square of differences between adjacent normal R-R intervals in a time interval). Statistical treatment used Spearman correlation adjusted by sex, ethnicity, age, body fatness and maturation. RESULTS: Independently of potential confounders, sports practice was positively related to autonomic parasympathetic nervous system activity (β=0.039 [0.01; 0.76]). On the other hand, the relationship between sport practice and mean between consecutive heartbeats (β=0,031 [-0.01; 0.07]) was significantly mediated by biological maturation. CONCLUSIONS: Sport practice was related to higher heart rate variability at rest. PMID:25887927

Application of statistical experimental design to study the formulation variables influencing the coating process of lidocaine liposomes.

PubMed

González-Rodríguez, M L; Barros, L B; Palma, J; González-Rodríguez, P L; Rabasco, A M

2007-06-07

In this paper, we have used statistical experimental design to investigate the effect of several factors in coating process of lidocaine hydrochloride (LID) liposomes by a biodegradable polymer (chitosan, CH). These variables were the concentration of CH coating solution, the dripping rate of this solution on the liposome colloidal dispersion, the stirring rate, the time since the liposome production to the liposome coating and finally the amount of drug entrapped into liposomes. The selected response variables were drug encapsulation efficiency (EE, %), coating efficiency (CE, %) and zeta potential. Liposomes were obtained by thin-layer evaporation method. They were subsequently coated with CH according the experimental plan provided by a fractional factorial (2(5-1)) screening matrix. We have used spectroscopic methods to determine the zeta potential values. The EE (%) assay was carried out in dialysis bags and the brilliant red probe was used to determine CE (%) due to its property of forming molecular complexes with CH. The graphic analysis of the effects allowed the identification of the main formulation and technological factors by the analysis of the selected responses and permitted the determination of the proper level of these factors for the response improvement. Moreover, fractional design allowed quantifying the interactions between the factors, which will consider in next experiments. The results obtained pointed out that LID amount was the predominant factor that increased the drug entrapment capacity (EE). The CE (%) response was mainly affected by the concentration of the CH solution and the stirring rate, although all the interactions between the main factors have statistical significance.

The Effect of Live Spontaneous Harp Music on Patients in the Intensive Care Unit

PubMed Central

Chiasson, Ann Marie; Linda Baldwin, Ann; Mclaughlin, Carrol; Cook, Paula; Sethi, Gulshan

2013-01-01

This study was performed to investigate the effect of live, spontaneous harp music on individual patients in an intensive care unit (ICU), either pre- or postoperatively. The purpose was to determine whether this intervention would serve as a relaxation or healing modality, as evidenced by the effect on patient's pain, heart rate, respiratory rate, blood pressure, oxygen saturation, and heart rate variability. Each consenting patient was randomly assigned to receive either a live 10-minute concert of spontaneous music played by an expert harpist or a 10-minute rest period. Spontaneous harp music significantly decreased patient perception of pain by 27% but did not significantly affect heart rate, respiratory rate, oxygen saturation, blood pressure, or heart rate variability. Trends emerged, although being not statistically significant, that systolic blood pressure increased while heart rate variability decreased. These findings may invoke patient engagement, as opposed to relaxation, as the underlying mechanism of the decrease in the patients' pain and of the healing benefit that arises from the relationship between healer, healing modality, and patient. PMID:24371459

Examining the Relationship Between Passenger Airline Aircraft Maintenance Outsourcing and Aircraft Safety

NASA Astrophysics Data System (ADS)

Monaghan, Kari L.

The problem addressed was the concern for aircraft safety rates as they relate to the rate of maintenance outsourcing. Data gathered from 14 passenger airlines: AirTran, Alaska, America West, American, Continental, Delta, Frontier, Hawaiian, JetBlue, Midwest, Northwest, Southwest, United, and USAir covered the years 1996 through 2008. A quantitative correlational design, utilizing Pearson's correlation coefficient, and the coefficient of determination were used in the present study to measure the correlation between variables. Elements of passenger airline aircraft maintenance outsourcing and aircraft accidents, incidents, and pilot deviations within domestic passenger airline operations were analyzed, examined, and evaluated. Rates of maintenance outsourcing were analyzed to determine the association with accident, incident, and pilot deviation rates. Maintenance outsourcing rates used in the evaluation were the yearly dollar expenditure of passenger airlines for aircraft maintenance outsourcing as they relate to the total airline aircraft maintenance expenditures. Aircraft accident, incident, and pilot deviation rates used in the evaluation were the yearly number of accidents, incidents, and pilot deviations per miles flown. The Pearson r-values were calculated to measure the linear relationship strength between the variables. There were no statistically significant correlation findings for accidents, r(174)=0.065, p=0.393, and incidents, r(174)=0.020, p=0.793. However, there was a statistically significant correlation for pilot deviation rates, r(174)=0.204, p=0.007 thus indicating a statistically significant correlation between maintenance outsourcing rates and pilot deviation rates. The calculated R square value of 0.042 represents the variance that can be accounted for in aircraft pilot deviation rates by examining the variance in aircraft maintenance outsourcing rates; accordingly, 95.8% of the variance is unexplained. Suggestions for future research include replication of the present study with the inclusion of maintenance outsourcing rate data for all airlines differentiated between domestic and foreign repair station utilization. Replication of the present study every five years is also encouraged to continue evaluating the impact of maintenance outsourcing practices on passenger airline safety.

Use of Angiotensin-Converting Enzyme Inhibitors and Angiotensin Receptor Blockers for Geriatric Ischemic Stroke Patients: Are the Rates Right?

PubMed

Brooks, John M; Chapman, Cole G; Suneja, Manish; Schroeder, Mary C; Fravel, Michelle A; Schneider, Kathleen M; Wilwert, June; Li, Yi-Jhen; Chrischilles, Elizabeth A; Brenton, Douglas W; Brenton, Marian; Robinson, Jennifer

2018-05-30

Our objective is to estimate the effects associated with higher rates of renin-angiotensin system antagonists, angiotensin-converting enzyme inhibitors and angiotensin receptor blockers (ACEI/ARBs), in secondary prevention for geriatric (aged >65 years) patients with new ischemic strokes by chronic kidney disease (CKD) status. The effects of ACEI/ARBs on survival and renal risk were estimated by CKD status using an instrumental variable (IV) estimator. Instruments were based on local area variation in ACEI/ARB use. Data abstracted from charts were used to assess the assumptions underlying the instrumental estimator. ACEI/ARBs were used after stroke by 45.9% and 45.2% of CKD and non-CKD patients, respectively. ACEI/ARB rate differences across local areas grouped by practice styles were nearly identical for CKD and non-CKD patients. Higher ACEI/ARB use rates for non-CKD patients were associated with higher 2-year survival rates, whereas higher ACEI/ARB use rates for patients with CKD were associated with lower 2-year survival rates. While the negative survival estimates for patients with CKD were not statistically different from zero, they were statistically lower than the estimates for non-CKD patients. Confounders abstracted from charts were not associated with the instrumental variable used. Higher ACEI/ARB use rates had different survival implications for older ischemic stroke patients with and without CKD. ACEI/ARBs appear underused in ischemic stroke patients without CKD as higher use rates were associated with higher 2-year survival rates. This conclusion is not generalizable to the ischemic stroke patients with CKD, as higher ACEI/ARBS use rates were associated with lower 2-year survival rates that were statistically lower than the estimates for non-CKD patients. © 2018 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Microprocessor-based long term cardiorespirography. II. Status evaluation in term and premature newborns.

PubMed

Hörnchen, H; Betz, R; Kotlarek, F; Roebruck, P

1983-01-01

In 1965 URBACH et al. and RUDOLPH et al. [35, 39] described a loss of heart rate variability in severely ill neonates. In this study we investigated the correlation between instantaneous heart rate patterns and status diagnosis. We used a microprocessor-based cardiorespirography system. Seventy five newborn infants (51 prematures and 24 term neonates) were studied for about 12 hours each. Twenty nine patients had a second record after the first investigation. Parameters were: Type of frequency and oscillation, long time variability (LTV), short time variability (STV) and the newly introduced P-value (maximal difference between two successive R-peaks in five minutes). We found clear differences between the study groups. With increasing severity of illness mean values ("group mean values") of long time variability, short time variability and P-value decreased. Fixed heart rate became predominant. The most pronounced loss of heart rate variability was seen in infants with severe intracranial bleeding, thus offering a tentative diagnosis. For statistical analysis long time variability and the silent oscillation type have been proved as best parameters for this diagnosis. Severely decreased heart rate variations also have been seen in infants with acute renal failure--possibly because of brain edema--, after application of muscle relaxants, repeated doses of sedatives, and after prolonged anesthesia. Otherwise, the heart rate variability was probably dependent on age and gestational age in prematures and newborn infants without intracranial bleeding. It is possible to use microprocessor-based long time cardiorespirography as a simple screening method for the diagnosis of neonatal intracerebral bleeding. In future experiences transcutaneous measurements of oxygen tension should be included.

Ambiguities and conflicting results: the limitations of the kappa statistic in establishing the interrater reliability of the Irish nursing minimum data set for mental health: a discussion paper.

PubMed

Morris, Roisin; MacNeela, Padraig; Scott, Anne; Treacy, Pearl; Hyde, Abbey; O'Brien, Julian; Lehwaldt, Daniella; Byrne, Anne; Drennan, Jonathan

2008-04-01

In a study to establish the interrater reliability of the Irish Nursing Minimum Data Set (I-NMDS) for mental health difficulties relating to the choice of reliability test statistic were encountered. The objective of this paper is to highlight the difficulties associated with testing interrater reliability for an ordinal scale using a relatively homogenous sample and the recommended kw statistic. One pair of mental health nurses completed the I-NMDS for mental health for a total of 30 clients attending a mental health day centre over a two-week period. Data was analysed using the kw and percentage agreement statistics. A total of 34 of the 38 I-NMDS for mental health variables with lower than acceptable levels of kw reliability scores achieved acceptable levels of reliability according to their percentage agreement scores. The study findings implied that, due to the homogeneity of the sample, low variability within the data resulted in the 'base rate problem' associated with the use of kw statistic. Conclusions point to the interpretation of kw in tandem with percentage agreement scores. Suggestions that kw scores were low due to chance agreement and that one should strive to use a study sample with known variability are queried.

Framework for making better predictions by directly estimating variables’ predictivity

PubMed Central

Chernoff, Herman; Lo, Shaw-Hwa

2016-01-01

We propose approaching prediction from a framework grounded in the theoretical correct prediction rate of a variable set as a parameter of interest. This framework allows us to define a measure of predictivity that enables assessing variable sets for, preferably high, predictivity. We first define the prediction rate for a variable set and consider, and ultimately reject, the naive estimator, a statistic based on the observed sample data, due to its inflated bias for moderate sample size and its sensitivity to noisy useless variables. We demonstrate that the I-score of the PR method of VS yields a relatively unbiased estimate of a parameter that is not sensitive to noisy variables and is a lower bound to the parameter of interest. Thus, the PR method using the I-score provides an effective approach to selecting highly predictive variables. We offer simulations and an application of the I-score on real data to demonstrate the statistic’s predictive performance on sample data. We conjecture that using the partition retention and I-score can aid in finding variable sets with promising prediction rates; however, further research in the avenue of sample-based measures of predictivity is much desired. PMID:27911830

Relationship of suicide rates with climate and economic variables in Europe during 2000-2012.

PubMed

Fountoulakis, Konstantinos N; Chatzikosta, Isaia; Pastiadis, Konstantinos; Zanis, Prodromos; Kawohl, Wolfram; Kerkhof, Ad J F M; Navickas, Alvydas; Höschl, Cyril; Lecic-Tosevski, Dusica; Sorel, Eliot; Rancans, Elmars; Palova, Eva; Juckel, Georg; Isacsson, Goran; Jagodic, Helena Korosec; Botezat-Antonescu, Ileana; Rybakowski, Janusz; Azorin, Jean Michel; Cookson, John; Waddington, John; Pregelj, Peter; Demyttenaere, Koen; Hranov, Luchezar G; Stevovic, Lidija Injac; Pezawas, Lucas; Adida, Marc; Figuera, Maria Luisa; Jakovljević, Miro; Vichi, Monica; Perugi, Giulio; Andreassen, Ole A; Vukovic, Olivera; Mavrogiorgou, Paraskevi; Varnik, Peeter; Dome, Peter; Winkler, Petr; Salokangas, Raimo K R; From, Tiina; Danileviciute, Vita; Gonda, Xenia; Rihmer, Zoltan; Forsman, Jonas; Grady, Anne; Hyphantis, Thomas; Dieset, Ingrid; Soendergaard, Susan; Pompili, Maurizio; Bech, Per

2016-01-01

It is well known that suicidal rates vary considerably among European countries and the reasons for this are unknown, although several theories have been proposed. The effect of economic variables has been extensively studied but not that of climate. Data from 29 European countries covering the years 2000-2012 and concerning male and female standardized suicidal rates (according to WHO), economic variables (according World Bank) and climate variables were gathered. The statistical analysis included cluster and principal component analysis and categorical regression. The derived models explained 62.4 % of the variability of male suicidal rates. Economic variables alone explained 26.9 % and climate variables 37.6 %. For females, the respective figures were 41.7, 11.5 and 28.1 %. Male suicides correlated with high unemployment rate in the frame of high growth rate and high inflation and low GDP per capita, while female suicides correlated negatively with inflation. Both male and female suicides correlated with low temperature. The current study reports that the climatic effect (cold climate) is stronger than the economic one, but both are present. It seems that in Europe suicidality follows the climate/temperature cline which interestingly is not from south to north but from south to north-east. This raises concerns that climate change could lead to an increase in suicide rates. The current study is essentially the first successful attempt to explain the differences across countries in Europe; however, it is an observational analysis based on aggregate data and thus there is a lack of control for confounders.

24 CFR 1000.330 - What are the data sources for the need variables?

Code of Federal Regulations, 2010 CFR

2010-04-01

... need data is collected, using Indian Health Service projections based upon birth and death rate data as provided by the National Center for Health Statistics. (c) Indian tribes may challenge the data described...

An analytical formulation of two‐dimensional groundwater dispersion induced by surficial recharge variability

USGS Publications Warehouse

Swain, Eric D.; Chin, David A.

2003-01-01

A predominant cause of dispersion in groundwater is advective mixing due to variability in seepage rates. Hydraulic conductivity variations have been extensively researched as a cause of this seepage variability. In this paper the effect of variations in surface recharge to a shallow surficial aquifer is investigated as an important additional effect. An analytical formulation has been developed that relates aquifer parameters and the statistics of recharge variability to increases in the dispersivity. This is accomplished by solving Fourier transforms of the small perturbation forms of the groundwater flow equations. Two field studies are presented in this paper to determine the statistics of recharge variability for input to the analytical formulation. A time series of water levels at a continuous groundwater recorder is used to investigate the temporal statistics of hydraulic head caused by recharge, and a series of infiltrometer measurements are used to define the spatial variability in the recharge parameters. With these field statistics representing head fluctuations due to recharge, the analytical formulation can be used to compute the dispersivity without an explicit representation of the recharge boundary. Results from a series of numerical experiments are used to define the limits of this analytical formulation and to provide some comparison. A sophisticated model has been developed using a particle‐tracking algorithm (modified to account for temporal variations) to estimate groundwater dispersion. Dispersivity increases of 9 percent are indicated by the analytical formulation for the aquifer at the field site. A comparison with numerical model results indicates that the analytical results are reasonable for shallow surficial aquifers in which two‐dimensional flow can be assumed.

Assessment of heart rate variability based on mobile device for planning physical activity

NASA Astrophysics Data System (ADS)

Svirin, I. S.; Epishina, E. V.; Voronin, V. V.; Semenishchev, E. A.; Solodova, E. N.; Nabilskaya, N. V.

2015-05-01

In this paper we present a method for the functional analysis of human heart based on electrocardiography (ECG) signals. The approach using the apparatus of analytical and differential geometry and correlation and regression analysis. ECG contains information on the current condition of the cardiovascular system as well as on the pathological changes in the heart. Mathematical processing of the heart rate variability allows to obtain a great set of mathematical and statistical characteristics. These characteristics of the heart rate are used when solving research problems to study physiological changes that determine functional changes of an individual. The proposed method implemented for up-to-date mobile Android and iOS based devices.

Innovating patient care delivery: DSRIP's interrupted time series analysis paradigm.

PubMed

Shenoy, Amrita G; Begley, Charles E; Revere, Lee; Linder, Stephen H; Daiger, Stephen P

2017-12-08

Adoption of Medicaid Section 1115 waiver is one of the many ways of innovating healthcare delivery system. The Delivery System Reform Incentive Payment (DSRIP) pool, one of the two funding pools of the waiver has four categories viz. infrastructure development, program innovation and redesign, quality improvement reporting and lastly, bringing about population health improvement. A metric of the fourth category, preventable hospitalization (PH) rate was analyzed in the context of eight conditions for two time periods, pre-reporting years (2010-2012) and post-reporting years (2013-2015) for two hospital cohorts, DSRIP participating and non-participating hospitals. The study explains how DSRIP impacted Preventable Hospitalization (PH) rates of eight conditions for both hospital cohorts within two time periods. Eight PH rates were regressed as the dependent variable with time, intervention and post-DSRIP Intervention as independent variables. PH rates of eight conditions were then consolidated into one rate for regressing with the above independent variables to evaluate overall impact of DSRIP. An interrupted time series regression was performed after accounting for auto-correlation, stationarity and seasonality in the dataset. In the individual regression model, PH rates showed statistically significant coefficients for seven out of eight conditions in DSRIP participating hospitals. In the combined regression model, the coefficient of the PH rate showed a statistically significant decrease with negative p-values for regression coefficients in DSRIP participating hospitals compared to positive/increased p-values for regression coefficients in DSRIP non-participating hospitals. Several macro- and micro-level factors may have likely contributed DSRIP hospitals outperforming DSRIP non-participating hospitals. Healthcare organization/provider collaboration, support from healthcare professionals, DSRIP's design, state reimbursement and coordination in care delivery methods may have led to likely success of DSRIP. IV, a retrospective cohort study based on longitudinal data. Copyright © 2017 Elsevier Inc. All rights reserved.

Cardiovascular oscillations at the bedside: early diagnosis of neonatal sepsis using heart rate characteristics monitoring

PubMed Central

Moorman, J. Randall; Delos, John B.; Flower, Abigail A.; Cao, Hanqing; Kovatchev, Boris P.; Richman, Joshua S.; Lake, Douglas E.

2014-01-01

We have applied principles of statistical signal processing and non-linear dynamics to analyze heart rate time series from premature newborn infants in order to assist in the early diagnosis of sepsis, a common and potentially deadly bacterial infection of the bloodstream. We began with the observation of reduced variability and transient decelerations in heart rate interval time series for hours up to days prior to clinical signs of illness. We find that measurements of standard deviation, sample asymmetry and sample entropy are highly related to imminent clinical illness. We developed multivariable statistical predictive models, and an interface to display the real-time results to clinicians. Using this approach, we have observed numerous cases in which incipient neonatal sepsis was diagnosed and treated without any clinical illness at all. This review focuses on the mathematical and statistical time series approaches used to detect these abnormal heart rate characteristics and present predictive monitoring information to the clinician. PMID:22026974

Measuring Investment in Learning: Can Electrocardiogram Provide an Indication of Cognitive Effort During Learning?

PubMed

Patterson, Jae T; Hart, Amanda; Hansen, Steve; Carter, Michael J; Ditor, David

2016-04-01

Heart rate variability (i.e., low frequency:high frequency ratio) was measured to differentiate invested cognitive effort during the acquisition and retention of a novel task. Participants (12 male, M = 25.1 year, SD = 3.6; 12 female, M = 22.8 year, SD = 1.1) were required to produce Braille equivalents of English letter primes on a standardized keyboard in proactive or retroactive conditions (groups, each n = 12). The correct Braille response was either provided before (i.e., proactively) or after (i.e., retroactively) the participant's response. During acquisition, participants in the proactive group demonstrated shorter study time, greater recall success, and reported lower cognitive investment. Participants in the proactive and retroactive groups did not statistically differ in heart rate variability. For retention, the retroactive group showed greater recall success, lower perceived cognitive effort investment, and lower heart rate variability. The results highlight the usefulness of heart rate variability in discriminating the cognitive effort invested for a recently acquired skill. © The Author(s) 2016.

The relationship of different socioeconomic variables and alcohol consumption with nighttime fatal traffic crashes in Spain: 1978-1993.

PubMed

González-Luque, J C; Rodríguez-Artalejo, F

2000-01-01

This paper identifies the variables associated with alcohol-related fatal traffic crashes (AFTC) in Spain. In addition, and for the first time in this country, these variables are used to describe the trend in AFTC, and to study the relationship between AFTC and alcohol consumption over the period 1976-1993. To this end, official data were obtained from the Traffic Department (Dirección General de Tráfico), the National Statistics Institute (Instituto Nacional de Estadística), and from international publications on trends in alcohol consumption. Nighttime fatal crashes (NFC) and male-driver single-vehicle nighttime fatal crashes (MNFC) were strongly associated with AFTC rates in Spain. A further finding was the decrease in NFC and MNFC rates during the period 1978-1993, though this decrease proved of a lower magnitude than that observed for daytime crashes. No relationship was observed between alcohol consumption at the population level and NFC or MNFC rates. The fatal crash rate, particularly the daytime rate, showed a rise with wealth level, as measured by gross domestic product and national private consumption, and an inverse relationship with the unemployment rate. The relationship between the fatal crash rate and economic variables was due, in most part, to changes in vehicle-km travelled.

The Effects of Local Economic Conditions on Navy Enlistments.

DTIC Science & Technology

1980-03-18

Standard Metropolitan Statistical Area (SMSA) as the basic economic unit, cross-sectional regression models were constructed for enlistment rate, recruiter...to eligible population suggesting that a cheaper alternative to raising mili- tary wages would be to increase the number of recruiters. Arima (1978...is faced with a number of cri- teria that must be satisfied by an acceptable test variable. As with other variables included in the model , economic

Optimization of non-thermal plasma efficiency in the simultaneous elimination of benzene, toluene, ethyl-benzene, and xylene from polluted airstreams using response surface methodology.

PubMed

Najafpoor, Ali Asghar; Jonidi Jafari, Ahmad; Hosseinzadeh, Ahmad; Khani Jazani, Reza; Bargozin, Hasan

2018-01-01

Treatment with a non-thermal plasma (NTP) is a new and effective technology applied recently for conversion of gases for air pollution control. This research was initiated to optimize the efficient application of the NTP process in benzene, toluene, ethyl-benzene, and xylene (BTEX) removal. The effects of four variables including temperature, initial BTEX concentration, voltage, and flow rate on the BTEX elimination efficiency were investigated using response surface methodology (RSM). The constructed model was evaluated by analysis of variance (ANOVA). The model goodness-of-fit and statistical significance was assessed using determination coefficients (R 2 and R 2 adj ) and the F-test. The results revealed that the R 2 proportion was greater than 0.96 for BTEX removal efficiency. The statistical analysis demonstrated that the BTEX removal efficiency was significantly correlated with the temperature, BTEX concentration, voltage, and flow rate. Voltage was the most influential variable affecting the dependent variable as it exerted a significant effect (p < 0.0001) on the response variable. According to the achieved results, NTP can be applied as a progressive, cost-effective, and practical process for treatment of airstreams polluted with BTEX in conditions of low residence time and high concentrations of pollutants.

Spatial Variability in Biodegradation Rates as Evidenced by Methane Production from an Aquifer

PubMed Central

Adrian, Neal R.; Robinson, Joseph A.; Suflita, Joseph M.

1994-01-01

Accurate predictions of carbon and energy cycling rates in the environment depend on sampling frequencies and on the spatial variability associated with biological activities. We examined the variability associated with anaerobic biodegradation rates at two sites in an alluvial sand aquifer polluted by municipal landfill leachate. In situ rates of methane production were measured for almost a year, using anaerobic wells installed at two sites. Methane production ranged from 0 to 560 μmol · m-2 · day-1 at one site (A), while a range of 0 to 120,000 μmol · m-2 · day-1 was measured at site B. The mean and standard deviations associated with methane production at site A were 17 and 57 μmol · m-2 · day-1, respectively. The comparable summary statistics for site B were 2,000 and 9,900 μmol · m-2 · day-1. The coefficients of variation at sites A and B were 340 and 490%, respectively. Despite these differences, the two sites had similar seasonal trends, with the maximal rate of methane production occurring in summer. However, the relative variability associated with the seasonal rates changed very little. Our results suggest that (i) two spatially distinct sites exist in the aquifer, (ii) methanogenesis is a highly variable process, (iii) the coefficient of variation varied little with the rate of methane production, and (iv) in situ anaerobic biodegradation rates are lognormally distributed. PMID:16349410

Approximate Entropies for Stochastic Time Series and EKG Time Series of Patients with Epilepsy and Pseudoseizures

NASA Astrophysics Data System (ADS)

Vyhnalek, Brian; Zurcher, Ulrich; O'Dwyer, Rebecca; Kaufman, Miron

2009-10-01

A wide range of heart rate irregularities have been reported in small studies of patients with temporal lobe epilepsy [TLE]. We hypothesize that patients with TLE display cardiac dysautonomia in either a subclinical or clinical manner. In a small study, we have retrospectively identified (2003-8) two groups of patients from the epilepsy monitoring unit [EMU] at the Cleveland Clinic. No patients were diagnosed with cardiovascular morbidities. The control group consisted of patients with confirmed pseudoseizures and the experimental group had confirmed right temporal lobe epilepsy through a seizure free outcome after temporal lobectomy. We quantified the heart rate variability using the approximate entropy [ApEn]. We found similar values of the ApEn in all three states of consciousness (awake, sleep, and proceeding seizure onset). In the TLE group, there is some evidence for greater variability in the awake than in either the sleep or proceeding seizure onset. Here we present results for mathematically-generated time series: the heart rate fluctuations ξ follow the γ statistics i.e., p(ξ)=γ-1(k) ξ^k exp(-ξ). This probability function has well-known properties and its Shannon entropy can be expressed in terms of the γ-function. The parameter k allows us to generate a family of heart rate time series with different statistics. The ApEn calculated for the generated time series for different values of k mimic the properties found for the TLE and pseudoseizure group. Our results suggest that the ApEn is an effective tool to probe differences in statistics of heart rate fluctuations.

Salt preference: age and sex related variability.

PubMed

Verma, Punam; Mittal, Sunita; Ghildiyal, Archana; Chaudhary, Lalita; Mahajan, K K

2007-01-01

Salt preference was assessed in 60 adults of 18-21 yrs of age (30 males and 30 females) and in 60 children of 7-12 yrs of age (30 boys and 30 girls). Subjects rated the preference on Likert scale for popcorns of five salt concentrations (OM, 1M, 2M, 3M and +3M). Statistical analysis using Two way ANOVA revealed statistically significant effect of age and sex on salt preference (F4,100 = 15.027, P < 0.01) and One Way ANOVA revealed statistically significant sex difference in salt preference of adults (F4,50 = 16.26, P < 0.01) but no statistically significant sex difference in salt preference of children (F4,50 = 4.08, P > 0.05). Dietary experiences during development and more physical activity in children may be responsible for higher salt preference in children while finding no sex variability in children favours the role of sex hormones in salt preference of male and females.

Caries prevalence in chronic alcoholics and the relationship to salivary flow rate and pH.

PubMed

Dukić, Walter; Dobrijević, Tanja Trivanović; Katunarić, Marina; Lesić, Stjepanka

2013-03-01

The aim of this study was to investigate the dental status of alcoholics; to evaluate the relationship of unstimulated and stimulated saliva pH on their decayed/missing/filled teeth (DMFT); and to evaluate the relationship of unstimulated and stimulated salivary flow rate on their DMFT. A cross-sectional study was conducted in patients treated for alcohol dependency (n = 70; mean age 41.7 years) and a control group of non-alcoholics (n = 70; mean age 39.1 years). Examinations for dental caries were conducted using the World Health Organization (WHO) criteria and questionnaires. The correlation between nominal variables was determined using chi2 test (alpha = 0.05). The correlation between interval variables was determined using Pearson's correlation coefficient. The mean DMFT was similar in alcoholics (14.40) and the control group (13.44) (p > 0.05). There was a statistically significant correlation between alcoholism and unstimulated salivary flow rate (p < 0.05), but no relationship on DMFT was recorded. No statistically significant differences were found between alcoholics and controls in terms of stimulated salivary flow rate (p > 0.05) or stimulated salivary flow on DMFT (p > 0.05). There was a statistically significant correlation between alcoholism and the pH value of stimulated saliva (p < 0.01). There was no correlation between the amount of alcohol consumed and the number of carious lesions (p > 0.05). No major differences were found with respect to overall DMFT in alcoholics compared to the control group. Alcoholism and stimulated salivary flow rate showed no correlation. Unstimulated salivary flow rate as well as the pH values of both unstimulated and stimulated saliva, were lower in the alcoholic group.

Use of the Wii Gaming System for Balance Rehabilitation: Establishing Parameters for Healthy Individuals.

PubMed

Burns, Melissa K; Andeway, Kathleen; Eppenstein, Paula; Ruroede, Kathleen

2014-06-01

This study was designed to establish balance parameters for the Nintendo(®) (Redmond, WA) "Wii Fit™" Balance Board system with three common games, in a sample of healthy adults, and to evaluate the balance measurement reproducibility with separation by age. This was a prospective, multivariate analysis of variance, cohort study design. Seventy-five participants who satisfied all inclusion criteria and completed an informed consent were enrolled. Participants were grouped into age ranges: 21-35 years (n=24), 36-50 years (n=24), and 51-65 years (n=27). Each participant completed the following games three consecutive times, in a randomized order, during one session: "Balance Bubble" (BB) for distance and duration, "Tight Rope" (TR) for distance and duration, and "Center of Balance" (COB) on the left and right sides. COB distributed weight was fairly symmetrical across all subjects and trials; therefore, no influence was assumed on or interaction with other "Wii Fit" measurements. Homogeneity of variance statistics indicated the assumption of distribution normality of the dependent variables (rates) were tenable. The multivariate analysis of variance included dependent variables BB and TR rates (distance divided by duration to complete) with age group and trials as the independent variables. The BB rate was statistically significant (F=4.725, P<0.005), but not the TR rate. The youngest group's BB rate was significantly larger than those of the other two groups. "Wii Fit" can discriminate among age groups across trials. The results show promise as a viable tool to measure balance and distance across time (speed) and center of balance distribution.

Characteristics of Inpatient Units Associated With Sustained Hand Hygiene Compliance.

PubMed

Wolfe, Jonathan D; Domenico, Henry J; Hickson, Gerald B; Wang, Deede; Dubree, Marilyn; Feistritzer, Nancye; Wells, Nancy; Talbot, Thomas R

2018-04-20

Following institution of a hand hygiene (HH) program at an academic medical center, HH compliance increased from 58% to 92% for 3 years. Some inpatient units modeled early, sustained increases, and others exhibited protracted improvement rates. We examined the association between patterns of HH compliance improvement and unit characteristics. Adult inpatient units (N = 35) were categorized into the following three tiers based on their pattern of HH compliance: early adopters, nonsustained and late adopters, and laggards. Unit-based culture measures were collected, including nursing practice environment scores (National Database of Nursing Quality Indicators [NDNQI]), patient rated quality and teamwork (Hospital Consumer Assessment of Healthcare Provider and Systems), patient complaint rates, case mix index, staff turnover rates, and patient volume. Associations between variables and the binary outcome of laggard (n = 18) versus nonlaggard (n = 17) were tested using a Mann-Whitney U test. Multivariate analysis was performed using an ordinal regression model. In direct comparison, laggard units had clinically relevant differences in NDNQI scores, Hospital Consumer Assessment of Healthcare Provider and Systems scores, case mix index, patient complaints, patient volume, and staff turnover. The results were not statistically significant. In the multivariate model, the predictor variables explained a significant proportion of the variability associated with laggard status, (R = 0.35, P = 0.0481) and identified NDNQI scores and patient complaints as statistically significant. Uptake of an HH program was associated with factors related to a unit's safety culture. In particular, NDNQI scores and patient complaint rates might be used to assist in identifying units that may require additional attention during implementation of an HH quality improvement program.

Success Rate of Microimplants in a University Orthodontic Clinic

PubMed Central

Sharma, P.; Valiathan, A.; Sivakumar, A.

2011-01-01

Introduction. The purpose of this study was to examine the success rate and find factors affecting the clinical success of microimplants used as orthodontic anchorage. Methods. Seventy-three consecutive patients (25 male, 48 female; mean age, 22.45 years) with a total of 139 screw implants of 2 types were examined. Success rate was determined according to 18 clinical variables. Results. The overall success rate was 87.8%. The clinical variables of microimplant factors (type), patient factors (sex, skeletal and dental relationships, overbite, jaw involved, side involved and site involved), and treatment factors (type of insertion, time of loading, purpose of microimplant insertion, mode of loading, type of anchorage used, direction of forces applied) did not show any statistical difference in success rates. Mandibular angle, vertical position of implant placement, oral hygiene status, and inflammation showed significant difference in success rates. Conclusions. Proper case selection and following the recommended protocol are extremely essential to minimise failures. PMID:22084789

Spike Pattern Structure Influences Synaptic Efficacy Variability under STDP and Synaptic Homeostasis. II: Spike Shuffling Methods on LIF Networks

PubMed Central

Bi, Zedong; Zhou, Changsong

2016-01-01

Synapses may undergo variable changes during plasticity because of the variability of spike patterns such as temporal stochasticity and spatial randomness. Here, we call the variability of synaptic weight changes during plasticity to be efficacy variability. In this paper, we investigate how four aspects of spike pattern statistics (i.e., synchronous firing, burstiness/regularity, heterogeneity of rates and heterogeneity of cross-correlations) influence the efficacy variability under pair-wise additive spike-timing dependent plasticity (STDP) and synaptic homeostasis (the mean strength of plastic synapses into a neuron is bounded), by implementing spike shuffling methods onto spike patterns self-organized by a network of excitatory and inhibitory leaky integrate-and-fire (LIF) neurons. With the increase of the decay time scale of the inhibitory synaptic currents, the LIF network undergoes a transition from asynchronous state to weak synchronous state and then to synchronous bursting state. We first shuffle these spike patterns using a variety of methods, each designed to evidently change a specific pattern statistics; and then investigate the change of efficacy variability of the synapses under STDP and synaptic homeostasis, when the neurons in the network fire according to the spike patterns before and after being treated by a shuffling method. In this way, we can understand how the change of pattern statistics may cause the change of efficacy variability. Our results are consistent with those of our previous study which implements spike-generating models on converging motifs. We also find that burstiness/regularity is important to determine the efficacy variability under asynchronous states, while heterogeneity of cross-correlations is the main factor to cause efficacy variability when the network moves into synchronous bursting states (the states observed in epilepsy). PMID:27555816

Speaking-rate-induced variability in F2 trajectories.

PubMed

Tjaden, K; Weismer, G

1998-10-01

This study examined speaking-rate-induced spectral and temporal variability of F2 formant trajectories for target words produced in a carrier phrase at speaking rates ranging from fast to slow. F2 onset frequency measured at the first glottal pulse following the stop consonant release in target words was used to quantify the extent to which adjacent consonantal and vocalic gestures overlapped; F2 target frequency was operationally defined as the first occurrence of a frequency minimum or maximum following F2 onset frequency. Regression analyses indicated 70% of functions relating F2 onset and vowel duration were statistically significant. The strength of the effect was variable, however, and the direction of significant functions often differed from that predicted by a simple model of overlapping, sliding gestures. Results of a partial correlation analysis examining interrelationships among F2 onset, F2 target frequency, and vowel duration across the speaking rate range indicated that covariation of F2 target with vowel duration may obscure the relationship between F2 onset and vowel duration across rate. The results further suggested that a sliding based model of acoustic variability associated with speaking rate change only partially accounts for the present data, and that such a view accounts for some speakers' data better than others.

Milk Flow Rates from bottle nipples used after hospital discharge.

PubMed

Pados, Britt Frisk; Park, Jinhee; Thoyre, Suzanne M; Estrem, Hayley; Nix, W Brant

To test the milk flow rates and variability in flow rates of bottle nipples used after hospital discharge. Twenty-six nipple types that represented 15 common brands as well as variety in price per nipple and store location sold (e.g., Babies R' Us, Walmart, Dollar Store) were chosen for testing. Ten of each nipple type (n = 260 total) were tested by measuring the amount of infant formula expressed in 1 minute using a breast pump. Mean milk flow rate (mL/min) and coefficient of variation (CV) were calculated. Flow rates of nipples within brand were compared statistically. Milk flow rates varied from 1.68 mL/min for the Avent Natural Newborn Flow to 85.34 mL/min for the Dr. Brown's Standard Y-cut. Variability between nipple types also varied widely, from .03 for the Dr. Brown's Standard Level 3 to .37 for MAM Nipple 1 Slow Flow. The extreme range of milk flow rates found may be significant for medically fragile infants being discharged home who are continuing to develop oral feeding skills. The name of the nipple does not provide clear information about the flow rate to guide parents in decision making. Variability in flow rates within nipples of the same type may complicate oral feeding for the medically fragile infant who may not be able to adapt easily to change in flow rates. Both flow rate and variability should be considered when guiding parents to a nipple choice.

An Independent Filter for Gene Set Testing Based on Spectral Enrichment.

PubMed

Frost, H Robert; Li, Zhigang; Asselbergs, Folkert W; Moore, Jason H

2015-01-01

Gene set testing has become an indispensable tool for the analysis of high-dimensional genomic data. An important motivation for testing gene sets, rather than individual genomic variables, is to improve statistical power by reducing the number of tested hypotheses. Given the dramatic growth in common gene set collections, however, testing is often performed with nearly as many gene sets as underlying genomic variables. To address the challenge to statistical power posed by large gene set collections, we have developed spectral gene set filtering (SGSF), a novel technique for independent filtering of gene set collections prior to gene set testing. The SGSF method uses as a filter statistic the p-value measuring the statistical significance of the association between each gene set and the sample principal components (PCs), taking into account the significance of the associated eigenvalues. Because this filter statistic is independent of standard gene set test statistics under the null hypothesis but dependent under the alternative, the proportion of enriched gene sets is increased without impacting the type I error rate. As shown using simulated and real gene expression data, the SGSF algorithm accurately filters gene sets unrelated to the experimental outcome resulting in significantly increased gene set testing power.

Statistical approaches to assessing single and multiple outcome measures in dry eye therapy and diagnosis.

PubMed

Tomlinson, Alan; Hair, Mario; McFadyen, Angus

2013-10-01

Dry eye is a multifactorial disease which would require a broad spectrum of test measures in the monitoring of its treatment and diagnosis. However, studies have typically reported improvements in individual measures with treatment. Alternative approaches involve multiple, combined outcomes being assessed by different statistical analyses. In order to assess the effect of various statistical approaches to the use of single and combined test measures in dry eye, this review reanalyzed measures from two previous studies (osmolarity, evaporation, tear turnover rate, and lipid film quality). These analyses assessed the measures as single variables within groups, pre- and post-intervention with a lubricant supplement, by creating combinations of these variables and by validating these combinations with the combined sample of data from all groups of dry eye subjects. The effectiveness of single measures and combinations in diagnosis of dry eye was also considered. Copyright © 2013. Published by Elsevier Inc.

Organisational injustice and impaired cardiovascular regulation among female employees.

PubMed

Elovainio, M; Kivimäki, M; Puttonen, S; Lindholm, H; Pohjonen, T; Sinervo, T

2006-02-01

To examine the relation between perceived organisational justice and cardiovascular reactivity in women. The participants were 57 women working in long term care homes. Heart rate variability and systolic arterial pressure variability were used as markers of autonomic function. Organisational justice was measured using the scale of Moorman. Data on other risk factors were also collected. Results from logistic regression models showed that the risk for increased low frequency band systolic arterial pressure variability was 3.8-5.8 times higher in employees with low justice than in employees with high justice. Low perceived justice was also related to an 80% excess risk of reduced high frequency heart rate variability compared to high perceived justice, but this association was not statistically significant. These findings are consistent with the hypothesis that cardiac dysregulation is one stress mechanism through which a low perceived justice of decision making procedures and interpersonal treatment increases the risk of health problems in personnel.

Tuberculosis inequalities and socio-economic deprivation in Portugal.

PubMed

Apolinário, D; Ribeiro, A I; Krainski, E; Sousa, P; Abranches, M; Duarte, R

2017-07-01

To analyse the geographical distribution of tuberculosis (TB) in Portugal and estimate the association between TB and socio-economic deprivation. An ecological study at the municipality level using TB notifications for 2010-2014 was conducted. Spatial Bayesian models were used to calculate smoothed standardised notification rates, identify high- and low-risk areas and estimate the association between TB notification and the European Deprivation Index (EDI) for Portugal and its component variables. Standardised notification rates ranged from 4.41 to 76.44 notifications per 100 000 population. Forty-one high-risk and 156 low-risk municipalities were identified. There was no statistically significant association between TB notification rate and the EDI, but some of its variables, such as the proportion of manual workers and the percentage unemployed, were significantly and directly associated with TB notification, whereas the variable 'proportion of residents with low education level' showed an inverse relationship. Wide inequalities in TB notification rates were observed, and some areas continued to exhibit high TB notification rates. We found significant associations between TB and some socio-economic factors of the EDI.

Respiratory effects of diesel exhaust in salt miners

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gamble, J.F.; Jones, W.G.

1983-09-01

The respiratory health of 259 white males working at 5 salt (NaCl) mines was assessed by questionnaire, chest radiographs, and air and He-O/sup 2/ spirometry. Response variables were symptoms, pneumoconiosis, and spirometry. Predictor variables included age, height, smoking, mine, and tenure in diesel-exposed jobs. The purpose was to assess the association of response measures of respiratory health with exposure to diesel exhaust. There were only 2 cases of Grade 1 pneumoconiosis, so no further analysis was done. Comparisons within the study population showed a statistically significant dose-related association of phlegm and diesel exposure. There was a nonsignificant trend for coughmore » and dyspnea, and no association with spirometry. Age- and smoking-adjusted rates of cough, phlegm, and dyspnea were 145, 159, and 93% of an external comparison population. Percent predicted flow rates showed statistically significant reductions, but the reductions were small and there were no dose-response relations. Percent predicted FEV1 and FVC were about 96% of predicted.« less

Quantitative approaches in climate change ecology

PubMed Central

Brown, Christopher J; Schoeman, David S; Sydeman, William J; Brander, Keith; Buckley, Lauren B; Burrows, Michael; Duarte, Carlos M; Moore, Pippa J; Pandolfi, John M; Poloczanska, Elvira; Venables, William; Richardson, Anthony J

2011-01-01

Contemporary impacts of anthropogenic climate change on ecosystems are increasingly being recognized. Documenting the extent of these impacts requires quantitative tools for analyses of ecological observations to distinguish climate impacts in noisy data and to understand interactions between climate variability and other drivers of change. To assist the development of reliable statistical approaches, we review the marine climate change literature and provide suggestions for quantitative approaches in climate change ecology. We compiled 267 peer-reviewed articles that examined relationships between climate change and marine ecological variables. Of the articles with time series data (n = 186), 75% used statistics to test for a dependency of ecological variables on climate variables. We identified several common weaknesses in statistical approaches, including marginalizing other important non-climate drivers of change, ignoring temporal and spatial autocorrelation, averaging across spatial patterns and not reporting key metrics. We provide a list of issues that need to be addressed to make inferences more defensible, including the consideration of (i) data limitations and the comparability of data sets; (ii) alternative mechanisms for change; (iii) appropriate response variables; (iv) a suitable model for the process under study; (v) temporal autocorrelation; (vi) spatial autocorrelation and patterns; and (vii) the reporting of rates of change. While the focus of our review was marine studies, these suggestions are equally applicable to terrestrial studies. Consideration of these suggestions will help advance global knowledge of climate impacts and understanding of the processes driving ecological change.

Land change variability and human-environment dynamics in the United States Great Plains

USGS Publications Warehouse

Drummond, M.A.; Auch, Roger F.; Karstensen, K.A.; Sayler, K. L.; Taylor, Janis L.; Loveland, Thomas R.

2012-01-01

Land use and land cover changes have complex linkages to climate variability and change, biophysical resources, and socioeconomic driving forces. To assess these land change dynamics and their causes in the Great Plains, we compare and contrast contemporary changes across 16 ecoregions using Landsat satellite data and statistical analysis. Large-area change analysis of agricultural regions is often hampered by change detection error and the tendency for land conversions to occur at the local-scale. To facilitate a regional-scale analysis, a statistical sampling design of randomly selected 10 km × 10 km blocks is used to efficiently identify the types and rates of land conversions for four time intervals between 1973 and 2000, stratified by relatively homogenous ecoregions. Nearly 8% of the overall Great Plains region underwent land-use and land-cover change during the study period, with a substantial amount of ecoregion variability that ranged from less than 2% to greater than 13%. Agricultural land cover declined by more than 2% overall, with variability contingent on the differential characteristics of regional human–environment systems. A large part of the Great Plains is in relatively stable land cover. However, other land systems with significant biophysical and climate limitations for agriculture have high rates of land change when pushed by economic, policy, technology, or climate forcing factors. The results indicate the regionally based potential for land cover to persist or fluctuate as land uses are adapted to spatially and temporally variable forcing factors.

[Analysis of the technical efficiency of hospitals in the Spanish National Health Service].

PubMed

Pérez-Romero, Carmen; Ortega-Díaz, M Isabel; Ocaña-Riola, Ricardo; Martín-Martín, José Jesús

To analyse the technical efficiency and productivity of general hospitals in the Spanish National Health Service (NHS) (2010-2012) and identify explanatory hospital and regional variables. 230 NHS hospitals were analysed by data envelopment analysis for overall, technical and scale efficiency, and Malmquist index. The robustness of the analysis is contrasted with alternative input-output models. A fixed effects multilevel cross-sectional linear model was used to analyse the explanatory efficiency variables. The average rate of overall technical efficiency (OTE) was 0.736 in 2012; there was considerable variability by region. Malmquist index (2010-2012) is 1.013. A 23% variability in OTE is attributable to the region in question. Statistically significant exogenous variables (residents per 100 physicians, aging index, average annual income per household, essential public service expenditure and public health expenditure per capita) explain 42% of the OTE variability between hospitals and 64% between regions. The number of residents showed a statistically significant relationship. As regards regions, there is a statistically significant direct linear association between OTE and annual income per capita and essential public service expenditure, and an indirect association with the aging index and annual public health expenditure per capita. The significant room for improvement in the efficiency of hospitals is conditioned by region-specific characteristics, specifically aging, wealth and the public expenditure policies of each one. Copyright © 2016 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

Howling at the moon? The effect of lunar phases on post-surgical pain outcome.

PubMed

Komann, Marcus; Weinmann, Claudia; Meissner, Winfried

2014-05-01

Many people are convinced that lunar phases influence their lives - despite the fact that a lot of studies have shown that this belief is wrong. In this article, we investigate the effect of lunar phases on acute post-surgical pain and on treatment-related side effects. We hypothesize that there is no influence. The data for the study were collected in 2010 and 2011 in 10 international hospitals participating in the research project PAIN OUT. Hospitalized patients were asked for their pain after surgery and pain treatment side effects using numerical ratings scales from 0 to 10. We applied Kurskal-Wallis H-tests to find out if the four moon phases show significant differences in 14 outcome variables. Afterwards, we adjusted for age, gender and three tracer surgeries. A total of 12,224 patient data sets were assessed. For most variables and sub-groups, there is no lunar effect on the observed outcome variables. The only items that show statistically significant differences are pain interference with sleep (p = 0.01) and drowsiness (p = 0.01). The only sub-groups that show statistically significant connections to lunar phases in some variables are men (7 out of 14 variables significant) and elderly people (4 out of 14 variables significant). Even in the statistically significant sub-groups, the differences are small and only show up in some variables. We conclude that lunar phases have no effect on post-surgical pain or its side effects. The hypothesis holds. Thus, there is no reason for patients to postpone surgeries or to fear surgeries on any given date.

Superposed epoch analysis of physiological fluctuations: possible space weather connections

NASA Astrophysics Data System (ADS)

Wanliss, James; Cornélissen, Germaine; Halberg, Franz; Brown, Denzel; Washington, Brien

2018-03-01

There is a strong connection between space weather and fluctuations in technological systems. Some studies also suggest a statistical connection between space weather and subsequent fluctuations in the physiology of living creatures. This connection, however, has remained controversial and difficult to demonstrate. Here we present support for a response of human physiology to forcing from the explosive onset of the largest of space weather events—space storms. We consider a case study with over 16 years of high temporal resolution measurements of human blood pressure (systolic, diastolic) and heart rate variability to search for associations with space weather. We find no statistically significant change in human blood pressure but a statistically significant drop in heart rate during the main phase of space storms. Our empirical findings shed light on how human physiology may respond to exogenous space weather forcing.

Superposed epoch analysis of physiological fluctuations: possible space weather connections.

PubMed

Wanliss, James; Cornélissen, Germaine; Halberg, Franz; Brown, Denzel; Washington, Brien

2018-03-01

There is a strong connection between space weather and fluctuations in technological systems. Some studies also suggest a statistical connection between space weather and subsequent fluctuations in the physiology of living creatures. This connection, however, has remained controversial and difficult to demonstrate. Here we present support for a response of human physiology to forcing from the explosive onset of the largest of space weather events-space storms. We consider a case study with over 16 years of high temporal resolution measurements of human blood pressure (systolic, diastolic) and heart rate variability to search for associations with space weather. We find no statistically significant change in human blood pressure but a statistically significant drop in heart rate during the main phase of space storms. Our empirical findings shed light on how human physiology may respond to exogenous space weather forcing.

The interaction between stratospheric monthly mean regional winds and sporadic-E

NASA Astrophysics Data System (ADS)

Çetin, Kenan; Özcan, Osman; Korlaelçi, Serhat

2017-03-01

In the present study, a statistical investigation is carried out to explore whether there is a relationship between the critical frequency (foEs) of the sporadic-E layer that is occasionally seen on the E region of the ionosphere and the quasi-biennial oscillation (QBO) that flows in the east-west direction in the equatorial stratosphere. Multiple regression model as a statistical tool was used to determine the relationship between variables. In this model, the stationarity of the variables (foEs and QBO) was firstly analyzed for each station (Cocos Island, Gibilmanna, Niue Island, and Tahiti). Then, a co-integration test was made to determine the existence of a long-term relationship between QBO and foEs. After verifying the presence of a long-term relationship between the variables, the magnitude of the relationship between variables was further determined using the multiple regression model. As a result, it is concluded that the variations in foEs were explainable with QBO measured at 10 hPa altitude at the rate of 69%, 94%, 79%, and 58% for Cocos Island, Gibilmanna, Niue Island, and Tahiti stations, respectively. It is observed that the variations in foEs were explainable with QBO measured at 70 hPa altitude at the rate of 66%, 69%, 53%, and 47% for Cocos Island, Gibilmanna, Niue Island, and Tahiti stations, respectively.

Fitting Cure Rate Model to Breast Cancer Data of Cancer Research Center.

PubMed

Baghestani, Ahmad Reza; Zayeri, Farid; Akbari, Mohammad Esmaeil; Shojaee, Leyla; Khadembashi, Naghmeh; Shahmirzalou, Parviz

2015-01-01

The Cox PH model is one of the most significant statistical models in studying survival of patients. But, in the case of patients with long-term survival, it may not be the most appropriate. In such cases, a cure rate model seems more suitable. The purpose of this study was to determine clinical factors associated with cure rate of patients with breast cancer. In order to find factors affecting cure rate (response), a non-mixed cure rate model with negative binomial distribution for latent variable was used. Variables selected were recurrence cancer, status for HER2, estrogen receptor (ER) and progesterone receptor (PR), size of tumor, grade of cancer, stage of cancer, type of surgery, age at the diagnosis time and number of removed positive lymph nodes. All analyses were performed using PROC MCMC processes in the SAS 9.2 program. The mean (SD) age of patients was equal to 48.9 (11.1) months. For these patients, 1, 5 and 10-year survival rates were 95, 79 and 50 percent respectively. All of the mentioned variables were effective in cure fraction. Kaplan-Meier curve showed cure model's use competence. Unlike other variables, existence of ER and PR positivity will increase probability of cure in patients. In the present study, Weibull distribution was used for the purpose of analysing survival times. Model fitness with other distributions such as log-N and log-logistic and other distributions for latent variable is recommended.

Analysis of model development strategies: predicting ventral hernia recurrence.

PubMed

Holihan, Julie L; Li, Linda T; Askenasy, Erik P; Greenberg, Jacob A; Keith, Jerrod N; Martindale, Robert G; Roth, J Scott; Liang, Mike K

2016-11-01

There have been many attempts to identify variables associated with ventral hernia recurrence; however, it is unclear which statistical modeling approach results in models with greatest internal and external validity. We aim to assess the predictive accuracy of models developed using five common variable selection strategies to determine variables associated with hernia recurrence. Two multicenter ventral hernia databases were used. Database 1 was randomly split into "development" and "internal validation" cohorts. Database 2 was designated "external validation". The dependent variable for model development was hernia recurrence. Five variable selection strategies were used: (1) "clinical"-variables considered clinically relevant, (2) "selective stepwise"-all variables with a P value <0.20 were assessed in a step-backward model, (3) "liberal stepwise"-all variables were included and step-backward regression was performed, (4) "restrictive internal resampling," and (5) "liberal internal resampling." Variables were included with P < 0.05 for the Restrictive model and P < 0.10 for the Liberal model. A time-to-event analysis using Cox regression was performed using these strategies. The predictive accuracy of the developed models was tested on the internal and external validation cohorts using Harrell's C-statistic where C > 0.70 was considered "reasonable". The recurrence rate was 32.9% (n = 173/526; median/range follow-up, 20/1-58 mo) for the development cohort, 36.0% (n = 95/264, median/range follow-up 20/1-61 mo) for the internal validation cohort, and 12.7% (n = 155/1224, median/range follow-up 9/1-50 mo) for the external validation cohort. Internal validation demonstrated reasonable predictive accuracy (C-statistics = 0.772, 0.760, 0.767, 0.757, 0.763), while on external validation, predictive accuracy dipped precipitously (C-statistic = 0.561, 0.557, 0.562, 0.553, 0.560). Predictive accuracy was equally adequate on internal validation among models; however, on external validation, all five models failed to demonstrate utility. Future studies should report multiple variable selection techniques and demonstrate predictive accuracy on external data sets for model validation. Copyright © 2016 Elsevier Inc. All rights reserved.

A multi-level approach for investigating socio-economic and agricultural risk factors associated with rates of reported cases of Escherichia coli O157 in humans in Alberta, Canada.

PubMed

Pearl, D L; Louie, M; Chui, L; Doré, K; Grimsrud, K M; Martin, S W; Michel, P; Svenson, L W; McEwen, S A

2009-10-01

Using negative binomial and multi-level Poisson models, the authors determined the statistical significance of agricultural and socio-economic risk factors for rates of reported disease associated with Escherichia coli O157 in census subdivisions (CSDs) in Alberta, Canada, 2000-2002. Variables relating to population stability, aboriginal composition of the CSDs, and the economic relationship between CSDs and urban centres were significant risk factors. The percentage of individuals living in low-income households was not a statistically significant risk factor for rates of disease. The statistical significance of cattle density, recorded at a higher geographical level, depended on the method used to correct for overdispersion, the number of levels included in the multi-level models, and the choice of using all reported cases or only sporadic cases. Our results highlight the importance of local socio-economic risk factors in determining rates of disease associated with E. coli O157, but their relationship with individual risk factors requires further evaluation.

A meta-analysis and statistical modelling of nitrates in groundwater at the African scale

NASA Astrophysics Data System (ADS)

Ouedraogo, Issoufou; Vanclooster, Marnik

2016-06-01

Contamination of groundwater with nitrate poses a major health risk to millions of people around Africa. Assessing the space-time distribution of this contamination, as well as understanding the factors that explain this contamination, is important for managing sustainable drinking water at the regional scale. This study aims to assess the variables that contribute to nitrate pollution in groundwater at the African scale by statistical modelling. We compiled a literature database of nitrate concentration in groundwater (around 250 studies) and combined it with digital maps of physical attributes such as soil, geology, climate, hydrogeology, and anthropogenic data for statistical model development. The maximum, medium, and minimum observed nitrate concentrations were analysed. In total, 13 explanatory variables were screened to explain observed nitrate pollution in groundwater. For the mean nitrate concentration, four variables are retained in the statistical explanatory model: (1) depth to groundwater (shallow groundwater, typically < 50 m); (2) recharge rate; (3) aquifer type; and (4) population density. The first three variables represent intrinsic vulnerability of groundwater systems to pollution, while the latter variable is a proxy for anthropogenic pollution pressure. The model explains 65 % of the variation of mean nitrate contamination in groundwater at the African scale. Using the same proxy information, we could develop a statistical model for the maximum nitrate concentrations that explains 42 % of the nitrate variation. For the maximum concentrations, other environmental attributes such as soil type, slope, rainfall, climate class, and region type improve the prediction of maximum nitrate concentrations at the African scale. As to minimal nitrate concentrations, in the absence of normal distribution assumptions of the data set, we do not develop a statistical model for these data. The data-based statistical model presented here represents an important step towards developing tools that will allow us to accurately predict nitrate distribution at the African scale and thus may support groundwater monitoring and water management that aims to protect groundwater systems. Yet they should be further refined and validated when more detailed and harmonized data become available and/or combined with more conceptual descriptions of the fate of nutrients in the hydrosystem.

Analysis of variables affecting unemployment rate and detecting for cluster in West Java, Central Java, and East Java in 2012

NASA Astrophysics Data System (ADS)

Samuel, Putra A.; Widyaningsih, Yekti; Lestari, Dian

2016-02-01

The objective of this study is modeling the Unemployment Rate (UR) in West Java, Central Java, and East Java, with rate of disease, infant mortality rate, educational level, population size, proportion of married people, and GDRP as the explanatory variables. Spatial factors are also considered in the modeling since the closer the distance, the higher the correlation. This study uses the secondary data from BPS (Badan Pusat Statistik). The data will be analyzed using Moran I test, to obtain the information about spatial dependence, and using Spatial Autoregressive modeling to obtain the information, which variables are significant affecting UR and how great the influence of the spatial factors. The result is, variables proportion of married people, rate of disease, and population size are related significantly to UR. In all three regions, the Hotspot of unemployed will also be detected districts/cities using Spatial Scan Statistics Method. The results are 22 districts/cities as a regional group with the highest unemployed (Most likely cluster) in the study area; 2 districts/cities as a regional group with the highest unemployed in West Java; 1 district/city as a regional groups with the highest unemployed in Central Java; 15 districts/cities as a regional group with the highest unemployed in East Java.

Combination therapy with milrinone and esmolol for heart protection in patients with severe sepsis: a prospective, randomized trial.

PubMed

Wang, Zenggeng; Wu, Qinghua; Nie, Xiangbi; Guo, Jinghua; Yang, Chunli

2015-11-01

As a β-adrenoceptor antagonist (β-blocker), esmolol can reduce cardiac output and the phosphodiesterase III inhibitor milrinone has been shown to improve heart contractility in patients with septic shock. This study was performed to assess the effects of esmolol combined with milrinone in patients with severe sepsis. This prospective randomized study was conducted in patients with severe sepsis in the intensive care unit of the Jiangxi Provincial People's Hospital (Nanchang, Jiangsu, China) between June 2013 and June 2014. Patients were randomly divided into control (C), milrinone (M), and milrinone-esmolol (ME) groups. The primary outcome was the rate of controlling the heart rate (HR) to achieve target levels. Secondary outcomes included the 28-day survival rate and changes in hemodynamic variables, organ function variables, myocardial injury markers, and the serum levels of proinflammatory factors. A total of 90 patients with severe sepsis were included in this study (30 per group). The HR in the ME group was lower than in the M and C groups after 12 h. The rate of successful HR control during the first 96 h was significantly higher in the ME group (60.0 vs. 33.3 % in the M group, vs. 26.7 % in the C group). Also, patients in the ME group had higher 28-day overall survival compared with the M (Log rank statistic = 5.452; P = 0.020) and C groups (Log rank statistic = 10.206; P = 0.001). Additionally, several variables showed significant improvement in the ME group 96 h after treatment compared with the M and C groups (P < 0.05). Combination therapy with milrinone and esmolol could improve cardiac function and the 28-day survival rate in patients with severe sepsis.

Daily commuting to work is not associated with variables of health.

PubMed

Mauss, Daniel; Jarczok, Marc N; Fischer, Joachim E

2016-01-01

Commuting to work is thought to have a negative impact on employee health. We tested the association of work commute and different variables of health in German industrial employees. Self-rated variables of an industrial cohort (n = 3805; 78.9 % male) including absenteeism, presenteeism and indices reflecting stress and well-being were assessed by a questionnaire. Fasting blood samples, heart-rate variability and anthropometric data were collected. Commuting was grouped into one of four categories: 0-19.9, 20-44.9, 45-59.9, ≥60 min travelling one way to work. Bivariate associations between commuting and all variables under study were calculated. Linear regression models tested this association further, controlling for potential confounders. Commuting was positively correlated with waist circumference and inversely with triglycerides. These associations did not remain statistically significant in linear regression models controlling for age, gender, marital status, and shiftwork. No other association with variables of physical, psychological, or mental health and well-being could be found. The results indicate that commuting to work has no significant impact on well-being and health of German industrial employees.

Statistics for laminar flamelet modeling

NASA Technical Reports Server (NTRS)

Cant, R. S.; Rutland, C. J.; Trouve, A.

1990-01-01

Statistical information required to support modeling of turbulent premixed combustion by laminar flamelet methods is extracted from a database of the results of Direct Numerical Simulation of turbulent flames. The simulations were carried out previously by Rutland (1989) using a pseudo-spectral code on a three dimensional mesh of 128 points in each direction. One-step Arrhenius chemistry was employed together with small heat release. A framework for the interpretation of the data is provided by the Bray-Moss-Libby model for the mean turbulent reaction rate. Probability density functions are obtained over surfaces of the constant reaction progress variable for the tangential strain rate and the principal curvature. New insights are gained which will greatly aid the development of modeling approaches.

Milk flow rates from bottle nipples used after hospital discharge

PubMed Central

Pados, Britt Frisk; Park, Jinhee; Thoyre, Suzanne M.; Estrem, Hayley; Nix, W. Brant

2016-01-01

Purpose To test the milk flow rates and variability in flow rates of bottle nipples used after hospital discharge. Study Design and Methods Twenty-six nipple types that represented 15 common brands as well as variety in price per nipple and store location sold (e.g., Babies R’ Us, Walmart, Dollar Store) were chosen for testing. Ten of each nipple type (n=260 total) were tested by measuring the amount of infant formula expressed in one minute using a breast pump. Mean milk flow rate (mL/min) and coefficient of variation (CV) were calculated. Flow rates of nipples within brand were compared statistically. Results Milk flow rates varied from 1.68 mL/min for the Avent Natural Newborn Flow to 85.34 mL/min for the Dr. Brown’s Standard Y-cut. Variability between nipple types also varied widely, from .03 for the Dr. Brown’s Standard Level 3 to .37 for MAM Nipple 1 Slow Flow. Clinical Implications The extreme range of milk flow rates found may be significant for medically fragile infants being discharged home who are continuing to develop oral feeding skills. The name of the nipple does not provide clear information about the flow rate to guide parents in decision-making. Variability in flow rates within nipples of the same type may complicate oral feeding for the medically fragile infant who may not be able to adapt easily to change in flow rates. Both flow rate and variability should be considered when guiding parents to a nipple choice. PMID:27008466

[Evaluation of autonomic nervous system function with heart rate variability analysis in patients with hyperthyroidism and during euthyroidism after pharmacologic and surgical treatment].

PubMed

Barczyński, M; Tabor, S; Thor, P

1997-01-01

The aim of the present study was both to estimate autonomic nervous system (ANS) function in patients with hyperthyroidism by the heart rate variability (HRV) analysis and to evaluate the impact of pharmacological and surgical treatment on the ANS function. Analysis of the HRV underwent 10 female patients in course of thyreotoxicosis and after reaching full clinical and biochemical euthyroidism, after pharmacological therapy and in month after surgical treatment. The 10 minutes records at rest, in horizontal position were evaluated. The HRV parameters like mean of the heart rate, mean of RR intervals, standard deviation of all normal RR intervals (SDNN), range of the heart rate variability, low frequency (LF), high frequency (HF) components of the heart rate power spectral density and LF/HF ratio were assessed. The results were compared to those obtained from 10 age-, sex-, and body mass index-matched control subjects. The statistical significance (p < 0.05) was found in reduction of range of RR intervals, in increase of LF/HF ratio and in decrease of SDNN in hyperthyroidism in comparison to the control group (151.6/346.8 ms; 2.4/0.74; 24.4/57.2 ms2). In course of pharmacological euthyroidism there were statistically significant (p < 0.05) increase of range of RR intervals, reduction of LF/HF ratio and increase of SDNN in comparison to hyperthyroidism (270/151.6 ms; 0.995/2.4; 39/24.4 ms2). In euthyroidism after surgical treatment all the above parameters kept the similar levels as in pharmacological euthyroidism (no statistical significance for p < 0.05). On the base of the outcomes it was considered that in hyperthyroid patients there is advantage of sympathetic part of ANS over parasympathetic one which is due to sharp reduction of parasympathetic system activity. Pharmacological therapy with thyreostatics normalises balance of ANS to the level of the control group and after surgical treatment the balance keeps the same. Moreover, in the estimation of ANS as important as LF/HF ratio is the mean range of RR intervals.

ARTiiFACT: a tool for heart rate artifact processing and heart rate variability analysis.

PubMed

Kaufmann, Tobias; Sütterlin, Stefan; Schulz, Stefan M; Vögele, Claus

2011-12-01

The importance of appropriate handling of artifacts in interbeat interval (IBI) data must not be underestimated. Even a single artifact may cause unreliable heart rate variability (HRV) results. Thus, a robust artifact detection algorithm and the option for manual intervention by the researcher form key components for confident HRV analysis. Here, we present ARTiiFACT, a software tool for processing electrocardiogram and IBI data. Both automated and manual artifact detection and correction are available in a graphical user interface. In addition, ARTiiFACT includes time- and frequency-based HRV analyses and descriptive statistics, thus offering the basic tools for HRV analysis. Notably, all program steps can be executed separately and allow for data export, thus offering high flexibility and interoperability with a whole range of applications.

PREDICTION OF VO2PEAK USING OMNI RATINGS OF PERCEIVED EXERTION FROM A SUBMAXIMAL CYCLE EXERCISE TEST

PubMed Central

Mays, Ryan J.; Goss, Fredric L.; Nagle-Stilley, Elizabeth F.; Gallagher, Michael; Schafer, Mark A.; Kim, Kevin H.; Robertson, Robert J.

2015-01-01

Summary The primary aim of this study was to develop statistical models to predict peak oxygen consumption (VO2peak) using OMNI Ratings of Perceived Exertion measured during submaximal cycle ergometry. Men (mean ± standard error: 20.90 ± 0.42 yrs) and women (21.59 ± 0.49 yrs) participants (n = 81) completed a load-incremented maximal cycle ergometer exercise test. Simultaneous multiple linear regression was used to develop separate VO2peak statistical models using submaximal ratings of perceived exertion for the overall body, legs, and chest/breathing as predictor variables. VO2peak (L·min−1) predicted for men and women from ratings of perceived exertion for the overall body (3.02 ± 0.06; 2.03 ± 0.04), legs (3.02 ± 0.06; 2.04 ± 0.04) and chest/breathing (3.02 ± 0.05; 2.03 ± 0.03) were similar with measured VO2peak (3.02 ± 0.10; 2.03 ± 0.06, ps > .05). Statistical models based on submaximal OMNI Ratings of Perceived Exertion provide an easily administered and accurate method to predict VO2peak. PMID:25068750

The AMRL Anthropometric Data Bank Library: Volumes 1-5

DTIC Science & Technology

1977-10-01

crinion arc (#127) which were not measured on bald and balding men. Non-metric variables on the tape include somatotype ratings, both by the Sheldon...158). An analysis of the somatotype material was pub- lished as A Statistical Comparison of the Body Typing Methods of Hooton and Sheldon by C

Comparative Analysis Between Computed and Conventional Inferior Alveolar Nerve Block Techniques.

PubMed

Araújo, Gabriela Madeira; Barbalho, Jimmy Charles Melo; Dias, Tasiana Guedes de Souza; Santos, Thiago de Santana; Vasconcellos, Ricardo José de Holanda; de Morais, Hécio Henrique Araújo

2015-11-01

The aim of this randomized, double-blind, controlled trial was to compare the computed and conventional inferior alveolar nerve block techniques in symmetrically positioned inferior third molars. Both computed and conventional anesthetic techniques were performed in 29 healthy patients (58 surgeries) aged between 18 and 40 years. The anesthetic of choice was 2% lidocaine with 1: 200,000 epinephrine. The Visual Analogue Scale assessed the pain variable after anesthetic infiltration. Patient satisfaction was evaluated using the Likert Scale. Heart and respiratory rates, mean time to perform technique, and the need for additional anesthesia were also evaluated. Pain variable means were higher for the conventional technique as compared with computed, 3.45 ± 2.73 and 2.86 ± 1.96, respectively, but no statistically significant differences were found (P > 0.05). Patient satisfaction showed no statistically significant differences. The average computed technique runtime and the conventional were 3.85 and 1.61 minutes, respectively, showing statistically significant differences (P <0.001). The computed anesthetic technique showed lower mean pain perception, but did not show statistically significant differences when contrasted to the conventional technique.

The effects of acupuncture on rates of clinical pregnancy among women undergoing in vitro fertilization: a systematic review and meta-analysis

PubMed Central

Manheimer, Eric; van der Windt, Daniëlle; Cheng, Ke; Stafford, Kristen; Liu, Jianping; Tierney, Jayne; Lao, Lixing; Berman, Brian M.; Langenberg, Patricia; Bouter, Lex M.

2013-01-01

BACKGROUND Recent systematic reviews of adjuvant acupuncture for IVF have pooled heterogeneous trials, without examining variables that might explain the heterogeneity. The aims of our meta-analysis were to quantify the overall pooled effects of adjuvant acupuncture on IVF clinical pregnancy success rates, and evaluate whether study design-, treatment- and population-related factors influence effect estimates. METHODS We included randomized controlled trials that compared needle acupuncture administered within 1 day of embryo transfer, versus sham acupuncture or no adjuvant treatment. Our primary outcome was clinical pregnancy rates. We obtained from all investigators additional methodological details and outcome data not included in their original publications. We analysed sham-controlled and no adjuvant treatment-controlled trials separately, but since there were no large or significant differences between these two subsets, we pooled all trials for subgroup analyses. We prespecified 11 subgroup variables (5 clinical and 6 methodological) to investigate sources of heterogeneity, using single covariate meta-regressions. RESULTS Sixteen trials (4021 participants) were included in the meta-analyses. There was no statistically significant difference between acupuncture and controls when combining all trials [risk ratio (RR) 1.12, 95% confidence interval (CI), 0.96–1.31; I2 = 68%; 16 trials; 4021 participants], or when restricting to sham-controlled (RR 1.02, 0.83–1.26; I2 = 66%; 7 trials; 2044 participants) or no adjuvant treatment-controlled trials (RR 1.22, 0.97–1.52; I2 = 67%; 9 trials; 1977 participants). The type of control used did not significantly explain the statistical heterogeneity (interaction P = 0.27). Baseline pregnancy rate, measured as the observed rate of clinical pregnancy in the control group of each trial, was a statistically significant effect modifier (interaction P < 0.001), and this covariate explained most of the heterogeneity of the effects of adjuvant acupuncture across all trials (adjusted R2 = 93%; I2 residual = 9%). Trials with lower control group rates of clinical pregnancy showed larger effects of adjuvant acupuncture (RR 1.53, 1.28–1.84; 7 trials; 1732 participants) than trials with higher control group rates of clinical pregnancy (RR 0.90, 0.80–1.01; 9 trials; 2289 participants). The asymmetric funnel plot showed a tendency for the intervention effects to be more beneficial in smaller trials. CONCLUSIONS We found no pooled benefit of adjuvant acupuncture for IVF. The subgroup finding of a benefit in trials with lower, but not higher, baseline pregnancy rates (the only statistically significant subgroup finding in our earlier review) has been confirmed in this update, and was not explained by any confounding variables evaluated. However, this baseline pregnancy rate subgroup finding among published trials requires further confirmation and exploration in additional studies because of the multiple subgroup tests conducted, the risk of unidentified confounders, the multiple different factors that determine baseline rates, and the possibility of publication bias. PMID:23814102

Characterizing the Joint Effect of Diverse Test-Statistic Correlation Structures and Effect Size on False Discovery Rates in a Multiple-Comparison Study of Many Outcome Measures

NASA Technical Reports Server (NTRS)

Feiveson, Alan H.; Ploutz-Snyder, Robert; Fiedler, James

2011-01-01

In their 2009 Annals of Statistics paper, Gavrilov, Benjamini, and Sarkar report the results of a simulation assessing the robustness of their adaptive step-down procedure (GBS) for controlling the false discovery rate (FDR) when normally distributed test statistics are serially correlated. In this study we extend the investigation to the case of multiple comparisons involving correlated non-central t-statistics, in particular when several treatments or time periods are being compared to a control in a repeated-measures design with many dependent outcome measures. In addition, we consider several dependence structures other than serial correlation and illustrate how the FDR depends on the interaction between effect size and the type of correlation structure as indexed by Foerstner s distance metric from an identity. The relationship between the correlation matrix R of the original dependent variables and R, the correlation matrix of associated t-statistics is also studied. In general R depends not only on R, but also on sample size and the signed effect sizes for the multiple comparisons.

[Infant mortality by cause of death in the Rio de Janeiro metropolitan area, 1976-1986: association with socioeconomic, climatic and air pollution variables].

PubMed

Duchiade, M P; Beltrao, K I

1992-01-01

The Metropolitan Region of Rio de Janeiro (RMR) consists of the capital (the city of Rio de Janeiro) and 13 surrounding cities. The city of Rio de Janeiro itself was divided into 24 rather heterogeneous administrative regions (RAS) based on the income level of their inhabitants, the supply of public services such as water and sewerage, and population density or air pollution. Three different socioeconomic covariables were selected in three residential zones (ZONA) or subareas: the central rich nucleus, the intermediary zone of transition, and the distant periphery. As dependent variables the specific rate of infant, neonatal, or postneonatal mortality were considered for causes. The RMRJ Civil Register mortality data were utilized. A factor of correction was estimated according to the technique of Brass using the fertility rate and the rate of delivery for specific 5-year age groups of mothers. A multivariate analysis, the adjusted generalized linear model (MLG), was used for studying associations between socioeconomic, climatic, and air pollution variables and the levels of mortality. The MLG was formulated by means of the statistical package, GLIM or Generalized Linear Interactive Modelling. Analysis of infant mortality trends during 1976-1986 for the large subareas of RMRJ and the outlying region showed that the peak months of total neonatal and perinatal mortality were March and February, while the lowest months were November and October. May and June represented maximum rates of postneonatal mortality for pneumonia, diarrhea, other respiratory infections, malnutrition, and other diseases. MLG indicated that there was a statistically significant association between the annual mortality rate for selected causes and socioeconomic indicators (INS, FS and Zona); the rates of mortality also varied depending on time (ANO and ANOQ); and the mortality rates also appeared to be associated with the variations of the log of average pollution (LPM).

Inferring time derivatives including cell growth rates using Gaussian processes

NASA Astrophysics Data System (ADS)

Swain, Peter S.; Stevenson, Keiran; Leary, Allen; Montano-Gutierrez, Luis F.; Clark, Ivan B. N.; Vogel, Jackie; Pilizota, Teuta

2016-12-01

Often the time derivative of a measured variable is of as much interest as the variable itself. For a growing population of biological cells, for example, the population's growth rate is typically more important than its size. Here we introduce a non-parametric method to infer first and second time derivatives as a function of time from time-series data. Our approach is based on Gaussian processes and applies to a wide range of data. In tests, the method is at least as accurate as others, but has several advantages: it estimates errors both in the inference and in any summary statistics, such as lag times, and allows interpolation with the corresponding error estimation. As illustrations, we infer growth rates of microbial cells, the rate of assembly of an amyloid fibril and both the speed and acceleration of two separating spindle pole bodies. Our algorithm should thus be broadly applicable.

Assessment of spatial variation of risks in small populations.

PubMed Central

Riggan, W B; Manton, K G; Creason, J P; Woodbury, M A; Stallard, E

1991-01-01

Often environmental hazards are assessed by examining the spatial variation of disease-specific mortality or morbidity rates. These rates, when estimated for small local populations, can have a high degree of random variation or uncertainty associated with them. If those rate estimates are used to prioritize environmental clean-up actions or to allocate resources, then those decisions may be influenced by this high degree of uncertainty. Unfortunately, the effect of this uncertainty is not to add "random noise" into the decision-making process, but to systematically bias action toward the smallest populations where uncertainty is greatest and where extreme high and low rate deviations are most likely to be manifest by chance. We present a statistical procedure for adjusting rate estimates for differences in variability due to differentials in local area population sizes. Such adjustments produce rate estimates for areas that have better properties than the unadjusted rates for use in making statistically based decisions about the entire set of areas. Examples are provided for county variation in bladder, stomach, and lung cancer mortality rates for U.S. white males for the period 1970 to 1979. PMID:1820268

FDR doesn't Tell the Whole Story: Joint Influence of Effect Size and Covariance Structure on the Distribution of the False Discovery Proportions

NASA Technical Reports Server (NTRS)

Feiveson, Alan H.; Ploutz-Snyder, Robert; Fiedler, James

2011-01-01

As part of a 2009 Annals of Statistics paper, Gavrilov, Benjamini, and Sarkar report results of simulations that estimated the false discovery rate (FDR) for equally correlated test statistics using a well-known multiple-test procedure. In our study we estimate the distribution of the false discovery proportion (FDP) for the same procedure under a variety of correlation structures among multiple dependent variables in a MANOVA context. Specifically, we study the mean (the FDR), skewness, kurtosis, and percentiles of the FDP distribution in the case of multiple comparisons that give rise to correlated non-central t-statistics when results at several time periods are being compared to baseline. Even if the FDR achieves its nominal value, other aspects of the distribution of the FDP depend on the interaction between signed effect sizes and correlations among variables, proportion of true nulls, and number of dependent variables. We show examples where the mean FDP (the FDR) is 10% as designed, yet there is a surprising probability of having 30% or more false discoveries. Thus, in a real experiment, the proportion of false discoveries could be quite different from the stipulated FDR.

Economic correlates of violent death rates in forty countries, 1962-2008: A cross-typological analysis.

PubMed

Lee, Bandy X; Marotta, Phillip L; Blay-Tofey, Morkeh; Wang, Winnie; de Bourmont, Shalila

2014-01-01

Our goal was to identify if there might be advantages to combining two major public health concerns, i.e., homicides and suicides, in an analysis with well-established macro-level economic determinants, i.e., unemployment and inequality. Mortality data, unemployment statistics, and inequality measures were obtained for 40 countries for the years 1962-2008. Rates of combined homicide and suicide, ratio of suicide to combined violent death, and ratio between homicide and suicide were graphed and analyzed. A fixed effects regression model was then performed for unemployment rates and Gini coefficients on homicide, suicide, and combined death rates. For a majority of nation states, suicide comprised a substantial proportion (mean 75.51%; range 0-99%) of the combined rate of homicide and suicide. When combined, a small but significant relationship emerged between logged Gini coefficient and combined death rates (0.0066, p < 0.05), suggesting that the combined rate improves the ability to detect a significant relationship when compared to either rate measurement alone. Results were duplicated by age group, whereby combining death rates into a single measure improved statistical power, provided that the association was strong. Violent deaths, when combined, were associated with an increase in unemployment and an increase in Gini coefficient, creating a more robust variable. As the effects of macro-level factors (e.g., social and economic policies) on violent death rates in a population are shown to be more significant than those of micro-level influences (e.g., individual characteristics), these associations may be useful to discover. An expansion of socioeconomic variables and the inclusion of other forms of violence in future research could help elucidate long-term trends.

Economic correlates of violent death rates in forty countries, 1962–2008: A cross-typological analysis

PubMed Central

Lee, Bandy X.; Marotta, Phillip L.; Blay-Tofey, Morkeh; Wang, Winnie; de Bourmont, Shalila

2015-01-01

Objectives Our goal was to identify if there might be advantages to combining two major public health concerns, i.e., homicides and suicides, in an analysis with well-established macro-level economic determinants, i.e., unemployment and inequality. Methods Mortality data, unemployment statistics, and inequality measures were obtained for 40 countries for the years 1962–2008. Rates of combined homicide and suicide, ratio of suicide to combined violent death, and ratio between homicide and suicide were graphed and analyzed. A fixed effects regression model was then performed for unemployment rates and Gini coefficients on homicide, suicide, and combined death rates. Results For a majority of nation states, suicide comprised a substantial proportion (mean 75.51%; range 0–99%) of the combined rate of homicide and suicide. When combined, a small but significant relationship emerged between logged Gini coefficient and combined death rates (0.0066, p < 0.05), suggesting that the combined rate improves the ability to detect a significant relationship when compared to either rate measurement alone. Results were duplicated by age group, whereby combining death rates into a single measure improved statistical power, provided that the association was strong. Conclusions Violent deaths, when combined, were associated with an increase in unemployment and an increase in Gini coefficient, creating a more robust variable. As the effects of macro-level factors (e.g., social and economic policies) on violent death rates in a population are shown to be more significant than those of micro-level influences (e.g., individual characteristics), these associations may be useful to discover. An expansion of socioeconomic variables and the inclusion of other forms of violence in future research could help elucidate long-term trends. PMID:26028985

Voice Tremor in Parkinson's Disease: An Acoustic Study.

PubMed

Gillivan-Murphy, Patricia; Miller, Nick; Carding, Paul

2018-01-30

Voice tremor associated with Parkinson disease (PD) has not been characterized. Its relationship with voice disability and disease variables is unknown. This study aimed to evaluate voice tremor in people with PD (pwPD) and a matched control group using acoustic analysis, and to examine correlations with voice disability and disease variables. Acoustic voice tremor analysis was completed on 30 pwPD and 28 age-gender matched controls. Voice disability (Voice Handicap Index), and disease variables of disease duration, Activities of Daily Living (Unified Parkinson's Disease Rating Scale [UPDRS II]), and motor symptoms related to PD (UPDRS III) were examined for relationship with voice tremor measures. Voice tremor was detected acoustically in pwPD and controls with similar frequency. PwPD had a statistically significantly higher rate of amplitude tremor (Hz) than controls (P = 0.001). Rate of amplitude tremor was negatively and significantly correlated with UPDRS III total score (rho -0.509). For pwPD, the magnitude and periodicity of acoustic tremor was higher than for controls without statistical significance. The magnitude of frequency tremor (Mftr%) was positively and significantly correlated with disease duration (rho 0.463). PwPD had higher Voice Handicap Index total, functional, emotional, and physical subscale scores than matched controls (P < 0.001). Voice disability did not correlate significantly with acoustic voice tremor measures. Acoustic analysis enhances understanding of PD voice tremor characteristics, its pathophysiology, and its relationship with voice disability and disease symptomatology. Copyright © 2018 The Voice Foundation. All rights reserved.

Geostatistical interpolation model selection based on ArcGIS and spatio-temporal variability analysis of groundwater level in piedmont plains, northwest China.

PubMed

Xiao, Yong; Gu, Xiaomin; Yin, Shiyang; Shao, Jingli; Cui, Yali; Zhang, Qiulan; Niu, Yong

2016-01-01

Based on the geo-statistical theory and ArcGIS geo-statistical module, datas of 30 groundwater level observation wells were used to estimate the decline of groundwater level in Beijing piedmont. Seven different interpolation methods (inverse distance weighted interpolation, global polynomial interpolation, local polynomial interpolation, tension spline interpolation, ordinary Kriging interpolation, simple Kriging interpolation and universal Kriging interpolation) were used for interpolating groundwater level between 2001 and 2013. Cross-validation, absolute error and coefficient of determination (R(2)) was applied to evaluate the accuracy of different methods. The result shows that simple Kriging method gave the best fit. The analysis of spatial and temporal variability suggest that the nugget effects from 2001 to 2013 were increasing, which means the spatial correlation weakened gradually under the influence of human activities. The spatial variability in the middle areas of the alluvial-proluvial fan is relatively higher than area in top and bottom. Since the changes of the land use, groundwater level also has a temporal variation, the average decline rate of groundwater level between 2007 and 2013 increases compared with 2001-2006. Urban development and population growth cause over-exploitation of residential and industrial areas. The decline rate of the groundwater level in residential, industrial and river areas is relatively high, while the decreasing of farmland area and development of water-saving irrigation reduce the quantity of water using by agriculture and decline rate of groundwater level in agricultural area is not significant.

Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining.

PubMed

Hero, Alfred O; Rajaratnam, Bala

2016-01-01

When can reliable inference be drawn in fue "Big Data" context? This paper presents a framework for answering this fundamental question in the context of correlation mining, wifu implications for general large scale inference. In large scale data applications like genomics, connectomics, and eco-informatics fue dataset is often variable-rich but sample-starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than fue number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for "Big Data". Sample complexity however has received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address fuis gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where fue variable dimension is fixed and fue sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; 3) the purely high dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa cale data dimension. We illustrate this high dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables fua t are of interest. Correlation mining arises in numerous applications and subsumes the regression context as a special case. we demonstrate various regimes of correlation mining based on the unifying perspective of high dimensional learning rates and sample complexity for different structured covariance models and different inference tasks.

Dose-Response Calculator for ArcGIS

USGS Publications Warehouse

Hanser, Steven E.; Aldridge, Cameron L.; Leu, Matthias; Nielsen, Scott E.

2011-01-01

The Dose-Response Calculator for ArcGIS is a tool that extends the Environmental Systems Research Institute (ESRI) ArcGIS 10 Desktop application to aid with the visualization of relationships between two raster GIS datasets. A dose-response curve is a line graph commonly used in medical research to examine the effects of different dosage rates of a drug or chemical (for example, carcinogen) on an outcome of interest (for example, cell mutations) (Russell and others, 1982). Dose-response curves have recently been used in ecological studies to examine the influence of an explanatory dose variable (for example, percentage of habitat cover, distance to disturbance) on a predicted response (for example, survival, probability of occurrence, abundance) (Aldridge and others, 2008). These dose curves have been created by calculating the predicted response value from a statistical model at different levels of the explanatory dose variable while holding values of other explanatory variables constant. Curves (plots) developed using the Dose-Response Calculator overcome the need to hold variables constant by using values extracted from the predicted response surface of a spatially explicit statistical model fit in a GIS, which include the variation of all explanatory variables, to visualize the univariate response to the dose variable. Application of the Dose-Response Calculator can be extended beyond the assessment of statistical model predictions and may be used to visualize the relationship between any two raster GIS datasets (see example in tool instructions). This tool generates tabular data for use in further exploration of dose-response relationships and a graph of the dose-response curve.

Statistical physics and physiology: monofractal and multifractal approaches

NASA Technical Reports Server (NTRS)

Stanley, H. E.; Amaral, L. A.; Goldberger, A. L.; Havlin, S.; Peng, C. K.

1999-01-01

Even under healthy, basal conditions, physiologic systems show erratic fluctuations resembling those found in dynamical systems driven away from a single equilibrium state. Do such "nonequilibrium" fluctuations simply reflect the fact that physiologic systems are being constantly perturbed by external and intrinsic noise? Or, do these fluctuations actually, contain useful, "hidden" information about the underlying nonequilibrium control mechanisms? We report some recent attempts to understand the dynamics of complex physiologic fluctuations by adapting and extending concepts and methods developed very recently in statistical physics. Specifically, we focus on interbeat interval variability as an important quantity to help elucidate possibly non-homeostatic physiologic variability because (i) the heart rate is under direct neuroautonomic control, (ii) interbeat interval variability is readily measured by noninvasive means, and (iii) analysis of these heart rate dynamics may provide important practical diagnostic and prognostic information not obtainable with current approaches. The analytic tools we discuss may be used on a wider range of physiologic signals. We first review recent progress using two analysis methods--detrended fluctuation analysis and wavelets--sufficient for quantifying monofractual structures. We then describe recent work that quantifies multifractal features of interbeat interval series, and the discovery that the multifractal structure of healthy subjects is different than that of diseased subjects.

Experimental design data for the biosynthesis of citric acid using Central Composite Design method.

PubMed

Kola, Anand Kishore; Mekala, Mallaiah; Goli, Venkat Reddy

2017-06-01

In the present investigation, we report that statistical design and optimization of significant variables for the microbial production of citric acid from sucrose in presence of filamentous fungi A. niger NCIM 705. Various combinations of experiments were designed with Central Composite Design (CCD) of Response Surface Methodology (RSM) for the production of citric acid as a function of six variables. The variables are; initial sucrose concentration, initial pH of medium, fermentation temperature, incubation time, stirrer rotational speed, and oxygen flow rate. From experimental data, a statistical model for this process has been developed. The optimum conditions reported in the present article are initial concentration of sucrose of 163.6 g/L, initial pH of medium 5.26, stirrer rotational speed of 247.78 rpm, incubation time of 8.18 days, fermentation temperature of 30.06 °C and flow rate of oxygen of 1.35 lpm. Under optimum conditions the predicted maximum citric acid is 86.42 g/L. The experimental validation carried out under the optimal values and reported citric acid to be 82.0 g/L. The model is able to represent the experimental data and the agreement between the model and experimental data is good.

Land Change Trends in the Great Plains: Linkages to Climate Variability and Socioeconomic Drivers

NASA Astrophysics Data System (ADS)

Drummond, M. A.

2009-12-01

Land use and land cover change have complex linkages to climate variability and change, socioeconomic driving forces, and land management challenges. To assess these land change dynamics and their driving forces in the Great Plains, we compare and contrast contemporary land conversion across seventeen ecoregions using Landsat remote sensing data and statistical analysis. Large area change analysis in agricultural regions is often hampered by the potential for substantial change detection error and the tendency for land conversions to occur in relatively small patches at the local level. To facilitate a regional scale analysis, a statistical sampling design of randomly selected 10-km by 10-km blocks is used in order to efficiently identify the types and rates of land conversions for four time periods between 1972 and 2000, stratified by relatively homogenous ecoregions. Results show a range of rates and processes of land change that vary by ecoregion contingent on the prevailing interactions between socioeconomic and environmental factors such as climate variability, water availability, and land quality. Ecoregions have differential climate and biophysical advantages for agricultural production and other land use change. Human actions further strengthen or dampen the characteristics of change through farm policy, technological advances, economic opportunities, population and demographic shifts, and surface and groundwater irrigation.

Clinical safety assessment of oral higenamine supplementation in healthy, young men.

PubMed

Bloomer, R J; Schriefer, J M; Gunnels, T A

2015-10-01

Higenamine, an herbal agent also known as norcoclaurine, is thought to stimulate β-androgenic receptors and possess lipolytic activity. It is currently making its way into the dietary supplement market. To our knowledge, no studies have been conducted to determine the safety profile of oral higenamine when used alone and in conjunction with other commonly used lipolytic agents. Forty-eight men were assigned to ingest either a placebo, higenamine, caffeine, or higenamine + caffeine + yohimbe bark extract daily for a period of 8 weeks. Before and after 4 and 8 weeks of supplementation, the following variables were measured: resting respiratory rate, heart rate, blood pressure, urinalysis, complete blood count, metabolic panel, liver enzyme activity, and lipid panel. No interaction effects were noted for any variable (p > 0.05), with no changes of statistical significance occurring across time for any of the four conditions (p > 0.05). This is the first study to determine the safety profile of oral higenamine intake in human subjects. Our data indicate that 8 weeks of daily higenamine supplementation, either alone or in conjunction with caffeine and yohimbe bark extract, does not result in a statistically significant change in any of the measured outcome variables. Additional studies, inclusive of a larger sample size, are needed to extend these initial findings. © The Author(s) 2015.

Inequalities in suicide mortality rates and the economic recession in the municipalities of Catalonia, Spain.

PubMed

Saurina, Carme; Marzo, Manel; Saez, Marc

2015-09-08

While previous research already exists on the impact of the current economic crisis and whether it leads to an increase in mortality by suicide, our objective in this paper is to determine if the increase in the suicide rate in Catalonia, Spain from 2010 onwards has been statistically significant and whether it is associated with rising unemployment. We used hierarchical mixed models, separately considering the crude death rate of suicides for municipalities with more than and less than 10,000 inhabitants as dependent variables both unstratified and stratified according to gender and/or age group. In municipalities with 10,000 or more inhabitants there was an increase in the relative risk of suicide from 2009 onwards. This increase was only statistically significant for working-aged women (16-64 years). In municipalities with less than 10,000 inhabitants the relative risk showed a decreasing trend even after 2009. In no case did we find the unemployment rate to be associated (statistically significant) with the suicide rate. The increase in the suicide rate from 2010 in Catalonia was not statistically significant as a whole, with the exception of working-aged women (16-64 years) living in municipalities with 10,000 or more inhabitants. We have not found this increase to be associated with rising unemployment in any of the cases. Future research into the effects of economic recessions on suicide mortality should take into account inequalities by age, sex and size of municipalities.

Stochastic variation in avian survival rates: Life-history predictions, population consequences, and the potential responses to human perturbations and climate change

USGS Publications Warehouse

Schmutz, Joel A.; Thomson, David L.; Cooch, Evan G.; Conroy, Michael J.

2009-01-01

Stochastic variation in survival rates is expected to decrease long-term population growth rates. This expectation influences both life-history theory and the conservation of species. From this expectation, Pfister (1998) developed the important life-history prediction that natural selection will have minimized variability in those elements of the annual life cycle (such as adult survival rate) with high sensitivity. This prediction has not been rigorously evaluated for bird populations, in part due to statistical difficulties related to variance estimation. I here overcome these difficulties, and in an analysis of 62 populations, I confirm her prediction by showing a negative relationship between the proportional sensitivity (elasticity) of adult survival and the proportional variance (CV) of adult survival. However, several species deviated significantly from this expectation, with more process variance in survival than predicted. For instance, projecting the magnitude of process variance in annual survival for American redstarts (Setophaga ruticilla) for 25 years resulted in a 44% decline in abundance without assuming any change in mean survival rate. For most of these species with high process variance, recent changes in harvest, habitats, or changes in climate patterns are the likely sources of environmental variability causing this variability in survival. Because of climate change, environmental variability is increasing on regional and global scales, which is expected to increase stochasticity in vital rates of species. Increased stochasticity in survival will depress population growth rates, and this result will magnify the conservation challenges we face.

Spatial clusters of suicide in the municipality of São Paulo 1996-2005: an ecological study.

PubMed

Bando, Daniel H; Moreira, Rafael S; Pereira, Julio C R; Barrozo, Ligia V

2012-08-23

In a classical study, Durkheim mapped suicide rates, wealth, and low family density and realized that they clustered in northern France. Assessing others variables, such as religious society, he constructed a framework for the analysis of the suicide, which still allows international comparisons using the same basic methodology. The present study aims to identify possible significantly clusters of suicide in the city of São Paulo, and then, verify their statistical associations with socio-economic and cultural characteristics. A spatial scan statistical test was performed to analyze the geographical pattern of suicide deaths of residents in the city of São Paulo by Administrative District, from 1996 to 2005. Relative risks and high and/or low clusters were calculated accounting for gender and age as co-variates, were analyzed using spatial scan statistics to identify geographical patterns. Logistic regression was used to estimate associations with socioeconomic variables, considering, the spatial cluster of high suicide rates as the response variable. Drawing from Durkheim's original work, current World Health Organization (WHO) reports and recent reviews, the following independent variables were considered: marital status, income, education, religion, and migration. The mean suicide rate was 4.1/100,000 inhabitant-years. Against this baseline, two clusters were identified: the first, of increased risk (RR=1.66), comprising 18 districts in the central region; the second, of decreased risk (RR=0.78), including 14 districts in the southern region. The downtown area toward the southwestern region of the city displayed the highest risk for suicide, and though the overall risk may be considered low, the rate climbs up to an intermediate level in this region. One logistic regression analysis contrasted the risk cluster (18 districts) against the other remaining 78 districts, testing the effects of socioeconomic-cultural variables. The following categories of proportion of persons within the clusters were identified as risk factors: singles (OR=2.36), migrants (OR=1.50), Catholics (OR=1.37) and higher income (OR=1.06). In a second logistic model, likewise conceived, the following categories of proportion of persons were identified as protective factors: married (OR=0.49) and Evangelical (OR=0.60). This risk/ protection profile is in accordance with the interpretation that, as a social phenomenon, suicide is related to social isolation. Thus, the classical framework put forward by Durkheim seems to still hold, even though its categorical expression requires re-interpretation.

Determinants of all cause mortality in Poland.

PubMed

Genowska, Agnieszka; Jamiołkowski, Jacek; Szpak, Andrzej; Pajak, Andrzej

2012-01-01

The study objective was to evaluate quantitatively the relationship between demographic characteristics, socio-economic status and medical care resources with all cause mortality in Poland. Ecological study was performed using data for the population of 66 subregions of Poland, obtained from the Central Statistical Office of Poland. The information on the determinants of health and all cause mortality covered the period from 1st January 2005 to 31st December 2010. Results for the repeated measures were analyzed using Generalized Estimating Equations GEE model. In the model 16 independent variables describing health determinants were used, including 6 demographic variables, 6 socio-economic variables, 4 medical care variables. The dependent variable, was age standardized all cause mortality rate. There was a large variation in all cause mortality, demographic features, socio-economic characteristics, and medical care resources by subregion. All cause mortality showed weak associations with demographic features, among which only the increased divorce rate was associated with higher mortality rate. Increased education level, salaries, gross domestic product (GDP) per capita, local government expenditures per capita and the number of non-governmental organizations per 10 thousand population was associated with decrease in all cause mortality. The increase of unemployment rate was related with a decrease of all cause mortality. Beneficial relationship between employment of medical staff and mortality was observed. Variation in mortality from all causes in Poland was explained partly by variation in socio-economic determinants and health care resources.

Forecast Verification: Identification of small changes in weather forecasting skill

NASA Astrophysics Data System (ADS)

Weatherhead, E. C.; Jensen, T. L.

2017-12-01

Global and regonal weather forecasts have improved over the past seven decades most often because of small, incrmental improvements. The identificaiton and verification of forecast improvement due to proposed small changes in forecasting can be expensive and, if not carried out efficiently, can slow progress in forecasting development. This presentation will look at the skill of commonly used verification techniques and show how the ability to detect improvements can depend on the magnitude of the improvement, the number of runs used to test the improvement, the location on the Earth and the statistical techniques used. For continuous variables, such as temperture, wind and humidity, the skill of a forecast can be directly compared using a pair-wise statistical test that accommodates the natural autocorrelation and magnitude of variability. For discrete variables, such as tornado outbreaks, or icing events, the challenges is to reduce the false alarm rate while improving the rate of correctly identifying th discrete event. For both continuus and discrete verification results, proper statistical approaches can reduce the number of runs needed to identify a small improvement in forecasting skill. Verification within the Next Generation Global Prediction System is an important component to the many small decisions needed to make stat-of-the-art improvements to weather forecasting capabilities. The comparison of multiple skill scores with often conflicting results requires not only appropriate testing, but also scientific judgment to assure that the choices are appropriate not only for improvements in today's forecasting capabilities, but allow improvements that will come in the future.

Medicaid reimbursement, prenatal care and infant health.

PubMed

Sonchak, Lyudmyla

2015-12-01

This paper evaluates the impact of state-level Medicaid reimbursement rates for obstetric care on prenatal care utilization across demographic groups. It also uses these rates as an instrumental variable to assess the importance of prenatal care on birth weight. The analysis is conducted using a unique dataset of Medicaid reimbursement rates and 2001-2010 Vital Statistics Natality data. Conditional on county fixed effects, the study finds a modest, but statistically significant positive relationship between Medicaid reimbursement rates and the number of prenatal visits obtained by pregnant women. Additionally, higher rates are associated with an increase in the probability of obtaining adequate care, as well as a reduction in the incidence of going without any prenatal care. However, the effect of an additional prenatal visit on birth weight is virtually zero for black disadvantaged mothers, while an additional visit yields a substantial increase in birth weight of over 20 g for white disadvantaged mothers. Copyright © 2015 Elsevier B.V. All rights reserved.

Using complexity metrics with R-R intervals and BPM heart rate measures

PubMed Central

Wallot, Sebastian; Fusaroli, Riccardo; Tylén, Kristian; Jegindø, Else-Marie

2013-01-01

Lately, growing attention in the health sciences has been paid to the dynamics of heart rate as indicator of impending failures and for prognoses. Likewise, in social and cognitive sciences, heart rate is increasingly employed as a measure of arousal, emotional engagement and as a marker of interpersonal coordination. However, there is no consensus about which measurements and analytical tools are most appropriate in mapping the temporal dynamics of heart rate and quite different metrics are reported in the literature. As complexity metrics of heart rate variability depend critically on variability of the data, different choices regarding the kind of measures can have a substantial impact on the results. In this article we compare linear and non-linear statistics on two prominent types of heart beat data, beat-to-beat intervals (R-R interval) and beats-per-min (BPM). As a proof-of-concept, we employ a simple rest-exercise-rest task and show that non-linear statistics—fractal (DFA) and recurrence (RQA) analyses—reveal information about heart beat activity above and beyond the simple level of heart rate. Non-linear statistics unveil sustained post-exercise effects on heart rate dynamics, but their power to do so critically depends on the type data that is employed: While R-R intervals are very susceptible to non-linear analyses, the success of non-linear methods for BPM data critically depends on their construction. Generally, “oversampled” BPM time-series can be recommended as they retain most of the information about non-linear aspects of heart beat dynamics. PMID:23964244

Why significant variables aren't automatically good predictors.

PubMed

Lo, Adeline; Chernoff, Herman; Zheng, Tian; Lo, Shaw-Hwa

2015-11-10

Thus far, genome-wide association studies (GWAS) have been disappointing in the inability of investigators to use the results of identified, statistically significant variants in complex diseases to make predictions useful for personalized medicine. Why are significant variables not leading to good prediction of outcomes? We point out that this problem is prevalent in simple as well as complex data, in the sciences as well as the social sciences. We offer a brief explanation and some statistical insights on why higher significance cannot automatically imply stronger predictivity and illustrate through simulations and a real breast cancer example. We also demonstrate that highly predictive variables do not necessarily appear as highly significant, thus evading the researcher using significance-based methods. We point out that what makes variables good for prediction versus significance depends on different properties of the underlying distributions. If prediction is the goal, we must lay aside significance as the only selection standard. We suggest that progress in prediction requires efforts toward a new research agenda of searching for a novel criterion to retrieve highly predictive variables rather than highly significant variables. We offer an alternative approach that was not designed for significance, the partition retention method, which was very effective predicting on a long-studied breast cancer data set, by reducing the classification error rate from 30% to 8%.

Variables associated with peripherally inserted central catheter related infection in high risk newborn infants 1

PubMed Central

Rangel, Uesliz Vianna; Gomes, Saint Clair dos Santos; Costa, Ana Maria Aranha Magalhães; Moreira, Maria Elisabeth Lopes

2014-01-01

OBJECTIVE: to relate the variables from a surveillance form for intravenous devices in high risk newborn infants with peripherally inserted central catheter related infection. METHODOLOGY: approximately 15 variables were studied, being associated with peripherally inserted central catheter related infection, this being defined by blood culture results. The variables analyzed were obtained from the surveillance forms used with intravenous devices, attached to the medical records of newborn infants weighing between 500 and 1,499 g. The statistical association was defined using the Chi-squared and Student t tests. The study was approved by the Research Ethics Committee of the Instituto Fernandes Figueira under process N. 140.703/12. RESULTS: 63 medical records were analyzed. The infection rate observed was 25.4%. Of the variables analyzed, only three had a statistically-significant relationship with the blood culture - the use of drugs capable of inhibiting acid secretion, post-natal steroid use, and undertaking more than one invasive procedure (p-value of 0.0141, 0.0472 and 0.0277, respectively). CONCLUSION: the absence of significance of the variables of the form may be related to the quality of the records and to the absence of standardization. It is recommended that the teams be encouraged to adhere to the protocol and fill out the form. PMID:25493681

Application of Statistic Experimental Design to Assess the Effect of Gammairradiation Pre-Treatment on the Drying Characteristics and Qualities of Wheat

NASA Astrophysics Data System (ADS)

Yu, Yong; Wang, Jun

Wheat, pretreated by 60Co gamma irradiation, was dried by hot-air with irradiation dosage 0-3 kGy, drying temperature 40-60 °C, and initial moisture contents 19-25% (drying basis). The drying characteristics and dried qualities of wheat were evaluated based on drying time, average dehydration rate, wet gluten content (WGC), moisture content of wet gluten (MCWG)and titratable acidity (TA). A quadratic rotation-orthogonal composite experimental design, with three variables (at five levels) and five response functions, and analysis method were employed to study the effect of three variables on the individual response functions. The five response functions (drying time, average dehydration rate, WGC, MCWG, TA) correlated with these variables by second order polynomials consisting of linear, quadratic and interaction terms. A high correlation coefficient indicated the suitability of the second order polynomial to predict these response functions. The linear, interaction and quadratic effects of three variables on the five response functions were all studied.

Organisational injustice and impaired cardiovascular regulation among female employees

PubMed Central

Elovainio, M; Kivimäki, M; Puttonen, S; Lindholm, H; Pohjonen, T; Sinervo, T

2006-01-01

Objectives To examine the relation between perceived organisational justice and cardiovascular reactivity in women. Methods The participants were 57 women working in long term care homes. Heart rate variability and systolic arterial pressure variability were used as markers of autonomic function. Organisational justice was measured using the scale of Moorman. Data on other risk factors were also collected. Results Results from logistic regression models showed that the risk for increased low frequency band systolic arterial pressure variability was 3.8–5.8 times higher in employees with low justice than in employees with high justice. Low perceived justice was also related to an 80% excess risk of reduced high frequency heart rate variability compared to high perceived justice, but this association was not statistically significant. Conclusions These findings are consistent with the hypothesis that cardiac dysregulation is one stress mechanism through which a low perceived justice of decision making procedures and interpersonal treatment increases the risk of health problems in personnel. PMID:16421394

[Differences in the recognition of occupational diseases by sex, occupation and business activity in Spain (1990-2009)].

PubMed

García Gómez, Montserrat; Castañeda López, Rosario; Herrador Ortiz, Zaida; Simón Soria, Fernando

2017-01-09

According to official statistics, men suffer more occupational diseases (OD) than women. Nevertheless, the unequal distribution and participation in the labor markets between men and women should be kept in mind. The purpose was to assess the gender impact in the recognition of OD in Spain, examining interaction and confounding factors. An incidence study of the occupational diseases declared through the official OD reporting forms from 1999 to 2009, provided by the General Subdirectorate of Social and Labor Statistics of the Ministry of Employment and Social Security, was conducted. The variables included were: reporting year, sex, age, occupation and economic activity of the company. Rates and crude relative risks (cRR) by these variables were calculated. Adjusted RR were also computed by using multivariate Poisson regression. During the study period a total of 243,310 OD were reported in Spain, with a sex ratio of men to women of 1.07. Correlation existed between occupation and business activity, thus the OD rates and RR were computed by these variables separately. By occupation, men had a crude RR of 1.067 (95%CI:1.058 to 1.076) versus women, while wen the analysis was adjusted by all the variables, the RR was 0.507 (95%CI:0.502 to 0.512). By economic activity of the company, the sense of risk was reversed too in the adjusted analysis (cRR=1.065, 95%CI:1.056 to 1.074 versus 0.632, 95%CI:0.626 to 0.638). Although crude OD rates were lower in women than in men during the period 1999-2009 in Spain, when these rates were adjusted by company activity or worker occupation, age and year of OD declaration, RRs become almost 50% higher in women than in men for the majority of occupations and types of company activity.

Can statistical linkage of missing variables reduce bias in treatment effect estimates in comparative effectiveness research studies?

PubMed

Crown, William; Chang, Jessica; Olson, Melvin; Kahler, Kristijan; Swindle, Jason; Buzinec, Paul; Shah, Nilay; Borah, Bijan

2015-09-01

Missing data, particularly missing variables, can create serious analytic challenges in observational comparative effectiveness research studies. Statistical linkage of datasets is a potential method for incorporating missing variables. Prior studies have focused upon the bias introduced by imperfect linkage. This analysis uses a case study of hepatitis C patients to estimate the net effect of statistical linkage on bias, also accounting for the potential reduction in missing variable bias. The results show that statistical linkage can reduce bias while also enabling parameter estimates to be obtained for the formerly missing variables. The usefulness of statistical linkage will vary depending upon the strength of the correlations of the missing variables with the treatment variable, as well as the outcome variable of interest.

Statistical estimates of absenteeism attributable to seasonal and pandemic influenza from the Canadian Labour Force Survey

PubMed Central

2011-01-01

Background As many respiratory viruses are responsible for influenza like symptoms, accurate measures of the disease burden are not available and estimates are generally based on statistical methods. The objective of this study was to estimate absenteeism rates and hours lost due to seasonal influenza and compare these estimates with estimates of absenteeism attributable to the two H1N1 pandemic waves that occurred in 2009. Methods Key absenteeism variables were extracted from Statistics Canada's monthly labour force survey (LFS). Absenteeism and the proportion of hours lost due to own illness or disability were modelled as a function of trend, seasonality and proxy variables for influenza activity from 1998 to 2009. Results Hours lost due to the H1N1/09 pandemic strain were elevated compared to seasonal influenza, accounting for a loss of 0.2% of potential hours worked annually. In comparison, an estimated 0.08% of hours worked annually were lost due to seasonal influenza illnesses. Absenteeism rates due to influenza were estimated at 12% per year for seasonal influenza over the 1997/98 to 2008/09 seasons, and 13% for the two H1N1/09 pandemic waves. Employees who took time off due to a seasonal influenza infection took an average of 14 hours off. For the pandemic strain, the average absence was 25 hours. Conclusions This study confirms that absenteeism due to seasonal influenza has typically ranged from 5% to 20%, with higher rates associated with multiple circulating strains. Absenteeism rates for the 2009 pandemic were similar to those occurring for seasonal influenza. Employees took more time off due to the pandemic strain than was typical for seasonal influenza. PMID:21486453

Statistical estimates of absenteeism attributable to seasonal and pandemic influenza from the Canadian Labour Force Survey.

PubMed

Schanzer, Dena L; Zheng, Hui; Gilmore, Jason

2011-04-12

As many respiratory viruses are responsible for influenza like symptoms, accurate measures of the disease burden are not available and estimates are generally based on statistical methods. The objective of this study was to estimate absenteeism rates and hours lost due to seasonal influenza and compare these estimates with estimates of absenteeism attributable to the two H1N1 pandemic waves that occurred in 2009. Key absenteeism variables were extracted from Statistics Canada's monthly labour force survey (LFS). Absenteeism and the proportion of hours lost due to own illness or disability were modelled as a function of trend, seasonality and proxy variables for influenza activity from 1998 to 2009. Hours lost due to the H1N1/09 pandemic strain were elevated compared to seasonal influenza, accounting for a loss of 0.2% of potential hours worked annually. In comparison, an estimated 0.08% of hours worked annually were lost due to seasonal influenza illnesses. Absenteeism rates due to influenza were estimated at 12% per year for seasonal influenza over the 1997/98 to 2008/09 seasons, and 13% for the two H1N1/09 pandemic waves. Employees who took time off due to a seasonal influenza infection took an average of 14 hours off. For the pandemic strain, the average absence was 25 hours. This study confirms that absenteeism due to seasonal influenza has typically ranged from 5% to 20%, with higher rates associated with multiple circulating strains. Absenteeism rates for the 2009 pandemic were similar to those occurring for seasonal influenza. Employees took more time off due to the pandemic strain than was typical for seasonal influenza.

Modeling heart rate variability including the effect of sleep stages

NASA Astrophysics Data System (ADS)

Soliński, Mateusz; Gierałtowski, Jan; Żebrowski, Jan

2016-02-01

We propose a model for heart rate variability (HRV) of a healthy individual during sleep with the assumption that the heart rate variability is predominantly a random process. Autonomic nervous system activity has different properties during different sleep stages, and this affects many physiological systems including the cardiovascular system. Different properties of HRV can be observed during each particular sleep stage. We believe that taking into account the sleep architecture is crucial for modeling the human nighttime HRV. The stochastic model of HRV introduced by Kantelhardt et al. was used as the initial starting point. We studied the statistical properties of sleep in healthy adults, analyzing 30 polysomnographic recordings, which provided realistic information about sleep architecture. Next, we generated synthetic hypnograms and included them in the modeling of nighttime RR interval series. The results of standard HRV linear analysis and of nonlinear analysis (Shannon entropy, Poincaré plots, and multiscale multifractal analysis) show that—in comparison with real data—the HRV signals obtained from our model have very similar properties, in particular including the multifractal characteristics at different time scales. The model described in this paper is discussed in the context of normal sleep. However, its construction is such that it should allow to model heart rate variability in sleep disorders. This possibility is briefly discussed.

A Geostatistical Scaling Approach for the Generation of Non Gaussian Random Variables and Increments

NASA Astrophysics Data System (ADS)

Guadagnini, Alberto; Neuman, Shlomo P.; Riva, Monica; Panzeri, Marco

2016-04-01

We address manifestations of non-Gaussian statistical scaling displayed by many variables, Y, and their (spatial or temporal) increments. Evidence of such behavior includes symmetry of increment distributions at all separation distances (or lags) with sharp peaks and heavy tails which tend to decay asymptotically as lag increases. Variables reported to exhibit such distributions include quantities of direct relevance to hydrogeological sciences, e.g. porosity, log permeability, electrical resistivity, soil and sediment texture, sediment transport rate, rainfall, measured and simulated turbulent fluid velocity, and other. No model known to us captures all of the documented statistical scaling behaviors in a unique and consistent manner. We recently proposed a generalized sub-Gaussian model (GSG) which reconciles within a unique theoretical framework the probability distributions of a target variable and its increments. We presented an algorithm to generate unconditional random realizations of statistically isotropic or anisotropic GSG functions and illustrated it in two dimensions. In this context, we demonstrated the feasibility of estimating all key parameters of a GSG model underlying a single realization of Y by analyzing jointly spatial moments of Y data and corresponding increments. Here, we extend our GSG model to account for noisy measurements of Y at a discrete set of points in space (or time), present an algorithm to generate conditional realizations of corresponding isotropic or anisotropic random field, and explore them on one- and two-dimensional synthetic test cases.

Spatio-temporal analysis of annual rainfall in Crete, Greece

NASA Astrophysics Data System (ADS)

Varouchakis, Emmanouil A.; Corzo, Gerald A.; Karatzas, George P.; Kotsopoulou, Anastasia

2018-03-01

Analysis of rainfall data from the island of Crete, Greece was performed to identify key hydrological years and return periods as well as to analyze the inter-annual behavior of the rainfall variability during the period 1981-2014. The rainfall spatial distribution was also examined in detail to identify vulnerable areas of the island. Data analysis using statistical tools and spectral analysis were applied to investigate and interpret the temporal course of the available rainfall data set. In addition, spatial analysis techniques were applied and compared to determine the rainfall spatial distribution on the island of Crete. The analysis presented that in contrast to Regional Climate Model estimations, rainfall rates have not decreased, while return periods vary depending on seasonality and geographic location. A small but statistical significant increasing trend was detected in the inter-annual rainfall variations as well as a significant rainfall cycle almost every 8 years. In addition, statistically significant correlation of the island's rainfall variability with the North Atlantic Oscillation is identified for the examined period. On the other hand, regression kriging method combining surface elevation as secondary information improved the estimation of the annual rainfall spatial variability on the island of Crete by 70% compared to ordinary kriging. The rainfall spatial and temporal trends on the island of Crete have variable characteristics that depend on the geographical area and on the hydrological period.

Improvements in sub-grid, microphysics averages using quadrature based approaches

NASA Astrophysics Data System (ADS)

Chowdhary, K.; Debusschere, B.; Larson, V. E.

2013-12-01

Sub-grid variability in microphysical processes plays a critical role in atmospheric climate models. In order to account for this sub-grid variability, Larson and Schanen (2013) propose placing a probability density function on the sub-grid cloud microphysics quantities, e.g. autoconversion rate, essentially interpreting the cloud microphysics quantities as a random variable in each grid box. Random sampling techniques, e.g. Monte Carlo and Latin Hypercube, can be used to calculate statistics, e.g. averages, on the microphysics quantities, which then feed back into the model dynamics on the coarse scale. We propose an alternate approach using numerical quadrature methods based on deterministic sampling points to compute the statistical moments of microphysics quantities in each grid box. We have performed a preliminary test on the Kessler autoconversion formula, and, upon comparison with Latin Hypercube sampling, our approach shows an increased level of accuracy with a reduction in sample size by almost two orders of magnitude. Application to other microphysics processes is the subject of ongoing research.

Predicting fire spread in Arizona's oak chaparral

Treesearch

A. W. Lindenmuth; James R. Davis

1973-01-01

Five existing fire models, both experimental and theoretical, did not adequately predict rate-of-spread (ROS) when tested on single- and multiclump fires in oak chaparral in Arizona. A statistical model developed using essentially the same input variables but weighted differently accounted for 81 percent ofthe variation in ROS. A chemical coefficient that accounts for...

An investigation of a low-variability tire treadwear test procedure and of treadwear adjustment for ambient temperature. Volume 1 : the test procedures, statistical analyses, and the findings

DOT National Transportation Integrated Search

1985-01-01

The program was conducted to evaluate the variation in tire treadwear rates as : experienced on identical vehicles during the various environmental exposure : conditions of the winter, spring, and summer seasons. The diurnal/nocturnal effect : on the...

The Impact of United States Monetary Policy in the Crude Oil futures market

NASA Astrophysics Data System (ADS)

Padilla-Padilla, Fernando M.

This research examines the empirical impact the United States monetary policy, through the federal fund interest rate, has on the volatility in the crude oil price in the futures market. Prior research has shown how macroeconomic events and variables have impacted different financial markets within short and long--term movements. After testing and decomposing the variables, the two stationary time series were analyzed using a Vector Autoregressive Model (VAR). The empirical evidence shows, with statistical significance, a direct relationship when explaining crude oil prices as function of fed fund rates (t-1) and an indirect relationship when explained as a function of fed fund rates (t-2). These results partially address the literature review lacunas within the topic of the existing implication monetary policy has within the crude oil futures market.

Online ratings of orthopedic surgeons: analysis of 2185 reviews.

PubMed

Bakhsh, Wajeeh; Mesfin, Addisu

2014-08-01

Online ratings of orthopedic surgeons have not been studied. We conducted a study to evaluate the online ratings of orthopedic surgeons in a major metropolitan region, to identify trends in ratings of orthopedic surgeons, and to analyze ratings to identify variables of significance in determining overall rating. Website traffic was used to identify the 8 busiest physician rating websites: AngiesList.com, EverydayHealth.com, Thirdage.com, Yelp.com, HealthGrades.com, Vitals.com, UCompareHealthcare.com, and RateMDs.com. These websites were consulted for data regarding orthopedic surgeons in a major metropolitan region with a population of 1.3 million in September 2012. Surgeon ratings were scaled from 0 to 100 for homogeneity. Of the 8 websites considered, 4 were excluded because of inaccessible or unreliable data. The qualifying sites were HealthGrades.com, Vitals.com, UCompareHealthcare.com, and RateMDs.com, with 2185 reviews total. Across these websites, mean overall rating of orthopedic surgeons was 81.8 (between 100, definitely recommend, and 80, mostly recommend). Five variables were statistically significant (Ps < .01) for higher ratings: ease of scheduling, time spent with patient, wait time, surgeon proficiency/knowledge, and bedside manner.

A data compression technique for synthetic aperture radar images

NASA Technical Reports Server (NTRS)

Frost, V. S.; Minden, G. J.

1986-01-01

A data compression technique is developed for synthetic aperture radar (SAR) imagery. The technique is based on an SAR image model and is designed to preserve the local statistics in the image by an adaptive variable rate modification of block truncation coding (BTC). A data rate of approximately 1.6 bit/pixel is achieved with the technique while maintaining the image quality and cultural (pointlike) targets. The algorithm requires no large data storage and is computationally simple.

Spatial analysis of participation in the Waterloo Residential Energy Efficiency Project

NASA Astrophysics Data System (ADS)

Song, Ge Bella

Researchers are in broad agreement that energy-conserving actions produce economic as well as energy savings. Household energy rating systems (HERS) have been established in many countries to inform households of their house's current energy performance and to help reduce their energy consumption and greenhouse gas emissions. In Canada, the national EnerGuide for Houses (EGH) program is delivered by many local delivery agents, including non-profit green community organizations. Waterloo Region Green Solutions is the local non-profit that offers the EGH residential energy evaluation service to local households. The purpose of this thesis is to explore the determinants of household's participation in the residential energy efficiency program (REEP) in Waterloo Region, to explain the relationship between the explanatory variables and REEP participation, and to propose ways to improve this kind of program. A spatial (trend) analysis was conducted within a geographic information system (GIS) to determine the spatial patterns of the REEP participation in Waterloo Region from 1999 to 2006. The impact of sources of information on participation and relationships between participation rates and explanatory variables were identified. GIS proved successful in presenting a visual interpretation of spatial patterns of the REEP participation. In general, the participating households tend to be clustered in urban areas and scattered in rural areas. Different sources of information played significant roles in reaching participants in different years. Moreover, there was a relationship between each explanatory variable and the REEP participation rates. Statistical analysis was applied to obtain a quantitative assessment of relationships between hypothesized explanatory variables and participation in the REEP. The Poisson regression model was used to determine the relationship between hypothesized explanatory variables and REEP participation at the CDA level. The results show that all of the independent variables have a statistically significant positive relationship with REEP participation. These variables include level of education, average household income, employment rate, home ownership, population aged 65 and over, age of home, and number of eligible dwellings. The logistic regression model was used to assess the ability of the hypothesized explanatory variables to predict whether or not households would participate in a second follow-up evaluation after completing upgrades to their home. The results show all the explanatory variables have significant relationships with the dependent variable. The increased rating score, average household income, aged population, and age of home are positively related to the dependent variable. While the dwelling size and education has negative relationships with the dependent variable. In general, the contribution of this work provides a practical understanding of how the energy efficiency program operates, and insight into the type of variables that may be successful in bringing about changes in performance in the energy efficiency project in Waterloo Region. Secondly, with the completion of this research, future residential energy efficiency programs can use the information from this research and emulate or expand upon the efforts and lessons learned from the Residential Energy Efficiency Project in Waterloo Region case study. Thirdly, this research also contributes to practical experience on how to integrate different datasets using GIS.

Statistical theory of nucleation in the presence of uncharacterized impurities

NASA Astrophysics Data System (ADS)

Sear, Richard P.

2004-08-01

First order phase transitions proceed via nucleation. The rate of nucleation varies exponentially with the free-energy barrier to nucleation, and so is highly sensitive to variations in this barrier. In practice, very few systems are absolutely pure, there are typically some impurities present which are rather poorly characterized. These interact with the nucleus, causing the barrier to vary, and so must be taken into account. Here the impurity-nucleus interactions are modelled by random variables. The rate then has the same form as the partition function of Derrida’s random energy model, and as in this model there is a regime in which the behavior is non-self-averaging. Non-self-averaging nucleation is nucleation with a rate that varies significantly from one realization of the random variables to another. In experiment this corresponds to variation in the nucleation rate from one sample to another. General analytic expressions are obtained for the crossover from a self-averaging to a non-self-averaging rate of nucleation.

Identifying the Bottom Line after a Stock Market Crash

NASA Astrophysics Data System (ADS)

Roehner, B. M.

In this empirical paper we show that in the months following a crash there is a distinct connection between the fall of stock prices and the increase in the range of interest rates for a sample of bonds. This variable, which is often referred to as the interest rate spread variable, can be considered as a statistical measure for the disparity in lenders' opinions about the future; in other words, it provides an operational definition of the uncertainty faced by economic agents. The observation that there is a strong negative correlation between stock prices and the spread variable relies on the examination of eight major crashes in the United States between 1857 and 1987. That relationship which has remained valid for one and a half century in spite of important changes in the organization of financial markets can be of interest in the perspective of Monte Carlo simulations of stock markets.

AUTONOMIC CONTROL OF HEART RATE AFTER EXERCISE IN TRAINED WRESTLERS

PubMed Central

Báez, San Martín E.; Von Oetinger, A.; Cañas, Jamett R.; Ramírez, Campillo R.

2013-01-01

The objective of this study was to establish differences in vagal reactivation, through heart rate recovery and heart rate variability post exercise, in Brazilian jiu-jitsu wrestlers (BJJW). A total of 18 male athletes were evaluated, ten highly trained (HT) and eight moderately trained (MT), who performed a maximum incremental test. At the end of the exercise, the R-R intervals were recorded during the first minute of recovery. We calculated heart rate recovery (HRR60s), and performed linear and non-linear (standard deviation of instantaneous beat-to-beat R-R interval variability – SD1) analysis of heart rate variability (HRV), using the tachogram of the first minute of recovery divided into four segments of 15 s each (0-15 s, 15-30 s, 30-45 s, 45-60 s). Between HT and MT individuals, there were statistically significant differences in HRR60s (p <0.05) and in the non linear analysis of HRV from SD130-45s (p <0.05) and SD145-60s (p <0.05). The results of this research suggest that heart rate kinetics during the first minute after exercise are related to training level and can be used as an index for autonomic cardiovascular control in BJJW. PMID:24744476

Autonomic control of heart rate after exercise in trained wrestlers.

PubMed

Henríquez, Olguín C; Báez, San Martín E; Von Oetinger, A; Cañas, Jamett R; Ramírez, Campillo R

2013-06-01

The objective of this study was to establish differences in vagal reactivation, through heart rate recovery and heart rate variability post exercise, in Brazilian jiu-jitsu wrestlers (BJJW). A total of 18 male athletes were evaluated, ten highly trained (HT) and eight moderately trained (MT), who performed a maximum incremental test. At the end of the exercise, the R-R intervals were recorded during the first minute of recovery. We calculated heart rate recovery (HRR60s), and performed linear and non-linear (standard deviation of instantaneous beat-to-beat R-R interval variability - SD1) analysis of heart rate variability (HRV), using the tachogram of the first minute of recovery divided into four segments of 15 s each (0-15 s, 15-30 s, 30-45 s, 45-60 s). Between HT and MT individuals, there were statistically significant differences in HRR60s (p <0.05) and in the non linear analysis of HRV from SD130-45s (p <0.05) and SD145-60s (p <0.05). The results of this research suggest that heart rate kinetics during the first minute after exercise are related to training level and can be used as an index for autonomic cardiovascular control in BJJW.

Superimpositional assessment of treatment-associated changes in the temporomandibular joint and the mandibular symphysis.

PubMed

Baumrind, S; Korn, E L; Isaacson, R J; West, E E; Molthen, R

1983-12-01

This article analyzes differences in the measured displacement of the condyle and of progonion when different vectors of force are delivered to the maxilla in the course of non-full-banded, Phase 1, mixed-dentition treatment for the correction of Class II malocclusion. The 238-case sample is identical to that for which changes in other parameters of facial form have been reported previously. Relative to superimposition on anterior cranial base and measured in a Frankfort-plane-determined coordinate system, we have attempted to identify and quantitate (1) the displacement of each structure which results from local remodeling and (2) the displacement of each structure which occurs as a secondary consequence of changes in other regions of the skull. We have also attempted to isolate treatment effects from those attributable to spontaneous growth and development. At the condyle, we note that in all three treatment groups and in the control group there is a small but real downward and backward displacement of the glenoid fossa. This change is not treatment induced but, rather, is associated with spontaneous growth and development. (See Fig. 5.) Some interesting differences in pattern of "growth at the condyle" were noted between samples. In the intraoral (modified activator) sample, there were small but statistically significant increases in growth rate as compared to the untreated group of Class II controls. To our surprise, similar statistically significant increases over the growth rate of the control group were noted in the cervical sample. (See Table III, variables 17 and 18.) Small but statistically significant differences between treatments were also noted in the patterns of change at pogonion. As compared to the untreated control group, the rate of total displacement in the modified activator group was significantly greater in the forward direction, while the rate of total displacement in the cervical group was significantly greater in the downward direction. There were no statistically significant differences in the rate of total displacement of pogonion between the high-pull sample and the control sample. (See Table IV, variables 21 and 22.

Prognostic grouping of metastatic prostate cancer using conventional pretreatment prognostic factors.

PubMed

Mikkola, Arto; Aro, Jussi; Rannikko, Sakari; Ruutu, Mirja

2009-01-01

To develop three prognostic groups for disease specific mortality based on the binary classified pretreatment variables age, haemoglobin concentration (Hb), erythrocyte sedimentation rate (ESR), alkaline phosphatase (ALP), prostate-specific antigen (PSA), plasma testosterone and estradiol level in hormonally treated patients with metastatic prostate cancer (PCa). The present study comprised 200 Finnprostate 6 study patients, but data on all variables were not known for every patient. The patients were divided into three prognostic risk groups (Rgs) using the prognostically best set of pretreatment variables. The best set was found by backward stepwise selection and the effect of every excluded variable on the binary classification cut-off points of the remaining variables was checked and corrected when needed. The best group of variables was ALP, PSA, ESR and age. All data were known in 142 patients. Patients were given one risk point each for ALP > 180 U/l (normal value 60-275 U/l), PSA > 35 microg/l, ESR > 80 mm/h and age < 60 years. Three risk groups were formed: Rg-a (0-1 risk points), Rg-b (2 risk points) and Rg-c (3-4 risk points). The risk of death from PCa increased statistically significantly with advancing prognostic group. Patients with metastatic PCa can be divided into three statistically significantly different prognostic risk groups for PCa-specific mortality by using the binary classified pretreatment variables ALP, PSA, ESR and age.

Significant Pre-Accession Factors Predicting Success or Failure During a Marine Corps Officer’s Initial Service Obligation

DTIC Science & Technology

2015-12-01

WAIVERS ..............................................................................................49  APPENDIX C. DESCRIPTIVE STATISTICS ... Statistics of Dependent Variables. .............................................23  Table 6.  Summary Statistics of Academics Variables...24  Table 7.  Summary Statistics of Application Variables ............................................25  Table 8

Mental Disorder Hospitalizations among Submarine Personnel in the U.S. Navy.

DTIC Science & Technology

1988-03-10

hospitalization rates ( Lilienfeld , 1980). T- tests were used to assess statistical signi- ficance of differences in descriptive variables (McNemar, 1969... Lilienfeld , D. E. Foundations of epidemiology. 2nd ed. New York: Oxford University Press, 1980. McNemar, Q. Psychological statistics. 4th ed. New York: Wiley...0 5/S I milI’l 11 1 ; 𔃻 28 112.5 U-2 11112.2 II~.2.4~ 11111J.6 MICROCOPY RESOLUTION TEST CHART NADONAL BUJR[AU OF STANDARDS Ib3 A IvM Mental

Between-Batch Pharmacokinetic Variability Inflates Type I Error Rate in Conventional Bioequivalence Trials: A Randomized Advair Diskus Clinical Trial.

PubMed

Burmeister Getz, E; Carroll, K J; Mielke, J; Benet, L Z; Jones, B

2017-03-01

We previously demonstrated pharmacokinetic differences among manufacturing batches of a US Food and Drug Administration (FDA)-approved dry powder inhalation product (Advair Diskus 100/50) large enough to establish between-batch bio-inequivalence. Here, we provide independent confirmation of pharmacokinetic bio-inequivalence among Advair Diskus 100/50 batches, and quantify residual and between-batch variance component magnitudes. These variance estimates are used to consider the type I error rate of the FDA's current two-way crossover design recommendation. When between-batch pharmacokinetic variability is substantial, the conventional two-way crossover design cannot accomplish the objectives of FDA's statistical bioequivalence test (i.e., cannot accurately estimate the test/reference ratio and associated confidence interval). The two-way crossover, which ignores between-batch pharmacokinetic variability, yields an artificially narrow confidence interval on the product comparison. The unavoidable consequence is type I error rate inflation, to ∼25%, when between-batch pharmacokinetic variability is nonzero. This risk of a false bioequivalence conclusion is substantially higher than asserted by regulators as acceptable consumer risk (5%). © 2016 The Authors Clinical Pharmacology & Therapeutics published by Wiley Periodicals, Inc. on behalf of The American Society for Clinical Pharmacology and Therapeutics.

The Prehospital Sepsis Project: out-of-hospital physiologic predictors of sepsis outcomes.

PubMed

Baez, Amado Alejandro; Hanudel, Priscilla; Wilcox, Susan Renee

2013-12-01

Severe sepsis and septic shock are common, expensive and often fatal medical problems. The care of the critically sick and injured often begins in the prehospital setting; there is limited data available related to predictors and interventions specific to sepsis in the prehospital arena. The objective of this study was to assess the predictive effect of physiologic elements commonly reported in the out-of-hospital setting in the outcomes of patients transported with sepsis. This was a cross-sectional descriptive study. Data from the years 2004-2006 were collected. Adult cases (≥18 years of age) transported by Emergency Medical Services to a major academic center with the diagnosis of sepsis as defined by ICD-9-CM diagnostic codes were included. Descriptive statistics and standard deviations were used to present group characteristics. Chi-square was used for statistical significance and odds ratio (OR) to assess strength of association. Statistical significance was set at the .05 level. Physiologic variables studied included mean arterial pressure (MAP), heart rate (HR), respiratory rate (RR) and shock index (SI). Sixty-three (63) patients were included. Outcome variables included a mean hospital length of stay (HLOS) of 13.75 days (SD = 9.97), mean ventilator days of 4.93 (SD = 7.87), in-hospital mortality of 22 out of 63 (34.9%), and mean intensive care unit length-of-stay (ICU-LOS) of 7.02 days (SD = 7.98). Although SI and RR were found to predict intensive care unit (ICU) admissions, [OR 5.96 (CI, 1.49-25.78; P = .003) and OR 4.81 (CI, 1.16-21.01; P = .0116), respectively] none of the studied variables were found to predict mortality (MAP <65 mmHg: P = .39; HR >90: P = .60; RR >20 P = .11; SI >0.7 P = .35). This study demonstrated that the out-of-hospital shock index and respiratory rate have high predictability for ICU admission. Further studies should include the development of an out-of-hospital sepsis score.

ASCS online fault detection and isolation based on an improved MPCA

NASA Astrophysics Data System (ADS)

Peng, Jianxin; Liu, Haiou; Hu, Yuhui; Xi, Junqiang; Chen, Huiyan

2014-09-01

Multi-way principal component analysis (MPCA) has received considerable attention and been widely used in process monitoring. A traditional MPCA algorithm unfolds multiple batches of historical data into a two-dimensional matrix and cut the matrix along the time axis to form subspaces. However, low efficiency of subspaces and difficult fault isolation are the common disadvantages for the principal component model. This paper presents a new subspace construction method based on kernel density estimation function that can effectively reduce the storage amount of the subspace information. The MPCA model and the knowledge base are built based on the new subspace. Then, fault detection and isolation with the squared prediction error (SPE) statistic and the Hotelling ( T 2) statistic are also realized in process monitoring. When a fault occurs, fault isolation based on the SPE statistic is achieved by residual contribution analysis of different variables. For fault isolation of subspace based on the T 2 statistic, the relationship between the statistic indicator and state variables is constructed, and the constraint conditions are presented to check the validity of fault isolation. Then, to improve the robustness of fault isolation to unexpected disturbances, the statistic method is adopted to set the relation between single subspace and multiple subspaces to increase the corrective rate of fault isolation. Finally fault detection and isolation based on the improved MPCA is used to monitor the automatic shift control system (ASCS) to prove the correctness and effectiveness of the algorithm. The research proposes a new subspace construction method to reduce the required storage capacity and to prove the robustness of the principal component model, and sets the relationship between the state variables and fault detection indicators for fault isolation.

Regression Models and Fuzzy Logic Prediction of TBM Penetration Rate

NASA Astrophysics Data System (ADS)

Minh, Vu Trieu; Katushin, Dmitri; Antonov, Maksim; Veinthal, Renno

2017-03-01

This paper presents statistical analyses of rock engineering properties and the measured penetration rate of tunnel boring machine (TBM) based on the data of an actual project. The aim of this study is to analyze the influence of rock engineering properties including uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), rock brittleness index (BI), the distance between planes of weakness (DPW), and the alpha angle (Alpha) between the tunnel axis and the planes of weakness on the TBM rate of penetration (ROP). Four (4) statistical regression models (two linear and two nonlinear) are built to predict the ROP of TBM. Finally a fuzzy logic model is developed as an alternative method and compared to the four statistical regression models. Results show that the fuzzy logic model provides better estimations and can be applied to predict the TBM performance. The R-squared value (R2) of the fuzzy logic model scores the highest value of 0.714 over the second runner-up of 0.667 from the multiple variables nonlinear regression model.

Eutrophication risk assessment in coastal embayments using simple statistical models.

PubMed

Arhonditsis, G; Eleftheriadou, M; Karydis, M; Tsirtsis, G

2003-09-01

A statistical methodology is proposed for assessing the risk of eutrophication in marine coastal embayments. The procedure followed was the development of regression models relating the levels of chlorophyll a (Chl) with the concentration of the limiting nutrient--usually nitrogen--and the renewal rate of the systems. The method was applied in the Gulf of Gera, Island of Lesvos, Aegean Sea and a surrogate for renewal rate was created using the Canberra metric as a measure of the resemblance between the Gulf and the oligotrophic waters of the open sea in terms of their physical, chemical and biological properties. The Chl-total dissolved nitrogen-renewal rate regression model was the most significant, accounting for 60% of the variation observed in Chl. Predicted distributions of Chl for various combinations of the independent variables, based on Bayesian analysis of the models, enabled comparison of the outcomes of specific scenarios of interest as well as further analysis of the system dynamics. The present statistical approach can be used as a methodological tool for testing the resilience of coastal ecosystems under alternative managerial schemes and levels of exogenous nutrient loading.

An examination of predictive variables toward graduation of minority students in science at a selected urban university

NASA Astrophysics Data System (ADS)

Hunter, Evelyn M. Irving

1998-12-01

The purpose of this study was to examine the relationship and predictive power of the variables gender, high school GPA, class rank, SAT scores, ACT scores, and socioeconomic status on the graduation rates of minority college students majoring in the sciences at a selected urban university. Data was examined on these variables as they related to minority students majoring in science. The population consisted of 101 minority college students who had majored in the sciences from 1986 to 1996 at an urban university in the southwestern region of Texas. A non-probability sampling procedure was used in this study. The non-probability sampling procedure in this investigation was incidental sampling technique. A profile sheet was developed to record the information regarding the variables. The composite scores from SAT and ACT testing were used in the study. The dichotomous variables gender and socioeconomic status were dummy coded for analysis. For the gender variable, zero (0) indicated male, and one (1) indicated female. Additionally, zero (0) indicated high SES, and one (1) indicated low SES. Two parametric procedures were used to analyze the data in this investigation. They were the multiple correlation and multiple regression procedures. Multiple correlation is a statistical technique that indicates the relationship between one variable and a combination of two other variables. The variables socioeconomic status and GPA were found to contribute significantly to the graduation rates of minority students majoring in all sciences when combined with chemistry (Hypotheses Two and Four). These variables accounted for 7% and 15% of the respective variance in the graduation rates of minority students in the sciences and in chemistry. Hypotheses One and Three, the predictor variables gender, high school GPA, SAT Total Scores, class rank, and socioeconomic status did not contribute significantly to the graduation rates of minority students in biology and pharmacy.

Mutual information and phase dependencies: measures of reduced nonlinear cardiorespiratory interactions after myocardial infarction.

PubMed

Hoyer, Dirk; Leder, Uwe; Hoyer, Heike; Pompe, Bernd; Sommer, Michael; Zwiener, Ulrich

2002-01-01

The heart rate variability (HRV) is related to several mechanisms of the complex autonomic functioning such as respiratory heart rate modulation and phase dependencies between heart beat cycles and breathing cycles. The underlying processes are basically nonlinear. In order to understand and quantitatively assess those physiological interactions an adequate coupling analysis is necessary. We hypothesized that nonlinear measures of HRV and cardiorespiratory interdependencies are superior to the standard HRV measures in classifying patients after acute myocardial infarction. We introduced mutual information measures which provide access to nonlinear interdependencies as counterpart to the classically linear correlation analysis. The nonlinear statistical autodependencies of HRV were quantified by auto mutual information, the respiratory heart rate modulation by cardiorespiratory cross mutual information, respectively. The phase interdependencies between heart beat cycles and breathing cycles were assessed basing on the histograms of the frequency ratios of the instantaneous heart beat and respiratory cycles. Furthermore, the relative duration of phase synchronized intervals was acquired. We investigated 39 patients after acute myocardial infarction versus 24 controls. The discrimination of these groups was improved by cardiorespiratory cross mutual information measures and phase interdependencies measures in comparison to the linear standard HRV measures. This result was statistically confirmed by means of logistic regression models of particular variable subsets and their receiver operating characteristics.

Features of Heart Rate Variability Capture Regulatory Changes During Kangaroo Care in Preterm Infants.

PubMed

Kommers, Deedee R; Joshi, Rohan; van Pul, Carola; Atallah, Louis; Feijs, Loe; Oei, Guid; Bambang Oetomo, Sidarto; Andriessen, Peter

2017-03-01

To determine whether heart rate variability (HRV) can serve as a surrogate measure to track regulatory changes during kangaroo care, a period of parental coregulation distinct from regulation within the incubator. Nurses annotated the starting and ending times of kangaroo care for 3 months. The pre-kangaroo care, during-kangaroo care, and post-kangaroo care data were retrieved in infants with at least 10 accurately annotated kangaroo care sessions. Eight HRV features (5 in the time domain and 3 in the frequency domain) were used to visually and statistically compare the pre-kangaroo care and during-kangaroo care periods. Two of these features, capturing the percentage of heart rate decelerations and the extent of heart rate decelerations, were newly developed for preterm infants. A total of 191 kangaroo care sessions were investigated in 11 preterm infants. Despite clinically irrelevant changes in vital signs, 6 of the 8 HRV features (SD of normal-to-normal intervals, root mean square of the SD, percentage of consecutive normal-to-normal intervals that differ by >50 ms, SD of heart rate decelerations, high-frequency power, and low-frequency/high-frequency ratio) showed a visible and statistically significant difference (P <.01) between stable periods of kangaroo care and pre-kangaroo care. HRV was reduced during kangaroo care owing to a decrease in the extent of transient heart rate decelerations. HRV-based features may be clinically useful for capturing the dynamic changes in autonomic regulation in response to kangaroo care and other changes in environment and state. Copyright © 2016 Elsevier Inc. All rights reserved.

Temperature, Not Fine Particulate Matter (PM2.5), is Causally Associated with Short-Term Acute Daily Mortality Rates: Results from One Hundred United States Cities

PubMed Central

Cox, Tony; Popken, Douglas; Ricci, Paolo F

2013-01-01

Exposures to fine particulate matter (PM2.5) in air (C) have been suspected of contributing causally to increased acute (e.g., same-day or next-day) human mortality rates (R). We tested this causal hypothesis in 100 United States cities using the publicly available NMMAPS database. Although a significant, approximately linear, statistical C-R association exists in simple statistical models, closer analysis suggests that it is not causal. Surprisingly, conditioning on other variables that have been extensively considered in previous analyses (usually using splines or other smoothers to approximate their effects), such as month of the year and mean daily temperature, suggests that they create strong, nonlinear confounding that explains the statistical association between PM2.5 and mortality rates in this data set. As this finding disagrees with conventional wisdom, we apply several different techniques to examine it. Conditional independence tests for potential causation, non-parametric classification tree analysis, Bayesian Model Averaging (BMA), and Granger-Sims causality testing, show no evidence that PM2.5 concentrations have any causal impact on increasing mortality rates. This apparent absence of a causal C-R relation, despite their statistical association, has potentially important implications for managing and communicating the uncertain health risks associated with, but not necessarily caused by, PM2.5 exposures. PMID:23983662

Some Variables in Relation to Students' Anxiety in Learning Statistics.

ERIC Educational Resources Information Center

Sutarso, Toto

The purpose of this study was to investigate some variables that relate to students' anxiety in learning statistics. The variables included sex, class level, students' achievement, school, mathematical background, previous statistics courses, and race. The instrument used was the 24-item Students' Attitudes Toward Statistics (STATS), which was…

On the Importance of Age-Adjustment Methods in Ecological Studies of Social Determinants of Mortality

PubMed Central

Milyo, Jeffrey; Mellor, Jennifer M

2003-01-01

Objective To illustrate the potential sensitivity of ecological associations between mortality and certain socioeconomic factors to different methods of age-adjustment. Data Sources Secondary analysis employing state-level data from several publicly available sources. Crude and age-adjusted mortality rates for 1990 are obtained from the U.S. Centers for Disease Control. The Gini coefficient for family income and percent of persons below the federal poverty line are from the U.S. Bureau of Labor Statistics. Putnam's (2000) Social Capital Index was downloaded from ; the Social Mistrust Index was calculated from responses to the General Social Survey, following the method described in Kawachi et al. (1997). All other covariates are obtained from the U.S. Census Bureau. Study Design We use least squares regression to estimate the effect of several state-level socioeconomic factors on mortality rates. We examine whether these statistical associations are sensitive to the use of alternative methods of accounting for the different age composition of state populations. Following several previous studies, we present results for the case when only mortality rates are age-adjusted. We contrast these results with those obtained from regressions of crude mortality on age variables. Principal Findings Different age-adjustment methods can cause a change in the sign or statistical significance of the association between mortality and various socioeconomic factors. When age variables are included as regressors, we find no significant association between mortality and either income inequality, minority racial concentration, or social capital. Conclusions Ecological associations between certain socioeconomic factors and mortality may be extremely sensitive to different age-adjustment methods. PMID:14727797

Efficacy of video-guided laryngoscope in airway management skills of medical students.

PubMed

Peirovifar, Ali; Mahmoodpoor, Ata; Golzari, Samad Ej; Soleimanpour, Hassan; Eslampour, Yashar; Fattahi, Vahid

2014-10-01

Video-guided laryngoscopy, though unproven in achieving better success rates of laryngoscopy outcome and intubation, seems to provide better glottic visualization compared with direct laryngoscopy. The objective of this study was to compare the efficacy of video-guided laryngoscope (VGL) in the airway management skills of medical students. Medical students throughout their anesthesiology rotations were enrolled in this study. All students received standard training in the airway management during their course and were randomly allocated into two 20 person groups. In Group D, airway management was performed by direct laryngoscopy via Macintosh blade and in Group G intubation was performed via VGL. Time to intubation, number of laryngoscopy attempts and success rate were noted. Successful intubation was considered as the primary outcome. All data were analyzed using SPSS 16 software. Chi-square and Fisher's exact test were used for analysis of categorical variables. For analyzing continuous variables independent t-test was used. P < 0.05 was considered as statistically significant. Number of laryngoscopy attempts was less in Group G in comparison to Group D; this, however, was statistically insignificant (P: 0.18). Time to intubation was significantly less in Group G as compared to Group D (P: 0.02). Successful intubation in Group G was less frequently when compared to Group D (P: 0.66). Need for attending intervention, esophageal intubation and hypoxemic events during laryngoscopy were less in Group G; this, however, was statistically insignificant. The use of video-guided laryngoscopy improved the first attempt success rate, time to intubation, laryngoscopy attempts and airway management ability of medical students compared to direct laryngoscopy.

The effect of a graphical interpretation of a statistic trend indicator (Trigg's Tracking Variable) on the detection of simulated changes.

PubMed

Kennedy, R R; Merry, A F

2011-09-01

Anaesthesia involves processing large amounts of information over time. One task of the anaesthetist is to detect substantive changes in physiological variables promptly and reliably. It has been previously demonstrated that a graphical trend display of historical data leads to more rapid detection of such changes. We examined the effect of a graphical indication of the magnitude of Trigg's Tracking Variable, a simple statistically based trend detection algorithm, on the accuracy and latency of the detection of changes in a micro-simulation. Ten anaesthetists each viewed 20 simulations with four variables displayed as the current value with a simple graphical trend display. Values for these variables were generated by a computer model, and updated every second; after a period of stability a change occurred to a new random value at least 10 units from baseline. In 50% of the simulations an indication of the rate of change was given by a five level graphical representation of the value of Trigg's Tracking Variable. Participants were asked to indicate when they thought a change was occurring. Changes were detected 10.9% faster with the trend indicator present (mean 13.1 [SD 3.1] cycles vs 14.6 [SD 3.4] cycles, 95% confidence interval 0.4 to 2.5 cycles, P = 0.013. There was no difference in accuracy of detection (median with trend detection 97% [interquartile range 95 to 100%], without trend detection 100% [98 to 100%]), P = 0.8. We conclude that simple statistical trend detection may speed detection of changes during routine anaesthesia, even when a graphical trend display is present.

Human Responses to Climate Variability: The Case of South Africa

NASA Astrophysics Data System (ADS)

Oppenheimer, M.; Licker, R.; Mastrorillo, M.; Bohra-Mishra, P.; Estes, L. D.; Cai, R.

2014-12-01

Climate variability has been associated with a range of societal and individual outcomes including migration, violent conflict, changes in labor productivity, and health impacts. Some of these may be direct responses to changes in mean temperature or precipitation or extreme events, such as displacement of human populations by tropical cyclones. Others may be mediated by a variety of biological, social, or ecological factors such as migration in response to long-term changes in crops yields. Research is beginning to elucidate and distinguish the many channels through which climate variability may influence human behavior (ranging from the individual to the collective, societal level) in order to better understand how to improve resilience in the face of current variability as well as future climate change. Using a variety of data sets from South Africa, we show how climate variability has influenced internal (within country) migration in recent history. We focus on South Africa as it is a country with high levels of internal migration and dramatic temperature and precipitation changes projected for the 21st century. High poverty rates and significant levels of rain-fed, smallholder agriculture leave large portions of South Africa's population base vulnerable to future climate change. In this study, we utilize two complementary statistical models - one micro-level model, driven by individual and household level survey data, and one macro-level model, driven by national census statistics. In both models, we consider the effect of climate on migration both directly (with gridded climate reanalysis data) and indirectly (with agricultural production statistics). With our historical analyses of climate variability, we gain insights into how the migration decisions of South Africans may be influenced by future climate change. We also offer perspective on the utility of micro and macro level approaches in the study of climate change and human migration.

Combining censored and uncensored data in a U-statistic: design and sample size implications for cell therapy research.

PubMed

Moyé, Lemuel A; Lai, Dejian; Jing, Kaiyan; Baraniuk, Mary Sarah; Kwak, Minjung; Penn, Marc S; Wu, Colon O

2011-01-01

The assumptions that anchor large clinical trials are rooted in smaller, Phase II studies. In addition to specifying the target population, intervention delivery, and patient follow-up duration, physician-scientists who design these Phase II studies must select the appropriate response variables (endpoints). However, endpoint measures can be problematic. If the endpoint assesses the change in a continuous measure over time, then the occurrence of an intervening significant clinical event (SCE), such as death, can preclude the follow-up measurement. Finally, the ideal continuous endpoint measurement may be contraindicated in a fraction of the study patients, a change that requires a less precise substitution in this subset of participants.A score function that is based on the U-statistic can address these issues of 1) intercurrent SCE's and 2) response variable ascertainments that use different measurements of different precision. The scoring statistic is easy to apply, clinically relevant, and provides flexibility for the investigators' prospective design decisions. Sample size and power formulations for this statistic are provided as functions of clinical event rates and effect size estimates that are easy for investigators to identify and discuss. Examples are provided from current cardiovascular cell therapy research.

Statistical Quality Control of Moisture Data in GEOS DAS

NASA Technical Reports Server (NTRS)

Dee, D. P.; Rukhovets, L.; Todling, R.

1999-01-01

A new statistical quality control algorithm was recently implemented in the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The final step in the algorithm consists of an adaptive buddy check that either accepts or rejects outlier observations based on a local statistical analysis of nearby data. A basic assumption in any such test is that the observed field is spatially coherent, in the sense that nearby data can be expected to confirm each other. However, the buddy check resulted in excessive rejection of moisture data, especially during the Northern Hemisphere summer. The analysis moisture variable in GEOS DAS is water vapor mixing ratio. Observational evidence shows that the distribution of mixing ratio errors is far from normal. Furthermore, spatial correlations among mixing ratio errors are highly anisotropic and difficult to identify. Both factors contribute to the poor performance of the statistical quality control algorithm. To alleviate the problem, we applied the buddy check to relative humidity data instead. This variable explicitly depends on temperature and therefore exhibits a much greater spatial coherence. As a result, reject rates of moisture data are much more reasonable and homogeneous in time and space.

Structure and covariance of cloud and rain water in marine stratocumulus

NASA Astrophysics Data System (ADS)

Witte, Mikael; Morrison, Hugh; Gettelman, Andrew

2017-04-01

Many state of the art cloud microphysics parameterizations in large-scale models use assumed probability density functions (pdfs) to represent subgrid scale variability of relevant resolved scale variables such as vertical velocity and cloud liquid water content (LWC). Integration over the assumed pdfs of small scale variability results in physically consistent prediction of nonlinear microphysical process rates and obviates the need to apply arbitrary tuning parameters to the calculated rates. In such parameterizations, the covariance of cloud and rain LWC is an important quantity for parameterizing the accretion process by which rain drops grow via collection of cloud droplets. This covariance has been diagnosed by other workers from a variety of observational and model datasets (Boutle et al., 2013; Larson and Griffin, 2013; Lebsock et al., 2013), but there is poor agreement in findings across the studies. Two key assumptions that may explain some of the discrepancies among past studies are 1) LWC (both cloud and rain) distributions are statistically stationary and 2) spatial structure may be neglected. Given the highly intermittent nature of precipitation and the fact that cloud LWC has been found to be poorly represented by stationary pdfs (e.g. Marshak et al., 1997), neither of the aforementioned assumptions are valid. Therefore covariance must be evaluated as a function of spatial scale without the assumption of stationary statistics (i.e. variability cannot be expressed as a fractional standard deviation, which necessitates well-defined first and second moments of the LWC distribution). The present study presents multifractal analyses of both rain and cloud LWC using aircraft data from the VOCALS-REx field campaign to illustrate the importance of spatial structure in microphysical parameterizations and extends the results of Boutle et al. (2013) to provide a parameterization of rain-cloud water covariance as a function of spatial scale without the assumption of statistical stationarity.

Deriving the Intrahepatic Arteriovenous Shunt Rate from CT Images and Biochemical Data Instead of from Arterial Perfusion Scintigraphy in Hepatic Arterial Infusion Chemotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ozaki, Toshiro, E-mail: ganronbun@amail.plala.or.jp; Seki, Hiroshi; Shiina, Makoto

2009-09-15

The purpose of the present study was to elucidate a method for predicting the intrahepatic arteriovenous shunt rate from computed tomography (CT) images and biochemical data, instead of from arterial perfusion scintigraphy, because adverse exacerbated systemic effects may be induced in cases where a high shunt rate exists. CT and arterial perfusion scintigraphy were performed in patients with liver metastases from gastric or colorectal cancer. Biochemical data and tumor marker levels of 33 enrolled patients were measured. The results were statistically verified by multiple regression analysis. The total metastatic hepatic tumor volume (V{sub metastasized}), residual hepatic parenchyma volume (V{sub residual};more » calculated from CT images), and biochemical data were treated as independent variables; the intrahepatic arteriovenous (IHAV) shunt rate (calculated from scintigraphy) was treated as a dependent variable. The IHAV shunt rate was 15.1 {+-} 11.9%. Based on the correlation matrixes, the best correlation coefficient of 0.84 was established between the IHAV shunt rate and V{sub metastasized} (p < 0.01). In the multiple regression analysis with the IHAV shunt rate as the dependent variable, the coefficient of determination (R{sup 2}) was 0.75, which was significant at the 0.1% level with two significant independent variables (V{sub metastasized} and V{sub residual}). The standardized regression coefficients ({beta}) of V{sub metastasized} and V{sub residual} were significant at the 0.1 and 5% levels, respectively. Based on this result, we can obtain a predicted value of IHAV shunt rate (p < 0.001) using CT images. When a high shunt rate was predicted, beneficial and consistent clinical monitoring can be initiated in, for example, hepatic arterial infusion chemotherapy.« less

SCD-HeFT: Use of RR Interval Statistics for Long-term Risk Stratification for Arrhythmic Sudden Cardiac Death

PubMed Central

Au-yeung, Wan-tai M.; Reinhall, Per; Poole, Jeanne E.; Anderson, Jill; Johnson, George; Fletcher, Ross D.; Moore, Hans J.; Mark, Daniel B.; Lee, Kerry L.; Bardy, Gust H.

2015-01-01

Background In the SCD-HeFT a significant fraction of the congestive heart failure (CHF) patients ultimately did not die suddenly from arrhythmic causes. CHF patients will benefit from better tools to identify if ICD therapy is needed. Objective To identify predictor variables from baseline SCD-HeFT patients’ RR intervals that correlate to arrhythmic sudden cardiac death (SCD) and mortality and to design an ICD therapy screening test. Methods Ten predictor variables were extracted from pre-randomization Holter data from 475 patients enrolled in the SCD-HeFT ICD arm using novel and traditional heart rate variability methods. All variables were correlated to SCD using Mann Whitney-Wilcoxon test and receiver operating characteristic analysis. ICD therapy screening tests were designed by minimizing the cost of false classifications. Survival analysis, including log-rank test and Cox models, was also performed. Results α1 and α2 from detrended fluctuation analysis, the ratio of low to high frequency power, the number of PVCs per hour and heart rate turbulence slope are all statistically significant for predicting the occurrences of SCD (p<0.001) and survival (log-rank p<0.01). The most powerful multivariate predictor tool using the Cox Proportional Hazards was α2 with a hazard ratio of 0.0465 (95% CI: 0.00528 – 0.409, p<0.01). Conclusion Predictor variables from RR intervals correlate to the occurrences of SCD and distinguish survival among SCD-HeFT ICD patients. We believe SCD prediction models should incorporate Holter based RR interval analysis to refine ICD patient selection especially in removing patients who are unlikely to benefit from ICD therapy. PMID:26096609

Using the Graded Response Model to Control Spurious Interactions in Moderated Multiple Regression

ERIC Educational Resources Information Center

Morse, Brendan J.; Johanson, George A.; Griffeth, Rodger W.

2012-01-01

Recent simulation research has demonstrated that using simple raw score to operationalize a latent construct can result in inflated Type I error rates for the interaction term of a moderated statistical model when the interaction (or lack thereof) is proposed at the latent variable level. Rescaling the scores using an appropriate item response…

Varsity Sport Participation and Consumption as Two of Several Factors Associated with College Achievement and Attrition.

ERIC Educational Resources Information Center

Henriksen, Larry; And Others

The study reported in this paper used path analysis statistical methodology and an attrition model to examine the separate and combined relationships of several different types of background, personal, and college experience variables with the attained college grade-point average (GPA) and graduation rate for 3,125 Ball State (Indiana) University…

Causality and cointegration analysis between macroeconomic variables and the Bovespa.

PubMed

da Silva, Fabiano Mello; Coronel, Daniel Arruda; Vieira, Kelmara Mendes

2014-01-01

The aim of this study is to analyze the causality relationship among a set of macroeconomic variables, represented by the exchange rate, interest rate, inflation (CPI), industrial production index as a proxy for gross domestic product in relation to the index of the São Paulo Stock Exchange (Bovespa). The period of analysis corresponded to the months from January 1995 to December 2010, making a total of 192 observations for each variable. Johansen tests, through the statistics of the trace and of the maximum eigenvalue, indicated the existence of at least one cointegration vector. In the analysis of Granger (1988) causality tests via error correction, it was found that a short-term causality existed between the CPI and the Bovespa. Regarding the Granger (1988) long-term causality, the results indicated a long-term behaviour among the macroeconomic variables with the BOVESPA. The results of the long-term normalized vector for the Bovespa variable showed that most signals of the cointegration equation parameters are in accordance with what is suggested by the economic theory. In other words, there was a positive behaviour of the GDP and a negative behaviour of the inflation and of the exchange rate (expected to be a positive relationship) in relation to the Bovespa, with the exception of the Selic rate, which was not significant with that index. The variance of the Bovespa was explained by itself in over 90% at the twelfth month, followed by the country risk, with less than 5%.

Causality and Cointegration Analysis between Macroeconomic Variables and the Bovespa

PubMed Central

da Silva, Fabiano Mello; Coronel, Daniel Arruda; Vieira, Kelmara Mendes

2014-01-01

The aim of this study is to analyze the causality relationship among a set of macroeconomic variables, represented by the exchange rate, interest rate, inflation (CPI), industrial production index as a proxy for gross domestic product in relation to the index of the São Paulo Stock Exchange (Bovespa). The period of analysis corresponded to the months from January 1995 to December 2010, making a total of 192 observations for each variable. Johansen tests, through the statistics of the trace and of the maximum eigenvalue, indicated the existence of at least one cointegration vector. In the analysis of Granger (1988) causality tests via error correction, it was found that a short-term causality existed between the CPI and the Bovespa. Regarding the Granger (1988) long-term causality, the results indicated a long-term behaviour among the macroeconomic variables with the BOVESPA. The results of the long-term normalized vector for the Bovespa variable showed that most signals of the cointegration equation parameters are in accordance with what is suggested by the economic theory. In other words, there was a positive behaviour of the GDP and a negative behaviour of the inflation and of the exchange rate (expected to be a positive relationship) in relation to the Bovespa, with the exception of the Selic rate, which was not significant with that index. The variance of the Bovespa was explained by itself in over 90% at the twelth month, followed by the country risk, with less than 5%. PMID:24587019

Effect of Variable Spatial Scales on USLE-GIS Computations

NASA Astrophysics Data System (ADS)

Patil, R. J.; Sharma, S. K.

2017-12-01

Use of appropriate spatial scale is very important in Universal Soil Loss Equation (USLE) based spatially distributed soil erosion modelling. This study aimed at assessment of annual rates of soil erosion at different spatial scales/grid sizes and analysing how changes in spatial scales affect USLE-GIS computations using simulation and statistical variabilities. Efforts have been made in this study to recommend an optimum spatial scale for further USLE-GIS computations for management and planning in the study area. The present research study was conducted in Shakkar River watershed, situated in Narsinghpur and Chhindwara districts of Madhya Pradesh, India. Remote Sensing and GIS techniques were integrated with Universal Soil Loss Equation (USLE) to predict spatial distribution of soil erosion in the study area at four different spatial scales viz; 30 m, 50 m, 100 m, and 200 m. Rainfall data, soil map, digital elevation model (DEM) and an executable C++ program, and satellite image of the area were used for preparation of the thematic maps for various USLE factors. Annual rates of soil erosion were estimated for 15 years (1992 to 2006) at four different grid sizes. The statistical analysis of four estimated datasets showed that sediment loss dataset at 30 m spatial scale has a minimum standard deviation (2.16), variance (4.68), percent deviation from observed values (2.68 - 18.91 %), and highest coefficient of determination (R2 = 0.874) among all the four datasets. Thus, it is recommended to adopt this spatial scale for USLE-GIS computations in the study area due to its minimum statistical variability and better agreement with the observed sediment loss data. This study also indicates large scope for use of finer spatial scales in spatially distributed soil erosion modelling.

Multivariate statistical analysis of a high rate biofilm process treating kraft mill bleach plant effluent.

PubMed

Goode, C; LeRoy, J; Allen, D G

2007-01-01

This study reports on a multivariate analysis of the moving bed biofilm reactor (MBBR) wastewater treatment system at a Canadian pulp mill. The modelling approach involved a data overview by principal component analysis (PCA) followed by partial least squares (PLS) modelling with the objective of explaining and predicting changes in the BOD output of the reactor. Over two years of data with 87 process measurements were used to build the models. Variables were collected from the MBBR control scheme as well as upstream in the bleach plant and in digestion. To account for process dynamics, a variable lagging approach was used for variables with significant temporal correlations. It was found that wood type pulped at the mill was a significant variable governing reactor performance. Other important variables included flow parameters, faults in the temperature or pH control of the reactor, and some potential indirect indicators of biomass activity (residual nitrogen and pH out). The most predictive model was found to have an RMSEP value of 606 kgBOD/d, representing a 14.5% average error. This was a good fit, given the measurement error of the BOD test. Overall, the statistical approach was effective in describing and predicting MBBR treatment performance.

Differentiation of women with premenstrual dysphoric disorder, recurrent brief depression, and healthy controls by daily mood rating dynamics.

PubMed

Pincus, Steven M; Schmidt, Peter J; Palladino-Negro, Paula; Rubinow, David R

2008-04-01

Enhanced statistical characterization of mood-rating data holds the potential to more precisely classify and sub-classify recurrent mood disorders like premenstrual dysphoric disorder (PMDD) and recurrent brief depressive disorder (RBD). We applied several complementary statistical methods to differentiate mood rating dynamics among women with PMDD, RBD, and normal controls (NC). We compared three subgroups of women: NC (n=8); PMDD (n=15); and RBD (n=9) on the basis of daily self-ratings of sadness, study lengths between 50 and 120 days. We analyzed mean levels; overall variability, SD; sequential irregularity, approximate entropy (ApEn); and a quantification of the extent of brief and staccato dynamics, denoted 'Spikiness'. For each of SD, irregularity (ApEn), and Spikiness, we showed highly significant subgroup differences, ANOVA0.001 for each statistic; additionally, many paired subgroup comparisons showed highly significant differences. In contrast, mean levels were indistinct among the subgroups. For SD, normal controls had much smaller levels than the other subgroups, with RBD intermediate. ApEn showed PMDD to be significantly more regular than the other subgroups. Spikiness showed NC and RBD data sets to be much more staccato than their PMDD counterparts, and appears to suitably characterize the defining feature of RBD dynamics. Compound criteria based on these statistical measures discriminated diagnostic subgroups with high sensitivity and specificity. Taken together, the statistical suite provides well-defined specifications of each subgroup. This can facilitate accurate diagnosis, and augment the prediction and evaluation of response to treatment. The statistical methodologies have broad and direct applicability to behavioral studies for many psychiatric disorders, and indeed to similar analyses of associated biological signals across multiple axes.

Effect of partition board color on mood and autonomic nervous function.

PubMed

Sakuragi, Sokichi; Sugiyama, Yoshiki

2011-12-01

The purpose of this study was to evaluate the effects of the presence or absence (control) of a partition board and its color (red, yellow, blue) on subjective mood ratings and changes in autonomic nervous system indicators induced by a video game task. The increase in the mean Profile of Mood States (POMS) Fatigue score and mean Oppressive feeling rating after the task was lowest with the blue partition board. Multiple-regression analysis identified oppressive feeling and error scores on the second half of the task as statistically significant contributors to Fatigue. While explanatory variables were limited to the physiological indices, multiple-regression analysis identified a significant contribution of autonomic reactivity (assessed by heart rate variability) to Fatigue. These results suggest that a blue partition board would reduce task-induced subjective fatigue, in part by lowering the oppressive feeling of being enclosed during the task, possibly by increasing autonomic reactivity.

Fuzzy support vector machines for adaptive Morse code recognition.

PubMed

Yang, Cheng-Hong; Jin, Li-Cheng; Chuang, Li-Yeh

2006-11-01

Morse code is now being harnessed for use in rehabilitation applications of augmentative-alternative communication and assistive technology, facilitating mobility, environmental control and adapted worksite access. In this paper, Morse code is selected as a communication adaptive device for persons who suffer from muscle atrophy, cerebral palsy or other severe handicaps. A stable typing rate is strictly required for Morse code to be effective as a communication tool. Therefore, an adaptive automatic recognition method with a high recognition rate is needed. The proposed system uses both fuzzy support vector machines and the variable-degree variable-step-size least-mean-square algorithm to achieve these objectives. We apply fuzzy memberships to each point, and provide different contributions to the decision learning function for support vector machines. Statistical analyses demonstrated that the proposed method elicited a higher recognition rate than other algorithms in the literature.

Simulating and Predicting Cereal Crop Yields in Ethiopia: Model Calibration and Verification

NASA Astrophysics Data System (ADS)

Yang, M.; Wang, G.; Ahmed, K. F.; Eggen, M.; Adugna, B.; Anagnostou, E. N.

2017-12-01

Agriculture in developing countries are extremely vulnerable to climate variability and changes. In East Africa, most people live in the rural areas with outdated agriculture techniques and infrastructure. Smallholder agriculture continues to play a key role in this area, and the rate of irrigation is among the lowest of the world. As a result, seasonal and inter-annual weather patterns play an important role in the spatiotemporal variability of crop yields. This study investigates how various climate variables (e.g., temperature, precipitation, sunshine) and agricultural practice (e.g., fertilization, irrigation, planting date) influence cereal crop yields using a process-based model (DSSAT) and statistical analysis, and focuses on the Blue Nile Basin of Ethiopia. The DSSAT model is driven with meteorological forcing from the ECMWF's latest reanalysis product that cover the past 35 years; the statistical model will be developed by linking the same meteorological reanalysis data with harvest data at the woreda level from the Ethiopian national dataset. Results from this study will set the stage for the development of a seasonal prediction system for weather and crop yields in Ethiopia, which will serve multiple sectors in coping with the agricultural impact of climate variability.

Effects of Classroom Ventilation Rate and Temperature on Students' Test Scores.

PubMed

Haverinen-Shaughnessy, Ulla; Shaughnessy, Richard J

2015-01-01

Using a multilevel approach, we estimated the effects of classroom ventilation rate and temperature on academic achievement. The analysis is based on measurement data from a 70 elementary school district (140 fifth grade classrooms) from Southwestern United States, and student level data (N = 3109) on socioeconomic variables and standardized test scores. There was a statistically significant association between ventilation rates and mathematics scores, and it was stronger when the six classrooms with high ventilation rates that were indicated as outliers were filtered (> 7.1 l/s per person). The association remained significant when prior year test scores were included in the model, resulting in less unexplained variability. Students' mean mathematics scores (average 2286 points) were increased by up to eleven points (0.5%) per each liter per second per person increase in ventilation rate within the range of 0.9-7.1 l/s per person (estimated effect size 74 points). There was an additional increase of 12-13 points per each 1°C decrease in temperature within the observed range of 20-25°C (estimated effect size 67 points). Effects of similar magnitude but higher variability were observed for reading and science scores. In conclusion, maintaining adequate ventilation and thermal comfort in classrooms could significantly improve academic achievement of students.

Effects of Classroom Ventilation Rate and Temperature on Students’ Test Scores

PubMed Central

2015-01-01

Using a multilevel approach, we estimated the effects of classroom ventilation rate and temperature on academic achievement. The analysis is based on measurement data from a 70 elementary school district (140 fifth grade classrooms) from Southwestern United States, and student level data (N = 3109) on socioeconomic variables and standardized test scores. There was a statistically significant association between ventilation rates and mathematics scores, and it was stronger when the six classrooms with high ventilation rates that were indicated as outliers were filtered (> 7.1 l/s per person). The association remained significant when prior year test scores were included in the model, resulting in less unexplained variability. Students’ mean mathematics scores (average 2286 points) were increased by up to eleven points (0.5%) per each liter per second per person increase in ventilation rate within the range of 0.9–7.1 l/s per person (estimated effect size 74 points). There was an additional increase of 12–13 points per each 1°C decrease in temperature within the observed range of 20–25°C (estimated effect size 67 points). Effects of similar magnitude but higher variability were observed for reading and science scores. In conclusion, maintaining adequate ventilation and thermal comfort in classrooms could significantly improve academic achievement of students. PMID:26317643

PROMISE: a tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables.

PubMed

Pounds, Stan; Cheng, Cheng; Cao, Xueyuan; Crews, Kristine R; Plunkett, William; Gandhi, Varsha; Rubnitz, Jeffrey; Ribeiro, Raul C; Downing, James R; Lamba, Jatinder

2009-08-15

In some applications, prior biological knowledge can be used to define a specific pattern of association of multiple endpoint variables with a genomic variable that is biologically most interesting. However, to our knowledge, there is no statistical procedure designed to detect specific patterns of association with multiple endpoint variables. Projection onto the most interesting statistical evidence (PROMISE) is proposed as a general procedure to identify genomic variables that exhibit a specific biologically interesting pattern of association with multiple endpoint variables. Biological knowledge of the endpoint variables is used to define a vector that represents the biologically most interesting values for statistics that characterize the associations of the endpoint variables with a genomic variable. A test statistic is defined as the dot-product of the vector of the observed association statistics and the vector of the most interesting values of the association statistics. By definition, this test statistic is proportional to the length of the projection of the observed vector of correlations onto the vector of most interesting associations. Statistical significance is determined via permutation. In simulation studies and an example application, PROMISE shows greater statistical power to identify genes with the interesting pattern of associations than classical multivariate procedures, individual endpoint analyses or listing genes that have the pattern of interest and are significant in more than one individual endpoint analysis. Documented R routines are freely available from www.stjuderesearch.org/depts/biostats and will soon be available as a Bioconductor package from www.bioconductor.org.

Pedagogical monitoring as a tool to reduce dropout in distance learning in family health.

PubMed

de Castro E Lima Baesse, Deborah; Grisolia, Alexandra Monteiro; de Oliveira, Ana Emilia Figueiredo

2016-08-22

This paper presents the results of a study of the Monsys monitoring system, an educational support tool designed to prevent and control the dropout rate in a distance learning course in family health. Developed by UNA-SUS/UFMA, Monsys was created to enable data mining in the virtual learning environment known as Moodle. This is an exploratory study using documentary and bibliographic research and analysis of the Monsys database. Two classes (2010 and 2011) were selected as research subjects, one with Monsys intervention and the other without. The samples were matched (using a ration of 1:1) by gender, age, marital status, graduation year, previous graduation status, location and profession. Statistical analysis was performed using the chi-square test and a multivariate logistic regression model with a 5 % significance level. The findings show that the dropout rate in the class in which Monsys was not employed (2010) was 43.2 %. However, the dropout rate in the class of 2011, in which the tool was employed as a pedagogical team aid, was 30.6 %. After statistical adjustment, the Monsys monitoring system remained in correlation with the course completion variable (adjusted OR = 1.74, IC95% = 1.17-2.59; p = 0.005), suggesting that the use of the Monsys tool, isolated to the adjusted variables, can enhance the likelihood that students will complete the course. Using the chi-square test, a profile analysis of students revealed a higher completion rate among women (67.7 %) than men (52.2 %). Analysis of age demonstrated that students between 40 and 49 years dropped out the least (32.1 %) and, with regard to professional training, nurses have the lowest dropout rates (36.3 %). The use of Monsys significantly reduced the dropout, with results showing greater association between the variables denoting presence of the monitoring system and female gender.

Vibration and stretching effects on flexibility and explosive strength in young gymnasts.

PubMed

Kinser, Ann M; Ramsey, Michael W; O'Bryant, Harold S; Ayres, Christopher A; Sands, William A; Stone, Michael H

2008-01-01

Effects of simultaneous vibration-stretching on flexibility and explosive strength in competitive female gymnasts were examined. Twenty-two female athletes (age = 11.3 +/- 2.6 yr; body mass = 35.3 +/- 11.6 kg; competitive levels = 3-9) composed the simultaneous vibration-stretching (VS) group, which performed both tests. Flexibility testing control groups were stretching-only (SF) (N = 7) and vibration-only (VF) (N = 8). Explosive strength-control groups were stretching-only (SES) (N = 8) and vibration-only (VES) (N = 7). Vibration (30 Hz, 2-mm displacement) was applied to four sites, four times for 10 s, with 5 s of rest in between. Right and left forward-split (RFS and LFS) flexibility was measured by the distance between the ground and the anterior suprailiac spine. A force plate (sampling rate, 1000 Hz) recorded countermovement and static jump characteristics. Explosive strength variables included flight time, jump height, peak force, instantaneous forces, and rates of force development. Data were analyzed using Bonferroni adjusted paired t-tests. VS had statistically increased flexibility (P) and large effect sizes (d) in both the RFS (P = 1.28 x 10(-7), d = 0.67) and LFS (P = 2.35 x 10(-7), d = 0.72). VS had statistically different results of favored (FL) (P = 4.67 x 10(-8), d= 0.78) and nonfavored (NFL) (P = 7.97 x 10(-10), d = 0.65) legs. VF resulted in statistical increases in flexibility and medium d on RFS (P = 6.98 x 10(-3), d = 0.25) and statistically increased flexibility on VF NFL flexibility (P = 0.002, d = 0.31). SF had no statistical difference between measures and small d. For explosive strength, there were no statistical differences in variables in the VS, SES, and VES for the pre- versus posttreatment tests. Simultaneous vibration and stretching may greatly increase flexibility while not altering explosive strength.

[Explore objective clinical variables for detecting delirium in ICU patients: a prospective case-control study].

PubMed

Liu, Xiaojiang; Lyu, Jie; An, Youzhong

2017-04-01

The aim of this case-control study is to explore clinical objective variables for diagnosing delirium of intensive care unit (ICU) patients. According to the method of prospective case-control study, critical adult postoperative patients who were transferred to ICU of Peking University People's Hospital from October 2015 to May 2016 and needed mechanical ventilation were included. After evaluating the Richmond agitation sedation scale score (RASS), the patients whose score were -2 or greater were sorted into two groups, delirium and non-delirium, according to the confusion assessment method for the ICU (CAM-ICU). Then these patients were observed by domestic multifunctional detector for electroencephalographic (EEG) variables such as brain lateralization, brain introvert, brain activity, brain energy consumption, focus inward, focus outward, cerebral inhibition, fatigue, sleep severity, sedation index, pain index, anxiety index, fidgety index, stress index and the cerebral blood flow (CBF) index which was named of perfusion index. Other variables including indexes of ICU blood gas analysis, which was consisted of variables of blood gas analysis, routine blood test and biochemistry, previous history and prognostic outcome was recorded. Binary logistic regression was used for multivariate analysis. Forty-three postoperative patients, who needed intensive care, were included. Eighteen were in delirium group and twenty-five in control group. Excluding the trauma, variables like gender, age, temperature, heart rate, respiratory rate, mean arterial pressure, acute physiology and chronic health evaluationII(APACHEII) score, organ failure, dementia and emergency surgery didn't show any statistical significance between two groups. The trauma in delirious patients increased obviously compared with the control group (33.3% vs. 4.0%, P = 0.031). Except for the brain activity [122.47 (88.62, 154.21) vs. 89.40 (86.27, 115.97), P = 0.034], there were no statistical differences in any other EEG and CBF variables. In ICU blood gas analysis, only pH value (7.43±0.42 vs. 7.47±0.31, P = 0.003), chloride concentration [Cl- (mmol/L): 114.66±4.32 vs. 111.90±3.08, P = 0.019], magnesium concentration [Mg2 + (mmol/L): 0.60±0.10 vs. 0.54±0.06, P = 0.035] and blood osmolality [mmol/L: 290.10 (284.15, 306.35) vs. 282.70 (280.20, 286.75), P = 0.014] were statistically significant. Compared with control group, the prognostic variables in delirium group such as duration of mechanical ventilation [days: 125.0 (49.0, 293.0) vs. 149.5 (32.0, 251.3)], length of stay in ICU [days: 216.5 (50.5, 360.8) vs. 190.0 (72.0, 330.5)] and mortality rate (22.2% vs. 24.0%) didn't appear to be statistically significant either (all P > 0.05). It was shown by multivariate logistic regression analysis that pH [odds ratio (OR) = 1.446, 95% confidence interval (95%CI) = 1.116-1.875, P = 0.005] and Cl - (OR = 0.708, 95%CI = 0.531-0.945, P = 0.019) were potential risk factors of delirium. The brain activity of HXD_I may contribute to the clinical diagnose of delirium, but it still remained to be proved further. The pH and Cl - are potential risk factors of delirium.

Effect of plasma arc welding variables on fusion zone grain size and hardness of AISI 321 austenitic stainless steel

NASA Astrophysics Data System (ADS)

Kondapalli, S. P.

2017-12-01

In the present work, pulsed current microplasma arc welding is carried out on AISI 321 austenitic stainless steel of 0.3 mm thickness. Peak current, Base current, Pulse rate and Pulse width are chosen as the input variables, whereas grain size and hardness are considered as output responses. Response surface method is adopted by using Box-Behnken Design, and in total 27 experiments are performed. Empirical relation between input and output response is developed using statistical software and analysis of variance (ANOVA) at 95% confidence level to check the adequacy. The main effect and interaction effect of input variables on output response are also studied.

Analysis of fluid flow and solute transport through a single fracture with variable apertures intersecting a canister: Comparison between fractal and Gaussian fractures

NASA Astrophysics Data System (ADS)

Liu, L.; Neretnieks, I.

Canisters with spent nuclear fuel will be deposited in fractured crystalline rock in the Swedish concept for a final repository. The fractures intersect the canister holes at different angles and they have variable apertures and therefore locally varying flowrates. Our previous model with fractures with a constant aperture and a 90° intersection angle is now extended to arbitrary intersection angles and stochastically variable apertures. It is shown that the previous basic model can be simply amended to account for these effects. More importantly, it has been found that the distributions of the volumetric and the equivalent flow rates are all close to the Normal for both fractal and Gaussian fractures, with the mean of the distribution of the volumetric flow rate being determined solely by the hydraulic aperture, and that of the equivalent flow rate being determined by the mechanical aperture. Moreover, the standard deviation of the volumetric flow rates of the many realizations increases with increasing roughness and spatial correlation length of the aperture field, and so does that of the equivalent flow rates. Thus, two simple statistical relations can be developed to describe the stochastic properties of fluid flow and solute transport through a single fracture with spatially variable apertures. This obviates, then, the need to simulate each fracture that intersects a canister in great detail, and allows the use of complex fractures also in very large fracture network models used in performance assessment.

Variability in home mechanical ventilation prescription.

PubMed

Escarrabill, Joan; Tebé, Cristian; Espallargues, Mireia; Torrente, Elena; Tresserras, Ricard; Argimón, J

2015-10-01

Few studies have analyzed the prevalence and accessibility of home mechanical ventilation (HMV). The aim of this study was to characterize the prevalence of HMV and variability in prescriptions from administrative data. Prescribing rates of HMV in the 37 healthcare sectors of the Catalan Health Service were compared from billing data from 2008 to 2011. Crude accumulated activity rates (per 100,000 population) were calculated using systematic component of variation (SCV) and empirical Bayes (EB) methods. Standardized activity ratios (SAR) were described using a map of healthcare sectors. A crude rate of 23 HMV prescriptions per 100,000 population was observed. Rates increase with age and have increased by 39%. Statistics measuring variation not due to chance show a high variation in women (CSV=0.20 and EB=0.30) and in men (CSV=0.21 and EB=0.40), and were constant over time. In a multilevel Poisson model, hospitals with a chest unit were associated with a greater number of cases (beta=0.68, P<.0001). High variability in prescribing HMV can be explained, in part, by the attitude of professionals towards treatment and accessibility to specialist centers with a chest unit. Analysis of administrative data and variability mapping help identify unexplained variations and, in the absence of systematic records, are a feasible way of tracking treatment. Copyright © 2014 SEPAR. Published by Elsevier Espana. All rights reserved.

Scan statistics with local vote for target detection in distributed system

NASA Astrophysics Data System (ADS)

Luo, Junhai; Wu, Qi

2017-12-01

Target detection has occupied a pivotal position in distributed system. Scan statistics, as one of the most efficient detection methods, has been applied to a variety of anomaly detection problems and significantly improves the probability of detection. However, scan statistics cannot achieve the expected performance when the noise intensity is strong, or the signal emitted by the target is weak. The local vote algorithm can also achieve higher target detection rate. After the local vote, the counting rule is always adopted for decision fusion. The counting rule does not use the information about the contiguity of sensors but takes all sensors' data into consideration, which makes the result undesirable. In this paper, we propose a scan statistics with local vote (SSLV) method. This method combines scan statistics with local vote decision. Before scan statistics, each sensor executes local vote decision according to the data of its neighbors and its own. By combining the advantages of both, our method can obtain higher detection rate in low signal-to-noise ratio environment than the scan statistics. After the local vote decision, the distribution of sensors which have detected the target becomes more intensive. To make full use of local vote decision, we introduce a variable-step-parameter for the SSLV. It significantly shortens the scan period especially when the target is absent. Analysis and simulations are presented to demonstrate the performance of our method.

The use of process models to inform and improve statistical models of nitrate occurrence, Great Miami River Basin, southwestern Ohio

USGS Publications Warehouse

Walter, Donald A.; Starn, J. Jeffrey

2013-01-01

Statistical models of nitrate occurrence in the glacial aquifer system of the northern United States, developed by the U.S. Geological Survey, use observed relations between nitrate concentrations and sets of explanatory variables—representing well-construction, environmental, and source characteristics— to predict the probability that nitrate, as nitrogen, will exceed a threshold concentration. However, the models do not explicitly account for the processes that control the transport of nitrogen from surface sources to a pumped well and use area-weighted mean spatial variables computed from within a circular buffer around the well as a simplified source-area conceptualization. The use of models that explicitly represent physical-transport processes can inform and, potentially, improve these statistical models. Specifically, groundwater-flow models simulate advective transport—predominant in many surficial aquifers— and can contribute to the refinement of the statistical models by (1) providing for improved, physically based representations of a source area to a well, and (2) allowing for more detailed estimates of environmental variables. A source area to a well, known as a contributing recharge area, represents the area at the water table that contributes recharge to a pumped well; a well pumped at a volumetric rate equal to the amount of recharge through a circular buffer will result in a contributing recharge area that is the same size as the buffer but has a shape that is a function of the hydrologic setting. These volume-equivalent contributing recharge areas will approximate circular buffers in areas of relatively flat hydraulic gradients, such as near groundwater divides, but in areas with steep hydraulic gradients will be elongated in the upgradient direction and agree less with the corresponding circular buffers. The degree to which process-model-estimated contributing recharge areas, which simulate advective transport and therefore account for local hydrologic settings, would inform and improve the development of statistical models can be implicitly estimated by evaluating the differences between explanatory variables estimated from the contributing recharge areas and the circular buffers used to develop existing statistical models. The larger the difference in estimated variables, the more likely that statistical models would be changed, and presumably improved, if explanatory variables estimated from contributing recharge areas were used in model development. Comparing model predictions from the two sets of estimated variables would further quantify—albeit implicitly—how an improved, physically based estimate of explanatory variables would be reflected in model predictions. Differences between the two sets of estimated explanatory variables and resultant model predictions vary spatially; greater differences are associated with areas of steep hydraulic gradients. A direct comparison, however, would require the development of a separate set of statistical models using explanatory variables from contributing recharge areas. Area-weighted means of three environmental variables—silt content, alfisol content, and depth to water from the U.S. Department of Agriculture State Soil Geographic (STATSGO) data—and one nitrogen-source variable (fertilizer-application rate from county data mapped to Enhanced National Land Cover Data 1992 (NLCDe 92) agricultural land use) can vary substantially between circular buffers and volume-equivalent contributing recharge areas and among contributing recharge areas for different sets of well variables. The differences in estimated explanatory variables are a function of the same factors affecting the contributing recharge areas as well as the spatial resolution and local distribution of the underlying spatial data. As a result, differences in estimated variables between circular buffers and contributing recharge areas are complex and site specific as evidenced by differences in estimated variables for circular buffers and contributing recharge areas of existing public-supply and network wells in the Great Miami River Basin. Large differences in areaweighted mean environmental variables are observed at the basin scale, determined by using the network of uniformly spaced hypothetical wells; the differences have a spatial pattern that generally is similar to spatial patterns in the underlying STATSGO data. Generally, the largest differences were observed for area-weighted nitrogen-application rate from county and national land-use data; the basin-scale differences ranged from -1,600 (indicating a larger value from within the volume-equivalent contributing recharge area) to 1,900 kilograms per year (kg/yr); the range in the underlying spatial data was from 0 to 2,200 kg/yr. Silt content, alfisol content, and nitrogen-application rate are defined by the underlying spatial data and are external to the groundwater system; however, depth to water is an environmental variable that can be estimated in more detail and, presumably, in a more physically based manner using a groundwater-flow model than using the spatial data. Model-calculated depths to water within circular buffers in the Great Miami River Basin differed substantially from values derived from the spatial data and had a much larger range. Differences in estimates of area-weighted spatial variables result in corresponding differences in predictions of nitrate occurrence in the aquifer. In addition to the factors affecting contributing recharge areas and estimated explanatory variables, differences in predictions also are a function of the specific set of explanatory variables used and the fitted slope coefficients in a given model. For models that predicted the probability of exceeding 1 and 4 milligrams per liter as nitrogen (mg/L as N), predicted probabilities using variables estimated from circular buffers and contributing recharge areas generally were correlated but differed significantly at the local and basin scale. The scale and distribution of prediction differences can be explained by the underlying differences in the estimated variables and the relative weight of the variables in the statistical models. Differences in predictions of exceeding 1 mg/L as N, which only includes environmental variables, generally correlated with the underlying differences in STATSGO data, whereas differences in exceeding 4 mg/L as N were more spatially extensive because that model included environmental and nitrogen-source variables. Using depths to water from within circular buffers derived from the spatial data and depths to water within the circular buffers calculated from the groundwater-flow model, restricted to the same range, resulted in large differences in predicted probabilities. The differences in estimated explanatory variables between contributing recharge areas and circular buffers indicate incorporation of physically based contributing recharge area likely would result in a different set of explanatory variables and an improved set of statistical models. The use of a groundwater-flow model to improve representations of source areas or to provide more-detailed estimates of specific explanatory variables includes a number of limitations and technical considerations. An assumption in these analyses is that (1) there is a state of mass balance between recharge and pumping, and (2) transport to a pumped well is under a steady state flow field. Comparison of volumeequivalent contributing recharge areas under steady-state and transient transport conditions at a location in the southeastern part of the basin shows the steady-state contributing recharge area is a reasonable approximation of the transient contributing recharge area after between 10 and 20 years of pumping. The first assumption is a more important consideration for this analysis. A gradient effect refers to a condition where simulated pumping from a well is less than recharge through the corresponding contributing recharge area. This generally takes place in areas with steep hydraulic gradients, such as near discharge locations, and can be mitigated using a finer model discretization. A boundary effect refers to a condition where recharge through the contributing recharge area is less than pumping. This indicates other sources of water to the simulated well and could reflect a real hydrologic process. In the Great Miami River Basin, large gradient and boundary effects—defined as the balance between pumping and recharge being less than half—occurred in 5 and 14 percent of the basin, respectively. The agreement between circular buffers and volume-equivalent contributing recharge areas, differences in estimated variables, and the effect on statisticalmodel predictions between the population of wells with a balance between pumping and recharge within 10 percent and the population of all wells were similar. This indicated process-model limitations did not affect the overall findings in the Great Miami River Basin; however, this would be model specific, and prudent use of a process model needs to entail a limitations analysis and, if necessary, alterations to the model.

Correlation of radiation dose and heart rate in dual-source computed tomography coronary angiography.

PubMed

Laspas, Fotios; Tsantioti, Dimitra; Roussakis, Arkadios; Kritikos, Nikolaos; Efthimiadou, Roxani; Kehagias, Dimitrios; Andreou, John

2011-04-01

Computed tomography coronary angiography (CTCA) has been widely used since the introduction of 64-slice scanners and dual-source CT technology, but the relatively high radiation dose remains a major concern. To evaluate the relationship between radiation exposure and heart rate (HR), in dual-source CTCA. Data from 218 CTCA examinations, performed with a dual-source 64-slices scanner, were statistically evaluated. Effective radiation dose, expressed in mSv, was calculated as the product of the dose-length product (DLP) times a conversion coefficient for the chest (mSv = DLPx0.017). Heart rate range and mean heart rate, expressed in beats per minute (bpm) of each individual during CTCA, were also provided by the system. Statistical analysis of effective dose and heart rate data was performed by using Pearson correlation coefficient and two-sample t-test. Mean HR and effective dose were found to have a borderline positive relationship. Individuals with a mean HR >65 bpm observed to receive a statistically significant higher effective dose as compared to those with a mean HR ≤65 bpm. Moreover, a strong correlation between effective dose and variability of HR of more than 20 bpm was observed. Dual-source CT scanners are considered to have the capability to provide diagnostic examinations even with high HR and arrhythmias. However, it is desirable to keep the mean heart rate below 65 bpm and heart rate fluctuation less than 20 bpm in order to reduce the radiation exposure.

Statistical variability and confidence intervals for planar dose QA pass rates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bailey, Daniel W.; Nelms, Benjamin E.; Attwood, Kristopher

Purpose: The most common metric for comparing measured to calculated dose, such as for pretreatment quality assurance of intensity-modulated photon fields, is a pass rate (%) generated using percent difference (%Diff), distance-to-agreement (DTA), or some combination of the two (e.g., gamma evaluation). For many dosimeters, the grid of analyzed points corresponds to an array with a low areal density of point detectors. In these cases, the pass rates for any given comparison criteria are not absolute but exhibit statistical variability that is a function, in part, on the detector sampling geometry. In this work, the authors analyze the statistics ofmore » various methods commonly used to calculate pass rates and propose methods for establishing confidence intervals for pass rates obtained with low-density arrays. Methods: Dose planes were acquired for 25 prostate and 79 head and neck intensity-modulated fields via diode array and electronic portal imaging device (EPID), and matching calculated dose planes were created via a commercial treatment planning system. Pass rates for each dose plane pair (both centered to the beam central axis) were calculated with several common comparison methods: %Diff/DTA composite analysis and gamma evaluation, using absolute dose comparison with both local and global normalization. Specialized software was designed to selectively sample the measured EPID response (very high data density) down to discrete points to simulate low-density measurements. The software was used to realign the simulated detector grid at many simulated positions with respect to the beam central axis, thereby altering the low-density sampled grid. Simulations were repeated with 100 positional iterations using a 1 detector/cm{sup 2} uniform grid, a 2 detector/cm{sup 2} uniform grid, and similar random detector grids. For each simulation, %/DTA composite pass rates were calculated with various %Diff/DTA criteria and for both local and global %Diff normalization techniques. Results: For the prostate and head/neck cases studied, the pass rates obtained with gamma analysis of high density dose planes were 2%-5% higher than respective %/DTA composite analysis on average (ranging as high as 11%), depending on tolerances and normalization. Meanwhile, the pass rates obtained via local normalization were 2%-12% lower than with global maximum normalization on average (ranging as high as 27%), depending on tolerances and calculation method. Repositioning of simulated low-density sampled grids leads to a distribution of possible pass rates for each measured/calculated dose plane pair. These distributions can be predicted using a binomial distribution in order to establish confidence intervals that depend largely on the sampling density and the observed pass rate (i.e., the degree of difference between measured and calculated dose). These results can be extended to apply to 3D arrays of detectors, as well. Conclusions: Dose plane QA analysis can be greatly affected by choice of calculation metric and user-defined parameters, and so all pass rates should be reported with a complete description of calculation method. Pass rates for low-density arrays are subject to statistical uncertainty (vs. the high-density pass rate), but these sampling errors can be modeled using statistical confidence intervals derived from the sampled pass rate and detector density. Thus, pass rates for low-density array measurements should be accompanied by a confidence interval indicating the uncertainty of each pass rate.« less

Simulation analysis of air flow and turbulence statistics in a rib grit roughened duct.

PubMed

Vogiatzis, I I; Denizopoulou, A C; Ntinas, G K; Fragos, V P

2014-01-01

The implementation of variable artificial roughness patterns on a surface is an effective technique to enhance the rate of heat transfer to fluid flow in the ducts of solar air heaters. Different geometries of roughness elements investigated have demonstrated the pivotal role that vortices and associated turbulence have on the heat transfer characteristics of solar air heater ducts by increasing the convective heat transfer coefficient. In this paper we investigate the two-dimensional, turbulent, unsteady flow around rectangular ribs of variable aspect ratios by directly solving the transient Navier-Stokes and continuity equations using the finite elements method. Flow characteristics and several aspects of turbulent flow are presented and discussed including velocity components and statistics of turbulence. The results reveal the impact that different rib lengths have on the computed mean quantities and turbulence statistics of the flow. The computed turbulence parameters show a clear tendency to diminish downstream with increasing rib length. Furthermore, the applied numerical method is capable of capturing small-scale flow structures resulting from the direct solution of Navier-Stokes and continuity equations.

A randomized evaluation of a computer-based physician's workstation: design considerations and baseline results.

PubMed Central

Rotman, B. L.; Sullivan, A. N.; McDonald, T.; DeSmedt, P.; Goodnature, D.; Higgins, M.; Suermondt, H. J.; Young, C. Y.; Owens, D. K.

1995-01-01

We are performing a randomized, controlled trial of a Physician's Workstation (PWS), an ambulatory care information system, developed for use in the General Medical Clinic (GMC) of the Palo Alto VA. Goals for the project include selecting appropriate outcome variables and developing a statistically powerful experimental design with a limited number of subjects. As PWS provides real-time drug-ordering advice, we retrospectively examined drug costs and drug-drug interactions in order to select outcome variables sensitive to our short-term intervention as well as to estimate the statistical efficiency of alternative design possibilities. Drug cost data revealed the mean daily cost per physician per patient was 99.3 cents +/- 13.4 cents, with a range from 0.77 cent to 1.37 cents. The rate of major interactions per prescription for each physician was 2.9% +/- 1%, with a range from 1.5% to 4.8%. Based on these baseline analyses, we selected a two-period parallel design for the evaluation, which maximized statistical power while minimizing sources of bias. PMID:8563376

Occurrence of pharmaceutically active compounds during 1-year period in wastewaters from four wastewater treatment plants in Seville (Spain).

PubMed

Santos, J L; Aparicio, I; Callejón, M; Alonso, E

2009-05-30

Several pharmaceutically active compounds have been monitored during 1-year period in influent and effluent wastewater from wastewater treatment plants (WWTPs) to evaluate their temporal evolution and removal from wastewater and to know which variables have influence in their removal rates. Pharmaceutical compounds monitored were four antiinflammatory drugs (diclofenac, ibuprofen, ketoprofen and naproxen), an antiepileptic drug (carbamazepine) and a nervous stimulant (caffeine). All of the pharmaceutically active compounds monitored, except diclofenac, were detected in influent and effluent wastewater. Mean concentrations measured in influent wastewater were 6.17, 0.48, 93.6, 1.83 and 5.41 microg/L for caffeine, carbamazepine, ibuprofen, ketoprofen and naproxen, respectively. Mean concentrations measured in effluent wastewater were 2.02, 0.56, 8.20, 0.84 and 2.10 microg/L for caffeine, carbamazepine, ibuprofen, ketoprofen and naproxen, respectively. Mean removal rates of the pharmaceuticals varied from 8.1% (carbamazepine) to 87.5% (ibuprofen). The existence of relationships between the concentrations of the pharmaceutical compounds, their removal rates, the characterization parameters of influent wastewaters and the WWTP control design parameters has been studied by means of statistical analysis (correlation and principal component analysis). With both statistical analyses, high correlations were obtained between the concentration of the pharmaceutical compounds and the characterization parameters of influent wastewaters; and between the removal rates of the pharmaceutical compounds, the removal rates of the characterization parameters of influent wastewaters and the WWTP hydraulic retention times. Principal component analysis showed the existence of two main components accounting for 76% of the total variability.

Observer Agreement for Measurements in Videolaryngostroboscopy.

PubMed

Brunings, Jan Wouter; Vanbelle, Sophie; Akkermans, Annemarie; Heemskerk, Nienke M M; Kremer, Bernd; Stokroos, Robert J; Baijens, Laura W J

2017-11-06

This study evaluated the levels of intraobserver and interobserver agreement for measurements of visuoperceptual variables in videolaryngostroboscopic examinations and compared the observers' behavior during independent versus consensus panel rating. This is a retrospective study. This study was conducted in a single-center tertiary care facility. Sixty-four patients with dysphonia of heterogeneous etiology were included. All subjects underwent a standardized videolaryngostroboscopic examination. Two experienced and trained observers scored exactly the same examinations, first independently and then on a consensus panel. Specific visuoperceptual variables and the clinical diagnosis (as recommended by the Committee on Phoniatrics and the Phonosurgery Committee of the European Laryngological Society and advised by the American Speech-Language-Hearing Association) were scored. Descriptive and kappa statistics were used. In general, intraobserver agreement was better than agreement between observers for measurements of several variables. The intrapanel observer agreement levels were slightly higher than the intraobserver agreement levels on the independent rating task. When rating on the consensus panel, the observers deviated considerably from the scores they had previously given on the independent rating task. Observer agreement in videolaryngostroboscopic assessment has important implications not only for the diagnosis and treatment of dysphonic patients but also for the interpretation of the results of scientific studies using videolaryngostroboscopic outcome parameters. The identification of factors that can influence the levels of observer agreement can provide a better understanding of the rating process and its limitations. The results of this study suggest that future research could achieve better agreement levels by rating the visuoperceptual variables in a panel setting. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Beyond R 0: Demographic Models for Variability of Lifetime Reproductive Output

PubMed Central

Caswell, Hal

2011-01-01

The net reproductive rate measures the expected lifetime reproductive output of an individual, and plays an important role in demography, ecology, evolution, and epidemiology. Well-established methods exist to calculate it from age- or stage-classified demographic data. As an expectation, provides no information on variability; empirical measurements of lifetime reproduction universally show high levels of variability, and often positive skewness among individuals. This is often interpreted as evidence of heterogeneity, and thus of an opportunity for natural selection. However, variability provides evidence of heterogeneity only if it exceeds the level of variability to be expected in a cohort of identical individuals all experiencing the same vital rates. Such comparisons require a way to calculate the statistics of lifetime reproduction from demographic data. Here, a new approach is presented, using the theory of Markov chains with rewards, obtaining all the moments of the distribution of lifetime reproduction. The approach applies to age- or stage-classified models, to constant, periodic, or stochastic environments, and to any kind of reproductive schedule. As examples, I analyze data from six empirical studies, of a variety of animal and plant taxa (nematodes, polychaetes, humans, and several species of perennial plants). PMID:21738586

Climate drivers on malaria transmission in Arunachal Pradesh, India.

PubMed

Upadhyayula, Suryanaryana Murty; Mutheneni, Srinivasa Rao; Chenna, Sumana; Parasaram, Vaideesh; Kadiri, Madhusudhan Rao

2015-01-01

The present study was conducted during the years 2006 to 2012 and provides information on prevalence of malaria and its regulation with effect to various climatic factors in East Siang district of Arunachal Pradesh, India. Correlation analysis, Principal Component Analysis and Hotelling's T² statistics models are adopted to understand the effect of weather variables on malaria transmission. The epidemiological study shows that the prevalence of malaria is mostly caused by the parasite Plasmodium vivax followed by Plasmodium falciparum. It is noted that, the intensity of malaria cases declined gradually from the year 2006 to 2012. The transmission of malaria observed was more during the rainy season, as compared to summer and winter seasons. Further, the data analysis study with Principal Component Analysis and Hotelling's T² statistic has revealed that the climatic variables such as temperature and rainfall are the most influencing factors for the high rate of malaria transmission in East Siang district of Arunachal Pradesh.

Self-Esteem, Locus of Control, and First-Time NCLEX-RN Passage of BSN Students at Historically Black Colleges and Universities.

PubMed

Chavis, Pamella Ivey

Relationships between self-esteem, locus of control (LOC), and first-time passage of National Council Licensure Examination for Registered Nurses (NCLEX-RN®) were examined at baccalaureate nursing programs at two historically black colleges and universities. Shortages continue to exceed demands for RNs prepared at the baccalaureate level. Inconsistent pass rates on the NCLEX-RN for graduates of historically black colleges and universities impede the supply of RNs. Surveys and archival data were used to examine characteristics of the sample and explore relationships among variables. All participants (N = 90) reported high self-esteem and internal LOC. Models suggested that all those with high self-esteem and internal LOC would pass the NCLEX-RN; only 85 percent passed the first time. Statistical analysis revealed a lack of statistical significance between self-esteem, LOC, and first-time passage. Variables not included in the study may have affected first-time passage.

PROMISE: a tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables

PubMed Central

Pounds, Stan; Cheng, Cheng; Cao, Xueyuan; Crews, Kristine R.; Plunkett, William; Gandhi, Varsha; Rubnitz, Jeffrey; Ribeiro, Raul C.; Downing, James R.; Lamba, Jatinder

2009-01-01

Motivation: In some applications, prior biological knowledge can be used to define a specific pattern of association of multiple endpoint variables with a genomic variable that is biologically most interesting. However, to our knowledge, there is no statistical procedure designed to detect specific patterns of association with multiple endpoint variables. Results: Projection onto the most interesting statistical evidence (PROMISE) is proposed as a general procedure to identify genomic variables that exhibit a specific biologically interesting pattern of association with multiple endpoint variables. Biological knowledge of the endpoint variables is used to define a vector that represents the biologically most interesting values for statistics that characterize the associations of the endpoint variables with a genomic variable. A test statistic is defined as the dot-product of the vector of the observed association statistics and the vector of the most interesting values of the association statistics. By definition, this test statistic is proportional to the length of the projection of the observed vector of correlations onto the vector of most interesting associations. Statistical significance is determined via permutation. In simulation studies and an example application, PROMISE shows greater statistical power to identify genes with the interesting pattern of associations than classical multivariate procedures, individual endpoint analyses or listing genes that have the pattern of interest and are significant in more than one individual endpoint analysis. Availability: Documented R routines are freely available from www.stjuderesearch.org/depts/biostats and will soon be available as a Bioconductor package from www.bioconductor.org. Contact: stanley.pounds@stjude.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19528086

Effect of Aperture Field Variability, Flow Rate, and Ionic Strength on Colloid Transport in Single Fractures: Laboratory-Scale Experiments and Numerical Simulation

NASA Astrophysics Data System (ADS)

Zheng, Q.; Dickson, S.; Guo, Y.

2007-12-01

A good understanding of the physico-chemical processes (i.e., advection, dispersion, attachment/detachment, straining, sedimentation etc.) governing colloid transport in fractured media is imperative in order to develop appropriate bioremediation and/or bioaugmentation strategies for contaminated fractured aquifers, form management plans for groundwater resources to prevent pathogen contamination, and identify suitable radioactive waste disposal sites. However, research in this field is still in its infancy due to the complex heterogeneous nature of fractured media and the resulting difficulty in characterizing this media. The goal of this research is to investigate the effects of aperture field variability, flow rate and ionic strength on colloid transport processes in well characterized single fractures. A combination of laboratory-scale experiments, numerical simulations, and imaging techniques were employed to achieve this goal. Transparent replicas were cast from natural rock fractures, and a light transmission technique was employed to measure their aperture fields directly. The surface properties of the synthetic fractures were characterized by measuring the zeta-potential under different ionic strengths. A 33 (3 increased to the power of 3) factorial experiment was implemented to investigate the influence of aperture field variability, flow rate, and ionic strength on different colloid transport processes in the laboratory-scale fractures, specifically dispersion and attachment/detachment. A fluorescent stain technique was employed to photograph the colloid transport processes, and an analytical solution to the one-dimensional transport equation was fit to the colloid breakthrough curves to calculate the average transport velocity, dispersion coefficient, and attachment/detachment coefficient. The Reynolds equation was solved to obtain the flow field in the measured aperture fields, and the random walk particle tracking technique was employed to model the colloid transport experiments. The images clearly show the development of preferential pathways for colloid transport in the different aperture fields and under different flow conditions. Additionally, a correlation between colloid deposition and fracture wall topography was identified. This presentation will demonstrate (1) differential transport between colloid and solute in single fractures, and the relationship between differential transport and aperture field statistics; (2) the relationship between the colloid dispersion coefficient and aperture field statistics; and (3) the relationship between attachment/detachment, aperture field statistics, fracture wall topography, flow rate, and ionic strength. In addition, this presentation will provide insight into the application of the random walk particle tracking technique for modeling colloid transport in variable-aperture fractures.

Assessing the prediction accuracy of a cure model for censored survival data with long-term survivors: Application to breast cancer data.

PubMed

Asano, Junichi; Hirakawa, Akihiro

2017-01-01

The Cox proportional hazards cure model is a survival model incorporating a cure rate with the assumption that the population contains both uncured and cured individuals. It contains a logistic regression for the cure rate, and a Cox regression to estimate the hazard for uncured patients. A single predictive model for both the cure and hazard can be developed by using a cure model that simultaneously predicts the cure rate and hazards for uncured patients; however, model selection is a challenge because of the lack of a measure for quantifying the predictive accuracy of a cure model. Recently, we developed an area under the receiver operating characteristic curve (AUC) for determining the cure rate in a cure model (Asano et al., 2014), but the hazards measure for uncured patients was not resolved. In this article, we propose novel C-statistics that are weighted by the patients' cure status (i.e., cured, uncured, or censored cases) for the cure model. The operating characteristics of the proposed C-statistics and their confidence interval were examined by simulation analyses. We also illustrate methods for predictive model selection and for further interpretation of variables using the proposed AUCs and C-statistics via application to breast cancer data.

Impact of Sample Size and Variability on the Power and Type I Error Rates of Equivalence Tests: A Simulation Study

ERIC Educational Resources Information Center

Rusticus, Shayna A.; Lovato, Chris Y.

2014-01-01

The question of equivalence between two or more groups is frequently of interest to many applied researchers. Equivalence testing is a statistical method designed to provide evidence that groups are comparable by demonstrating that the mean differences found between groups are small enough that they are considered practically unimportant. Few…

Lost in Translation: Piloting a Novel Framework to Assess the Challenges in Translating Scientific Uncertainty From Empirical Findings to WHO Policy Statements

PubMed Central

Benmarhnia, Tarik; Huang, Jonathan Y.; Jones, Catherine M.

2017-01-01

Background: Calls for evidence-informed public health policy, with implicit promises of greater program effectiveness, have intensified recently. The methods to produce such policies are not self-evident, requiring a conciliation of values and norms between policy-makers and evidence producers. In particular, the translation of uncertainty from empirical research findings, particularly issues of statistical variability and generalizability, is a persistent challenge because of the incremental nature of research and the iterative cycle of advancing knowledge and implementation. This paper aims to assess how the concept of uncertainty is considered and acknowledged in World Health Organization (WHO) policy recommendations and guidelines. Methods: We selected four WHO policy statements published between 2008-2013 regarding maternal and child nutrient supplementation, infant feeding, heat action plans, and malaria control to represent topics with a spectrum of available evidence bases. Each of these four statements was analyzed using a novel framework to assess the treatment of statistical variability and generalizability. Results: WHO currently provides substantial guidance on addressing statistical variability through GRADE (Grading of Recommendations Assessment, Development, and Evaluation) ratings for precision and consistency in their guideline documents. Accordingly, our analysis showed that policy-informing questions were addressed by systematic reviews and representations of statistical variability (eg, with numeric confidence intervals). In contrast, the presentation of contextual or "background" evidence regarding etiology or disease burden showed little consideration for this variability. Moreover, generalizability or "indirectness" was uniformly neglected, with little explicit consideration of study settings or subgroups. Conclusion: In this paper, we found that non-uniform treatment of statistical variability and generalizability factors that may contribute to uncertainty regarding recommendations were neglected, including the state of evidence informing background questions (prevalence, mechanisms, or burden or distributions of health problems) and little assessment of generalizability, alternate interventions, and additional outcomes not captured by systematic review. These other factors often form a basis for providing policy recommendations, particularly in the absence of a strong evidence base for intervention effects. Consequently, they should also be subject to stringent and systematic evaluation criteria. We suggest that more effort is needed to systematically acknowledge (1) when evidence is missing, conflicting, or equivocal, (2) what normative considerations were also employed, and (3) how additional evidence may be accrued. PMID:29179291

Exploring the use of mothers' own milk as oral care for mechanically ventilated very low-birth-weight preterm infants.

PubMed

Thibeau, Shelley; Boudreaux, Cynthia

2013-06-01

The purpose of this study was to explore the use of mothers' own milk (colostrums, transitional milk, and mature milk) as oral care in the ventilator-associated pneumonia (VAP)-prevention bundle of mechanically ventilated preterm infants weighing 1500 g or less. Mechanically ventilated preterm infants weighing 1500 g or less admitted to a regional level III NICU in the Gulf South between January 1, 2006, and December 31, 2009. Retrospective descriptive. Oral care with mothers' own milk was implemented as part of the VAP-prevention bundle in the neonatal intensive care unit in the fourth quarter of 2007. Using retrospective deidentified data retrieved from the electronic medical record, the primary and secondary outcome variables were collected among eligible infants (≤1500 g) admitted January 1, 2006, to December 31, 2007 (before implementation) and January 1, 2008, to December 31, 2009 (after implementation). Sample characteristics, including infant gestational age, birth weight, and gender, as well as maternal age, type of delivery, and incidence of maternal chorioamnionitis, were also collected. Data analysis included frequencies and distributions to summarize sample characteristics and variables of interest. Appropriate tests for differences were conducted on outcome variables between the before and after groups of the human milk oral care intervention. The feasibility outcome variable included nursing compliance with the oral care procedure. The safety outcome variable included record of any adverse events associated with the oral care procedure. The efficacy health outcomes included the rate of positive tracheal aspirates, positive blood cultures, the number of ventilator days, and length of stay. Infant age (26.1-26.6 weeks) and weight (840-863 g) were similar in the before (n = 70) and after (n = 68) sample subjects. There were no statistically significant differences in ventilator days, χ² (46, n = 115) = 46.22, P = .46, and length of stay, χ (75, n = 115) = 78.78, P = .36, between groups. Although the rate of positive tracheal aspirates and positive blood cultures reduced after implementation of oral care with mothers' own milk, these differences were not statistically significant (U(47) = 250, z = -7.1, P = .48; U(47) = 217.5, z = -1.44, P = .15). There were no statistically significant differences in the rates of positive tracheal aspirates and blood cultures after implementation of oral care with mothers' own milk. The findings of this study suggest that using mothers' own milk as part of the VAP-prevention bundle is a feasible and safe practice; however, further research is needed to determine the immunological benefits of this practice.

Asymmetry between Activation and Deactivation during a Transcriptional Pulse.

PubMed

Dunham, Lee S S; Momiji, Hiroshi; Harper, Claire V; Downton, Polly J; Hey, Kirsty; McNamara, Anne; Featherstone, Karen; Spiller, David G; Rand, David A; Finkenstädt, Bärbel; White, Michael R H; Davis, Julian R E

2017-12-27

Transcription in eukaryotic cells occurs in gene-specific bursts or pulses of activity. Recent studies identified a spectrum of transcriptionally active "on-states," interspersed with periods of inactivity, but these "off-states" and the process of transcriptional deactivation are poorly understood. To examine what occurs during deactivation, we investigate the dynamics of switching between variable rates. We measured live single-cell expression of luciferase reporters from human growth hormone or human prolactin promoters in a pituitary cell line. Subsequently, we applied a statistical variable-rate model of transcription, validated by single-molecule FISH, to estimate switching between transcriptional rates. Under the assumption that transcription can switch to any rate at any time, we found that transcriptional activation occurs predominantly as a single switch, whereas deactivation occurs with graded, stepwise decreases in transcription rate. Experimentally altering cAMP signalling with forskolin or chromatin remodelling with histone deacetylase inhibitor modifies the duration of defined transcriptional states. Our findings reveal transcriptional activation and deactivation as mechanistically independent, asymmetrical processes. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Factors Explaining Racial/Ethnic Disparities in Rates of Physician Recommendation for Colorectal Cancer Screening

PubMed Central

Pelletier, Valerie; Winter, Kelly; Albatineh, Ahmed N.

2013-01-01

Objectives. Physician recommendation plays a crucial role in receiving endoscopic screening for colorectal cancer (CRC). This study explored factors associated with racial/ethnic differences in rates of screening recommendation. Methods. Data on 5900 adults eligible for endoscopic screening were obtained from the National Health Interview Survey. Odds ratios of receiving an endoscopy recommendation were calculated for selected variables. Planned, sequenced logistic regressions were conducted to examine the extent to which socioeconomic and health care variables account for racial/ethnic disparities in recommendation rates. Results. Differential rates were observed for CRC screening and screening recommendations among racial/ethnic groups. Compared with Whites, Hispanics were 34% less likely (P < .01) and Blacks were 26% less likely (P < .05) to receive this recommendation. The main predictors that emerged in sequenced analysis were education for Hispanics and Blacks and income for Blacks. After accounting for the effects of usual source of care, insurance coverage, and education, the disparity reduced and became statistically insignificant. Conclusions. Socioeconomic status and access to health care may explain major racial/ethnic disparities in CRC screening recommendation rates. PMID:23678899

Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hero, Alfred O.; Rajaratnam, Bala

When can reliable inference be drawn in the ‘‘Big Data’’ context? This article presents a framework for answering this fundamental question in the context of correlation mining, with implications for general large-scale inference. In large-scale data applications like genomics, connectomics, and eco-informatics, the data set is often variable rich but sample starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than the number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for ‘‘Big Data.’’ Sample complexity, however, hasmore » received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address this gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where the variable dimension is fixed and the sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; and 3) the purely high-dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa-scale data dimension. We illustrate this high-dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables that are of interest. Correlation mining arises in numerous applications and subsumes the regression context as a special case. We demonstrate various regimes of correlation mining based on the unifying perspective of high-dimensional learning rates and sample complexity for different structured covariance models and different inference tasks.« less

Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining

PubMed Central

Hero, Alfred O.; Rajaratnam, Bala

2015-01-01

When can reliable inference be drawn in fue “Big Data” context? This paper presents a framework for answering this fundamental question in the context of correlation mining, wifu implications for general large scale inference. In large scale data applications like genomics, connectomics, and eco-informatics fue dataset is often variable-rich but sample-starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than fue number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for “Big Data”. Sample complexity however has received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address fuis gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where fue variable dimension is fixed and fue sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; 3) the purely high dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa cale data dimension. We illustrate this high dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables fua t are of interest. Correlation mining arises in numerous applications and subsumes the regression context as a special case. we demonstrate various regimes of correlation mining based on the unifying perspective of high dimensional learning rates and sample complexity for different structured covariance models and different inference tasks. PMID:27087700

Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining

DOE PAGES

Hero, Alfred O.; Rajaratnam, Bala

2015-12-09

When can reliable inference be drawn in the ‘‘Big Data’’ context? This article presents a framework for answering this fundamental question in the context of correlation mining, with implications for general large-scale inference. In large-scale data applications like genomics, connectomics, and eco-informatics, the data set is often variable rich but sample starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than the number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for ‘‘Big Data.’’ Sample complexity, however, hasmore » received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address this gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where the variable dimension is fixed and the sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; and 3) the purely high-dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa-scale data dimension. We illustrate this high-dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables that are of interest. Correlation mining arises in numerous applications and subsumes the regression context as a special case. We demonstrate various regimes of correlation mining based on the unifying perspective of high-dimensional learning rates and sample complexity for different structured covariance models and different inference tasks.« less

A Stochastic Fractional Dynamics Model of Space-time Variability of Rain

NASA Technical Reports Server (NTRS)

Kundu, Prasun K.; Travis, James E.

2013-01-01

Rainfall varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, that allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and times scales. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and in Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to the second moment statistics of radar data. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well without any further adjustment.

Ambient temperature effect on pulse rate variability as an alternative to heart rate variability in young adult.

PubMed

Shin, Hangsik

2016-12-01

Pulse rate variability (PRV) is a promising physiological and analytic technique used as a substitute for heart rate variability (HRV). PRV is measured by pulse wave from various devices including mobile and wearable devices but HRV is only measured by an electrocardiogram (ECG). The purpose of this study was to evaluate PRV and HRV at various ambient temperatures and elaborate on the interchangeability of PRV and HRV. Twenty-eight healthy young subjects were enrolled in the experiment. We prepared temperature-controlled rooms and recorded the ECG and photoplethysmography (PPG) under temperature-controlled, constant humidity conditions. The rooms were kept at 17, 25, and 38 °C as low, moderate, and high ambient temperature environments, respectively. HRV and PRV were derived from the synchronized ECG and PPG measures and they were studied in time and frequency domain analysis for PRV/HRV ratio and pulse transit time (PTT). Similarity and differences between HRV and PRV were determined by a statistical analysis. PRV/HRV ratio analysis revealed that there was a significant difference between HRV and PRV for a given ambient temperature; this was with short-term variability measures such as SDNN SDSD or RMSSD, and HF-based variables including HF, LF/HF and normalized HF. In our analysis the absolute value of PTT was not significantly influenced by temperature. Standard deviation of PTT, however, showed significant difference not only between low and moderate temperatures but also between low and high temperatures. Our results suggest that ambient temperature induces a significant difference in PRV compared to HRV and that the difference becomes greater at a higher ambient temperature.

Computerized analysis of fetal heart rate variability signal during the stages of labor.

PubMed

Annunziata, Maria Laura; Tagliaferri, Salvatore; Esposito, Francesca Giovanna; Giuliano, Natascia; Mereghini, Flavia; Di Lieto, Andrea; Campanile, Marta

2016-03-01

To analyze computerized cardiotocographic (cCTG) parameters (baseline fetal heart rate, baseline FHR; short term variability, STV; approximate entropy, ApEn; low frequency, LF; movement frequency, MF; high frequency, HF) in physiological pregnancy in order to correlate them with the stages of labor. This could provide more information for understanding the mechanisms of nervous system control of FHR during labor progression. A total of 534 pregnant women were monitored on cCTG from the 37th week before the onset of spontaneous labor and during the first and the second stage of labor. Statistical analysis was performed using Kruskal-Wallis test and Wilcoxon rank-sum test with the Bonferroni adjusted α (< 0.05). Statistically significant differences were seen between baseline FHR, MF and HF (P < 0.001), in which the first two were reduced and the third was increased when compared between pre-labor, and the first and second stages of labor. Differences between some of the stages were found for ApEn, LF and for LF/(HF + MF), where the first and the third were reduced and the second was increased. cCTG modifications during labor may reflect the physiologic increased activation of the autonomous nervous system. Using computerized fetal heart rate analysis during labor it may be possible to obtain more information from the fetal cardiac signal, in comparison with the traditional tracing. © 2016 Japan Society of Obstetrics and Gynecology.

A Modified Mechanical Threshold Stress Constitutive Model for Austenitic Stainless Steels

NASA Astrophysics Data System (ADS)

Prasad, K. Sajun; Gupta, Amit Kumar; Singh, Yashjeet; Singh, Swadesh Kumar

2016-12-01

This paper presents a modified mechanical threshold stress (m-MTS) constitutive model. The m-MTS model incorporates variable athermal and dynamic strain aging (DSA) Components to accurately predict the flow stress behavior of austenitic stainless steels (ASS)-316 and 304. Under strain rate variations between 0.01-0.0001 s-1, uniaxial tensile tests were conducted at temperatures ranging from 50-650 °C to evaluate the material constants of constitutive models. The test results revealed the high dependence of flow stress on strain, strain rate and temperature. In addition, it was observed that DSA occurred at elevated temperatures and very low strain rates, causing an increase in flow stress. While the original MTS model is capable of predicting the flow stress behavior for ASS, statistical parameters point out the inefficiency of the model when compared to other models such as Johnson Cook model, modified Zerilli-Armstrong (m-ZA) model, and modified Arrhenius-type equations (m-Arr). Therefore, in order to accurately model both the DSA and non-DSA regimes, the original MTS model was modified by incorporating variable athermal and DSA components. The suitability of the m-MTS model was assessed by comparing the statistical parameters. It was observed that the m-MTS model was highly accurate for the DSA regime when compared to the existing models. However, models like m-ZA and m-Arr showed better results for the non-DSA regime.

A statistical method for estimating rates of soil development and ages of geologic deposits: A design for soil-chronosequence studies

USGS Publications Warehouse

Switzer, P.; Harden, J.W.; Mark, R.K.

1988-01-01

A statistical method for estimating rates of soil development in a given region based on calibration from a series of dated soils is used to estimate ages of soils in the same region that are not dated directly. The method is designed specifically to account for sampling procedures and uncertainties that are inherent in soil studies. Soil variation and measurement error, uncertainties in calibration dates and their relation to the age of the soil, and the limited number of dated soils are all considered. Maximum likelihood (ML) is employed to estimate a parametric linear calibration curve, relating soil development to time or age on suitably transformed scales. Soil variation on a geomorphic surface of a certain age is characterized by replicate sampling of soils on each surface; such variation is assumed to have a Gaussian distribution. The age of a geomorphic surface is described by older and younger bounds. This technique allows age uncertainty to be characterized by either a Gaussian distribution or by a triangular distribution using minimum, best-estimate, and maximum ages. The calibration curve is taken to be linear after suitable (in certain cases logarithmic) transformations, if required, of the soil parameter and age variables. Soil variability, measurement error, and departures from linearity are described in a combined fashion using Gaussian distributions with variances particular to each sampled geomorphic surface and the number of sample replicates. Uncertainty in age of a geomorphic surface used for calibration is described using three parameters by one of two methods. In the first method, upper and lower ages are specified together with a coverage probability; this specification is converted to a Gaussian distribution with the appropriate mean and variance. In the second method, "absolute" older and younger ages are specified together with a most probable age; this specification is converted to an asymmetric triangular distribution with mode at the most probable age. The statistical variability of the ML-estimated calibration curve is assessed by a Monte Carlo method in which simulated data sets repeatedly are drawn from the distributional specification; calibration parameters are reestimated for each such simulation in order to assess their statistical variability. Several examples are used for illustration. The age of undated soils in a related setting may be estimated from the soil data using the fitted calibration curve. A second simulation to assess age estimate variability is described and applied to the examples. ?? 1988 International Association for Mathematical Geology.

Survival Model for Foot and Leg High Rate Axial Impact Injury Data.

PubMed

Bailey, Ann M; McMurry, Timothy L; Poplin, Gerald S; Salzar, Robert S; Crandall, Jeff R

2015-01-01

Understanding how lower extremity injuries from automotive intrusion and underbody blast (UBB) differ is of key importance when determining whether automotive injury criteria can be applied to blast rate scenarios. This article provides a review of existing injury risk analyses and outlines an approach to improve injury prediction for an expanded range of loading rates. This analysis will address issues with existing injury risk functions including inaccuracies due to inertial and potential viscous resistance at higher loading rates. This survival analysis attempts to minimize these errors by considering injury location statistics and a predictor variable selection process dependent upon failure mechanisms of bone. Distribution of foot/ankle/leg injuries induced by axial impact loading at rates characteristic of UBB as well as automotive intrusion was studied and calcaneus injuries were found to be the most common injury; thus, footplate force was chosen as the main predictor variable because of its proximity to injury location to prevent inaccuracies associated with inertial differences due to loading rate. A survival analysis was then performed with age, sex, dorsiflexion angle, and mass as covariates. This statistical analysis uses data from previous axial postmortem human surrogate (PMHS) component leg tests to provide perspectives on how proximal boundary conditions and loading rate affect injury probability in the foot/ankle/leg (n = 82). Tibia force-at-fracture proved to be up to 20% inaccurate in previous analyses because of viscous resistance and inertial effects within the data set used, suggesting that previous injury criteria are accurate only for specific rates of loading and boundary conditions. The statistical model presented in this article predicts 50% probability of injury for a plantar force of 10.2 kN for a 50th percentile male with a neutral ankle position. Force rate was found to be an insignificant covariate because of the limited range of loading rate differences within the data set; however, compensation for inertial effects caused by measuring the force-at-fracture in a location closer to expected injury location improved the model's predictive capabilities for the entire data set. This study provides better injury prediction capabilities for both automotive and blast rates because of reduced sensitivity to inertial effects and tibia-fibula load sharing. Further, a framework is provided for future injury criteria generation for high rate loading scenarios. This analysis also suggests key improvements to be made to existing anthropomorphic test device (ATD) lower extremities to provide accurate injury prediction for high rate applications such as UBB.

[Association between social deprivation and causes of mortality among elderly residents in the city of Recife, Pernambuco State, Brazil].

PubMed

Silva, Vanessa de Lima; Leal, Márcia Carréra Campos; Marino, Jacira Guiro; Marques, Ana Paula de Oliveira

2008-05-01

This paper aims to analyze mortality among elderly residents in the city of Recife, Pernambuco State, Brazil, and its association with social deprivation (hardship) in the year 2000. An ecological study was performed, and 94 neighborhoods and 5 social strata were analyzed. The independent variable consisted of a composite social deprivation indicator, obtained for each neighborhood and calculated through a scoring technique based on census variables: water supply, sewage, illiteracy, and head-of-household's years of schooling and income. The dependent variables were: mortality rate in individuals > 60 years of age and cause-specific mortality rates. The association was calculated by means of the Pearson correlation coefficient, linear regression, and mortality odds between social deprivation strata formed by grouping of neighborhoods according to the indicator's quintiles. The data show a statistically significant positive correlation between social deprivation and mortality in the elderly from pneumonia, protein-energy malnutrition, tuberculosis, diarrhea/gastroenteritis, and traffic accidents, and a negative correlation with deaths from bronchopulmonary and breast cancers.

The Chandra Source Catalog: Source Variability

NASA Astrophysics Data System (ADS)

Nowak, Michael; Rots, A. H.; McCollough, M. L.; Primini, F. A.; Glotfelty, K. J.; Bonaventura, N. R.; Chen, J. C.; Davis, J. E.; Doe, S. M.; Evans, J. D.; Fabbiano, G.; Galle, E.; Gibbs, D. G.; Grier, J. D.; Hain, R.; Hall, D. M.; Harbo, P. N.; He, X.; Houck, J. C.; Karovska, M.; Lauer, J.; McDowell, J. C.; Miller, J. B.; Mitschang, A. W.; Morgan, D. L.; Nichols, J. S.; Plummer, D. A.; Refsdal, B. L.; Siemiginowska, A. L.; Sundheim, B. A.; Tibbetts, M. S.; Van Stone, D. W.; Winkelman, S. L.; Zografou, P.

2009-01-01

The Chandra Source Catalog (CSC) contains fields of view that have been studied with individual, uninterrupted observations that span integration times ranging from 1 ksec to 160 ksec, and a large number of which have received (multiple) repeat observations days to years later. The CSC thus offers an unprecedented look at the variability of the X-ray sky over a broad range of time scales, and across a wide diversity of variable X-ray sources: stars in the local galactic neighborhood, galactic and extragalactic X-ray binaries, Active Galactic Nuclei, etc. Here we describe the methods used to identify and quantify source variability within a single observation, and the methods used to assess the variability of a source when detected in multiple, individual observations. Three tests are used to detect source variability within a single observation: the Kolmogorov-Smirnov test and its variant, the Kuiper test, and a Bayesian approach originally suggested by Gregory and Loredo. The latter test not only provides an indicator of variability, but is also used to create a best estimate of the variable lightcurve shape. We assess the performance of these tests via simulation of statistically stationary, variable processes with arbitrary input power spectral densities (here we concentrate on results of red noise simulations) at variety of mean count rates and fractional root mean square variabilities relevant to CSC sources. We also assess the false positive rate via simulations of constant sources whose sole source of fluctuation is Poisson noise. We compare these simulations to a preliminary assessment of the variability found in real CSC sources, and estimate the variability sensitivities of the CSC.

The Chandra Source Catalog: Source Variability

NASA Astrophysics Data System (ADS)

Nowak, Michael; Rots, A. H.; McCollough, M. L.; Primini, F. A.; Glotfelty, K. J.; Bonaventura, N. R.; Chen, J. C.; Davis, J. E.; Doe, S. M.; Evans, J. D.; Evans, I.; Fabbiano, G.; Galle, E. C.; Gibbs, D. G., II; Grier, J. D.; Hain, R.; Hall, D. M.; Harbo, P. N.; He, X.; Houck, J. C.; Karovska, M.; Lauer, J.; McDowell, J. C.; Miller, J. B.; Mitschang, A. W.; Morgan, D. L.; Nichols, J. S.; Plummer, D. A.; Refsdal, B. L.; Siemiginowska, A. L.; Sundheim, B. A.; Tibbetts, M. S.; van Stone, D. W.; Winkelman, S. L.; Zografou, P.

2009-09-01

The Chandra Source Catalog (CSC) contains fields of view that have been studied with individual, uninterrupted observations that span integration times ranging from 1 ksec to 160 ksec, and a large number of which have received (multiple) repeat observations days to years later. The CSC thus offers an unprecedented look at the variability of the X-ray sky over a broad range of time scales, and across a wide diversity of variable X-ray sources: stars in the local galactic neighborhood, galactic and extragalactic X-ray binaries, Active Galactic Nuclei, etc. Here we describe the methods used to identify and quantify source variability within a single observation, and the methods used to assess the variability of a source when detected in multiple, individual observations. Three tests are used to detect source variability within a single observation: the Kolmogorov-Smirnov test and its variant, the Kuiper test, and a Bayesian approach originally suggested by Gregory and Loredo. The latter test not only provides an indicator of variability, but is also used to create a best estimate of the variable lightcurve shape. We assess the performance of these tests via simulation of statistically stationary, variable processes with arbitrary input power spectral densities (here we concentrate on results of red noise simulations) at variety of mean count rates and fractional root mean square variabilities relevant to CSC sources. We also assess the false positive rate via simulations of constant sources whose sole source of fluctuation is Poisson noise. We compare these simulations to an assessment of the variability found in real CSC sources, and estimate the variability sensitivities of the CSC.

Effects of price and availability on abortion demand.

PubMed

Gohmann, S F; Ohsfeldt, R L

1993-10-01

This study explained the variation in US state abortion demand due to the price of services, the net of insurance cost of birth services, the ability to pay, contraceptive use, individual attitudes regarding abortion, and government policy affecting cost of benefits of terminating an unintended pregnancy or of carrying to birth. The empirical model uses pooled data from 48 states for 1982, 1984, 1985, and 1987. Prices are deflated to 1977 dollars. Another two-staged least squares model is based on cross-sectional state level data for 1985. The dependent variable is the log of abortion per 1000 pregnancies. Other variables pertain to income, education, labor force, family planning, tax, aid to families with dependent children, religion, and abortion-related measures. The results of the cross-sectional analysis are consistent with Medoff's and Garbacz's findings. The estimated coefficient of per capita income is positive with a point elasticity ranging from 0.62 to 1.0. The model with the most complete specifications has an abortion price elasticity range from -0.75 to -1.3 and is statistically significant when religion measures are excluded. The Hausman test shows the pro-choice variable significantly correlated with the error term. The net price of birth services is not statistically significant. Catholic religion and no religion are only significant when the abortion provider variable is excluded. The suggestion is that the effect of Catholicism is ambiguous. In the pooled analysis, the fixed effects model is used to control for abortion attitudes and other unobserved factors. Abortion demand includes abortion per 1000 pregnancies, the ratio of abortions to pregnancies, and the logarithm of abortions per 1000 pregnancies. Higher income is associated with a higher abortion rate and elasticities of 0.76 and 0.35 and is associated with a higher pregnancy rate. The abortion ratio is found to be elastic with respect to price, and price elasticities are sensitive to choice of state abortion attitude measures. The availability of family planning services reduces the rate of pregnancy as well as the abortion rate and ratio.

Can Statistical Machine Learning Algorithms Help for Classification of Obstructive Sleep Apnea Severity to Optimal Utilization of Polysomnography Resources?

PubMed

Bozkurt, Selen; Bostanci, Asli; Turhan, Murat

2017-08-11

The goal of this study is to evaluate the results of machine learning methods for the classification of OSA severity of patients with suspected sleep disorder breathing as normal, mild, moderate and severe based on non-polysomnographic variables: 1) clinical data, 2) symptoms and 3) physical examination. In order to produce classification models for OSA severity, five different machine learning methods (Bayesian network, Decision Tree, Random Forest, Neural Networks and Logistic Regression) were trained while relevant variables and their relationships were derived empirically from observed data. Each model was trained and evaluated using 10-fold cross-validation and to evaluate classification performances of all methods, true positive rate (TPR), false positive rate (FPR), Positive Predictive Value (PPV), F measure and Area Under Receiver Operating Characteristics curve (ROC-AUC) were used. Results of 10-fold cross validated tests with different variable settings promisingly indicated that the OSA severity of suspected OSA patients can be classified, using non-polysomnographic features, with 0.71 true positive rate as the highest and, 0.15 false positive rate as the lowest, respectively. Moreover, the test results of different variables settings revealed that the accuracy of the classification models was significantly improved when physical examination variables were added to the model. Study results showed that machine learning methods can be used to estimate the probabilities of no, mild, moderate, and severe obstructive sleep apnea and such approaches may improve accurate initial OSA screening and help referring only the suspected moderate or severe OSA patients to sleep laboratories for the expensive tests.

Ethnic analogies and differences in fetal heart rate variability signal: A retrospective study.

PubMed

Tagliaferri, Salvatore; Esposito, Francesca Giovanna; Fagioli, Rosa; Di Cresce, Marco; Sacchi, Lucia; Signorini, Maria Gabriella; Campanile, Marta; Martinelli, Pasquale; Magenes, Giovanni

2017-02-01

We aimed to analyze computerized cardiotocographic (cCTG) parameters (including fetal heart rate baseline, short-term variability, Delta, long-term irregularity [LTI], interval index [II], low frequency [LF], movement frequency [MF], high frequency [HF], and approximate entropy [ApEn]) in physiological term pregnancies in order to correlate them with ethnic differences. The clinical meaning of numerical parameters may explain physiological or paraphysiological phenomena that occur in fetuses of different ethnic origins. A total of 696 pregnant women, including 384 from Europe, 246 from sub-Saharan Africa, 45 from South-East Asia, and 21 from South America, were monitored from the 37th to the 41st week of gestation. Statistical analysis was performed with the analysis of variance test, Pearson correlation test and receiver-operator curves (P < 0.05). Our results showed statistically significant differences (P < 0.05) between white and black women for Delta, LTI, LF, MF, HF, and ApEn; between white and Asian women for Delta, LTI, MF, and the LF/(HF + MF) ratio; and between white and Latina women for Delta, LTI, and ApEn. In particular, Delta and LTI performed better in the white group than in the black, Asian, and Latina groups. Instead, LF, MF, HF, and ApEn performed better in the black than in the white group. Our results confirmed the integrity and normal functionality of both central and autonomic nervous system components for all fetuses investigated. Therefore, CTG monitoring should include both linear and nonlinear components of fetal heart rate variability in order to avoid misinterpretations of the CTG trace among ethnic groups. © 2016 Japan Society of Obstetrics and Gynecology.

Resting Heart Rate Variability Among Professional Baseball Starting Pitchers.

PubMed

Cornell, David J; Paxson, Jeffrey L; Caplinger, Roger A; Seligman, Joshua R; Davis, Nicholas A; Ebersole, Kyle T

2017-03-01

Cornell, DJ, Paxson, JL, Caplinger, RA, Seligman, JR, Davis, NA, and Ebersole, KT. Resting heart rate variability among professional baseball starting pitchers. J Strength Cond Res 31(3): 575-581, 2017-The purpose of this study was to examine the changes in resting heart rate variability (HRV) across a 5-day pitching rotation schedule among professional baseball starting pitchers. The HRV data were collected daily among 8 Single-A level professional baseball starting pitchers (mean ± SD, age = 21.9 ± 1.3 years; height = 185.4 ± 3.6 cm; weight = 85.2 ± 7.5 kg) throughout the entire baseball season with the participant quietly lying supine for 10 minutes. The HRV was quantified by calculating the natural log of the square root of the mean sum of the squared differences (lnRMSSD) during the middle 5 minutes of each R-R series data file. A split-plot repeated-measures analysis of variance was used to examine the influence of pitching rotation day on resting lnRMSSD. A statistically significant main effect of rotation day was identified (F4,706 = 3.139, p = 0.029). Follow-up pairwise analyses indicated that resting lnRMSSD on day 2 was significantly (p ≤ 0.05) lower than all other rotation days. In addition, a statistically significant main effect of pitcher was also identified (F7,706 = 83.388, p < 0.001). These results suggest that professional baseball starting pitchers display altered autonomic nervous system function 1 day after completing a normally scheduled start, as day 2 resting HRV was significantly lower than all other rotation days. In addition, the season average resting lnRMSSD varied among participants, implying that single-subject analysis of resting measures of HRV may be more appropriate when monitoring cumulative workload among this cohort population of athletes.

Burst of ULF Electric Field Recorded by DEMETER Possibly Related to the Series of Earthquakes Occurred during the Tsunami Over the Indian Region (P19)

NASA Astrophysics Data System (ADS)

Gwal, A. K.; Shrivastava, A.

2006-11-01

ak_gwal@yahoo.co.in The scientists have found that the accumulation of tectonic energy is localized in certain places and is not universal. Taking into account this hypothesis the authors have studied the sequence of occurrence rate of the earthquakes (M≥5) in the South-East Asian region, as the chronological data related to the occurrence of earthquakes collected in that region for last five years i.e. from 2001 to 2005 have revealed that the disastrous tsunami events which took place on 26th December, 2004 as an effect of Sumatra earthquake( M=9) have increased the occurrence of earthquake frequency for a longer period (which might be due to adjustment of tectonic plates). Observing these facts i.e. sudden enhancement in occurrence rate of earthquakes, the authors have availed this opportunity to further explore the concept of seismoelectromagnetic-ionospheric phenomena, which still needs a lot of statistical evidences, comprising tremendous amount of data to establish it. In this paper the authors have tried to analyze the chain of observations made and data collected and stored month wise w.e.f. 26th December, 2004 to 31st March, 2005 in the region, using DEMETER satellite. Further, efforts have also been made to provide the statistical analysis of the ionospheric variability caused due to detected electromagnetic burst in ULF frequency ranges in the context of natural variability in order to distinguish the variability introduced by other sources. In brief, it could be concluded that there is possibility of getting the electromagnetic precursors in the ionosphere at different frequency ranges due to excess release of tectonic energy as a result of occurrence rate of the earthquakes in the region.

Correlation spectrometer for filtering of (quasi) elastic neutron scattering with variable resolution

NASA Astrophysics Data System (ADS)

Magazù, Salvatore; Mezei, Ferenc; Migliardo, Federica

2018-05-01

In a variety of applications of inelastic neutron scattering spectroscopy the goal is to single out the elastic scattering contribution from the total scattered spectrum as a function of momentum transfer and sample environment parameters. The elastic part of the spectrum is defined in such a case by the energy resolution of the spectrometer. Variable elastic energy resolution offers a way to distinguish between elastic and quasi-elastic intensities. Correlation spectroscopy lends itself as an efficient, high intensity approach for accomplishing this both at continuous and pulsed neutron sources. On the one hand, in beam modulation methods the Liouville theorem coupling between intensity and resolution is relaxed and time-of-flight velocity analysis of the neutron velocity distribution can be performed with 50 % duty factor exposure for all available resolutions. On the other hand, the (quasi)elastic part of the spectrum generally contains the major part of the integrated intensity at a given detector, and thus correlation spectroscopy can be applied with most favorable signal to statistical noise ratio. The novel spectrometer CORELLI at SNS is an example for this type of application of the correlation technique at a pulsed source. On a continuous neutron source a statistical chopper can be used for quasi-random time dependent beam modulation and the total time-of-flight of the neutron from the statistical chopper to detection is determined by the analysis of the correlation between the temporal fluctuation of the neutron detection rate and the statistical chopper beam modulation pattern. The correlation analysis can either be used for the determination of the incoming neutron velocity or for the scattered neutron velocity, depending of the position of the statistical chopper along the neutron trajectory. These two options are considered together with an evaluation of spectrometer performance compared to conventional spectroscopy, in particular for variable resolution elastic neutron scattering (RENS) studies of relaxation processes and the evolution of mean square displacements. A particular focus of our analysis is the unique feature of correlation spectroscopy of delivering high and resolution independent beam intensity, thus the same statistical chopper scan contains both high intensity and high resolution information at the same time, and can be evaluated both ways. This flexibility for variable resolution data handling represents an additional asset for correlation spectroscopy in variable resolution work. Changing the beam width for the same statistical chopper allows us to additionally trade resolution for intensity in two different experimental runs, similarly for conventional single slit chopper spectroscopy. The combination of these two approaches is a capability of particular value in neutron spectroscopy studies requiring variable energy resolution, such as the systematic study of quasi-elastic scattering and mean square displacement. Furthermore the statistical chopper approach is particularly advantageous for studying samples with low scattering intensity in the presence of a high, sample independent background.

Global Diffusion Pattern and Hot SPOT Analysis of Vaccine-Preventable Diseases

NASA Astrophysics Data System (ADS)

Jiang, Y.; Fan, F.; Zanoni, I. Holly; Li, Y.

2017-10-01

Spatial characteristics reveal the concentration of vaccine-preventable disease in Africa and the Near East and that disease dispersion is variable depending on disease. The exception is whooping cough, which has a highly variable center of concentration from year to year. Measles exhibited the only statistically significant spatial autocorrelation among all the diseases under investigation. Hottest spots of measles are in Africa and coldest spots are in United States, warm spots are in Near East and cool spots are in Western Europe. Finally, cases of measles could not be explained by the independent variables, including Gini index, health expenditure, or rate of immunization. Since the literature confirms that each of the selected variables is considered determinants of disease dissemination, it is anticipated that the global dataset of disease cases was influenced by reporting bias.

[Detection of underlying causes of death among the deceased of Yusho patients by linkage to the national vital statistics data].

PubMed

Kaneko, S; Yoshimura, T; Ikeda, M; Nishisaka, K

2001-05-01

As of January 31, 1996, 292 deaths among registered patients of Yusho were identified by three follow-up studies conducted in 1986, 1990, and 1996. In this study, we attempted to identify underlying causes of death by linkage of the registered data to the National Vital Statistics Data provided by the Management and Coordination Agency of Japan, which included 15 million deaths between 1978 and 1996. The two datasets were linked by matching for six variables; birth year/month/day, death year/month, and sex, along with a variable of death day or death place, or both. The matched cases were 203 among 235 deaths between 1978 and 1996 (matching rate was 86%). Among the 203 deaths, 58 underlying causes of death were newly identified, 146 causes of death were already grasped by the follow-up studies, and 31 deaths did not have matching pair in the National Vital Statistics data. Among the 146 deaths, 110 causes of death were concordant with each other, however, 35 causes of death were completely discord. The reason of the discordance and the unmatched deaths might be due to difference in information of the matching variables in the two datasets. In order to conduct an efficient follow-up study of Yusho patients, identification of underlying causes of death by linkage to the National Vital Statistics Date is evitable. For that, we need to substitute basic information in the Yusho database to those compatible to the National civil registration system.

A self-consistency approach to improve microwave rainfall rate estimation from space

NASA Technical Reports Server (NTRS)

Kummerow, Christian; Mack, Robert A.; Hakkarinen, Ida M.

1989-01-01

A multichannel statistical approach is used to retrieve rainfall rates from the brightness temperature T(B) observed by passive microwave radiometers flown on a high-altitude NASA aircraft. T(B) statistics are based upon data generated by a cloud radiative model. This model simulates variabilities in the underlying geophysical parameters of interest, and computes their associated T(B) in each of the available channels. By further imposing the requirement that the observed T(B) agree with the T(B) values corresponding to the retrieved parameters through the cloud radiative transfer model, the results can be made to agree quite well with coincident radar-derived rainfall rates. Some information regarding the cloud vertical structure is also obtained by such an added requirement. The applicability of this technique to satellite retrievals is also investigated. Data which might be observed by satellite-borne radiometers, including the effects of nonuniformly filled footprints, are simulated by the cloud radiative model for this purpose.

Prediction of pilot reserve attention capacity during air-to-air target tracking

NASA Technical Reports Server (NTRS)

Onstott, E. D.; Faulkner, W. H.

1977-01-01

Reserve attention capacity of a pilot was calculated using a pilot model that allocates exclusive model attention according to the ranking of task urgency functions whose variables are tracking error and error rate. The modeled task consisted of tracking a maneuvering target aircraft both vertically and horizontally, and when possible, performing a diverting side task which was simulated by the precise positioning of an electrical stylus and modeled as a task of constant urgency in the attention allocation algorithm. The urgency of the single loop vertical task is simply the magnitude of the vertical tracking error, while the multiloop horizontal task requires a nonlinear urgency measure of error and error rate terms. Comparison of model results with flight simulation data verified the computed model statistics of tracking error of both axes, lateral and longitudinal stick amplitude and rate, and side task episodes. Full data for the simulation tracking statistics as well as the explicit equations and structure of the urgency function multiaxis pilot model are presented.

Effects of different training amplitudes on heart rate and heart rate variability in young rowers.

PubMed

Vaz, Marcelo S; Picanço, Luan M; Del Vecchio, Fabrício B

2014-10-01

The aim of this study was to investigate the autonomic nervous system recovery and the psychological response as a result of 3 training amplitudes on heart rate (HR), heart rate variability (HRV), and rate of perceived exertion (RPE) in rowing. Eight young rowers (16.8 ± 1.4 years) performed, in a randomized fashion, 2 sessions of high-intensity interval training, with high and low amplitude and a continuous training (CT) session, with the same exercise duration (10 minutes) and mean intensity (60% of maximal stroke test). The data of HR, HRV, and RPE were collected 5 minutes before, immediately after each session, and 24 hours later. High amplitude promoted higher impact in maximum HR (p ≤ 0.05) and RPE (p < 0.001) when compared with CT. For the time domain HRV variable, there was a statistically significant difference between moments of rest (pretraining or post 24 hours) and posttraining in all training sessions. Originally, we conclude that training with higher load variation between effort and recovery impacts HRV, HR, and RPE with greater intensity, but the younger rowers were ready for new training sessions 24 hours after either training method. Coaches can use the polarized training method, observing the stimulus nature and time required for recovery, because it may be an adequate strategy for the development of rower's conditioning.

Human embryo culture media comparisons.

PubMed

Pool, Thomas B; Schoolfield, John; Han, David

2012-01-01

Every program of assisted reproduction strives to maximize pregnancy outcomes from in vitro fertilization and selecting an embryo culture medium, or medium pair, consistent with high success rates is key to this process. The common approach is to replace an existing medium with a new one of interest in the overall culture system and then perform enough cycles of IVF to see if a difference is noted both in laboratory measures of embryo quality and in pregnancy. This approach may allow a laboratory to select one medium over another but the outcomes are only relevant to that program, given that there are well over 200 other variables that may influence the results in an IVF cycle. A study design that will allow for a more global application of IVF results, ones due to culture medium composition as the single variable, is suggested. To perform a study of this design, the center must have a patient caseload appropriate to meet study entrance criteria, success rates high enough to reveal a difference if one exists and a strong program of quality assurance and control in both the laboratory and clinic. Sibling oocytes are randomized to two study arms and embryos are evaluated on day 3 for quality grades. Inter and intra-observer variability are evaluated by kappa statistics and statistical power and study size estimates are performed to bring discriminatory capability to the study. Finally, the complications associated with extending such a study to include blastocyst production on day 5 or 6 are enumerated.

CAN'T MISS--conquer any number task by making important statistics simple. Part 1. Types of variables, mean, median, variance, and standard deviation.

PubMed

Hansen, John P

2003-01-01

Healthcare quality improvement professionals need to understand and use inferential statistics to interpret sample data from their organizations. In quality improvement and healthcare research studies all the data from a population often are not available, so investigators take samples and make inferences about the population by using inferential statistics. This three-part series will give readers an understanding of the concepts of inferential statistics as well as the specific tools for calculating confidence intervals for samples of data. This article, Part 1, presents basic information about data including a classification system that describes the four major types of variables: continuous quantitative variable, discrete quantitative variable, ordinal categorical variable (including the binomial variable), and nominal categorical variable. A histogram is a graph that displays the frequency distribution for a continuous variable. The article also demonstrates how to calculate the mean, median, standard deviation, and variance for a continuous variable.

Cardiovascular reactivity patterns and pathways to hypertension: a multivariate cluster analysis.

PubMed

Brindle, R C; Ginty, A T; Jones, A; Phillips, A C; Roseboom, T J; Carroll, D; Painter, R C; de Rooij, S R

2016-12-01

Substantial evidence links exaggerated mental stress induced blood pressure reactivity to future hypertension, but the results for heart rate reactivity are less clear. For this reason multivariate cluster analysis was carried out to examine the relationship between heart rate and blood pressure reactivity patterns and hypertension in a large prospective cohort (age range 55-60 years). Four clusters emerged with statistically different systolic and diastolic blood pressure and heart rate reactivity patterns. Cluster 1 was characterised by a relatively exaggerated blood pressure and heart rate response while the blood pressure and heart rate responses of cluster 2 were relatively modest and in line with the sample mean. Cluster 3 was characterised by blunted cardiovascular stress reactivity across all variables and cluster 4, by an exaggerated blood pressure response and modest heart rate response. Membership to cluster 4 conferred an increased risk of hypertension at 5-year follow-up (hazard ratio=2.98 (95% CI: 1.50-5.90), P<0.01) that survived adjustment for a host of potential confounding variables. These results suggest that the cardiac reactivity plays a potentially important role in the link between blood pressure reactivity and hypertension and support the use of multivariate approaches to stress psychophysiology.

The association between the supply of primary care physicians and population health outcomes in Korea.

PubMed

Lee, Juhyun; Park, Sangmin; Choi, Kyunghyun; Kwon, Soon-Man

2010-10-01

Several studies reported that primary care improves health outcomes for populations. The objective of this study was to examine the relationship between the supply of primary care physicians and population health outcomes in Korea. Data were extracted from the 2007 report of the Health Insurance Review, the 2005 report from the Korean National Statistical Office, and the 2008 Korean Community Health Survey. The dependent variables were age-adjusted all-cause and disease-specific mortality rates, and independent variables were the supply of primary care physicians, the ratio of primary care physicians to specialists, the number of beds, socioeconomic factors (unemployment rate, local tax, education), population (population size, proportion of the elderly over age 65), and health behaviors (smoking, exercise, using seat belts rates). We used multivariate linear regression as well as ANOVA and t tests. A higher number of primary care physicians was associated with lower all-cause mortality, cancer mortality, and cardiovascular mortality. However, the ratio of primary care physicians to specialists was not related to all-cause mortality. In addition, the relationship between socioeconomic variables and mortality rates was similar in strength to the relationship between the supply of primary care physicians and mortality rates. Accident mortality, suicide mortality, infection mortality, and perinatal mortality were not related to the supply of primary care physicians. The supply of primary care physicians is associated with improved health outcomes, especially in chronic diseases and cancer. However, other variables such as the socioeconomic factors and population factors seem to have a more significant influence on these outcomes.

An Econometric Model of External Labor Supply to the Establishment Within a Confined Geographic Market.

ERIC Educational Resources Information Center

Hines, Robert James

The study conducted in the Buffalo, New York standard metropolitan statistical area, was undertaken to formulate and test a simple model of labor supply for a local labor market. The principal variables to be examined to determine the external supply function of labor to the establishment are variants of the rate of change of the entry wage and…

Using the Sampling Margin of Error to Assess the Interpretative Validity of Student Evaluations of Teaching

ERIC Educational Resources Information Center

James, David E.; Schraw, Gregory; Kuch, Fred

2015-01-01

We present an equation, derived from standard statistical theory, that can be used to estimate sampling margin of error for student evaluations of teaching (SETs). We use the equation to examine the effect of sample size, response rates and sample variability on the estimated sampling margin of error, and present results in four tables that allow…

Adaptation to climate change: changes in farmland use and stocking rate in the U.S.

USGS Publications Warehouse

Mu, Jianhong E.; McCarl, Bruce A.; Wein, Anne M.

2013-01-01

This paper examines possible adaptations to climate change in terms of pasture and crop land use and stocking rate in the United States (U.S.). Using Agricultural Census and climate data in a statistical model, we find that as temperature and precipitation increases agricultural commodity producers respond by reducing crop land and increasing pasture land. In addition, cattle stocking rate decreases as the summer Temperature-humidity Index (THI) increases and summer precipitation decreases. Using the statistical model with climate data from four General Circulation Models (GCMs), we project that land use shifts from cropping to grazing and the stocking rate declines, and these adaptations are more pronounced in the central and the southeast regions of the U.S. Controlling for other farm production variables, crop land decreases by 6 % and pasture land increases by 33 % from the baseline. Correspondingly, the associated economic impact due to adaptation is around -14 and 29 million dollars to crop producers and pasture producers by the end of this century, respectively. The national and regional results have implications for farm programs and subsidy policies.

Effect of fertility on secondary sex ratio and twinning rate in Sweden, 1749-1870.

PubMed

Fellman, Johan; Eriksson, Aldur W

2015-02-01

We analyzed the effect of total fertility rate (TFR) and crude birth rate (CBR) on the number of males per 100 females at birth, also called the secondary sex ratio (SR), and on the twinning rate (TWR). Earlier studies have noted regional variations in TWR and racial differences in the SR. Statistical analyses have shown that comparisons between SRs demand large data sets because random fluctuations in moderate data are marked. Consequently, reliable results presuppose national birth data. Here, we analyzed historical demographic data and their regional variations between counties in Sweden. We built spatial models for the TFR in 1860 and the CBR in 1751-1870, and as regressors we used geographical coordinates for the provincial capitals of the counties. For both variables, we obtained significant spatial variations, albeit of different patterns and power. The SR among the live-born in 1749-1869 and the TWR in 1751-1860 showed slight spatial variations. The influence of CBR and TFR on the SR and TWR was examined and statistical significant effects were found.

Waste generated in high-rise buildings construction: a quantification model based on statistical multiple regression.

PubMed

Parisi Kern, Andrea; Ferreira Dias, Michele; Piva Kulakowski, Marlova; Paulo Gomes, Luciana

2015-05-01

Reducing construction waste is becoming a key environmental issue in the construction industry. The quantification of waste generation rates in the construction sector is an invaluable management tool in supporting mitigation actions. However, the quantification of waste can be a difficult process because of the specific characteristics and the wide range of materials used in different construction projects. Large variations are observed in the methods used to predict the amount of waste generated because of the range of variables involved in construction processes and the different contexts in which these methods are employed. This paper proposes a statistical model to determine the amount of waste generated in the construction of high-rise buildings by assessing the influence of design process and production system, often mentioned as the major culprits behind the generation of waste in construction. Multiple regression was used to conduct a case study based on multiple sources of data of eighteen residential buildings. The resulting statistical model produced dependent (i.e. amount of waste generated) and independent variables associated with the design and the production system used. The best regression model obtained from the sample data resulted in an adjusted R(2) value of 0.694, which means that it predicts approximately 69% of the factors involved in the generation of waste in similar constructions. Most independent variables showed a low determination coefficient when assessed in isolation, which emphasizes the importance of assessing their joint influence on the response (dependent) variable. Copyright © 2015 Elsevier Ltd. All rights reserved.

Factors influencing crime rates: an econometric analysis approach

NASA Astrophysics Data System (ADS)

Bothos, John M. A.; Thomopoulos, Stelios C. A.

2016-05-01

The scope of the present study is to research the dynamics that determine the commission of crimes in the US society. Our study is part of a model we are developing to understand urban crime dynamics and to enhance citizens' "perception of security" in large urban environments. The main targets of our research are to highlight dependence of crime rates on certain social and economic factors and basic elements of state anticrime policies. In conducting our research, we use as guides previous relevant studies on crime dependence, that have been performed with similar quantitative analyses in mind, regarding the dependence of crime on certain social and economic factors using statistics and econometric modelling. Our first approach consists of conceptual state space dynamic cross-sectional econometric models that incorporate a feedback loop that describes crime as a feedback process. In order to define dynamically the model variables, we use statistical analysis on crime records and on records about social and economic conditions and policing characteristics (like police force and policing results - crime arrests), to determine their influence as independent variables on crime, as the dependent variable of our model. The econometric models we apply in this first approach are an exponential log linear model and a logit model. In a second approach, we try to study the evolvement of violent crime through time in the US, independently as an autonomous social phenomenon, using autoregressive and moving average time-series econometric models. Our findings show that there are certain social and economic characteristics that affect the formation of crime rates in the US, either positively or negatively. Furthermore, the results of our time-series econometric modelling show that violent crime, viewed solely and independently as a social phenomenon, correlates with previous years crime rates and depends on the social and economic environment's conditions during previous years.

Evaluating the Use of Existing Data Sources, Probabilistic Linkage, and Multiple Imputation to Build Population-based Injury Databases Across Phases of Trauma Care

PubMed Central

Newgard, Craig; Malveau, Susan; Staudenmayer, Kristan; Wang, N. Ewen; Hsia, Renee Y.; Mann, N. Clay; Holmes, James F.; Kuppermann, Nathan; Haukoos, Jason S.; Bulger, Eileen M.; Dai, Mengtao; Cook, Lawrence J.

2012-01-01

Objectives The objective was to evaluate the process of using existing data sources, probabilistic linkage, and multiple imputation to create large population-based injury databases matched to outcomes. Methods This was a retrospective cohort study of injured children and adults transported by 94 emergency medical systems (EMS) agencies to 122 hospitals in seven regions of the western United States over a 36-month period (2006 to 2008). All injured patients evaluated by EMS personnel within specific geographic catchment areas were included, regardless of field disposition or outcome. The authors performed probabilistic linkage of EMS records to four hospital and postdischarge data sources (emergency department [ED] data, patient discharge data, trauma registries, and vital statistics files) and then handled missing values using multiple imputation. The authors compare and evaluate matched records, match rates (proportion of matches among eligible patients), and injury outcomes within and across sites. Results There were 381,719 injured patients evaluated by EMS personnel in the seven regions. Among transported patients, match rates ranged from 14.9% to 87.5% and were directly affected by the availability of hospital data sources and proportion of missing values for key linkage variables. For vital statistics records (1-year mortality), estimated match rates ranged from 88.0% to 98.7%. Use of multiple imputation (compared to complete case analysis) reduced bias for injury outcomes, although sample size, percentage missing, type of variable, and combined-site versus single-site imputation models all affected the resulting estimates and variance. Conclusions This project demonstrates the feasibility and describes the process of constructing population-based injury databases across multiple phases of care using existing data sources and commonly available analytic methods. Attention to key linkage variables and decisions for handling missing values can be used to increase match rates between data sources, minimize bias, and preserve sampling design. PMID:22506952

Assessment of statistical methods used in library-based approaches to microbial source tracking.

PubMed

Ritter, Kerry J; Carruthers, Ethan; Carson, C Andrew; Ellender, R D; Harwood, Valerie J; Kingsley, Kyle; Nakatsu, Cindy; Sadowsky, Michael; Shear, Brian; West, Brian; Whitlock, John E; Wiggins, Bruce A; Wilbur, Jayson D

2003-12-01

Several commonly used statistical methods for fingerprint identification in microbial source tracking (MST) were examined to assess the effectiveness of pattern-matching algorithms to correctly identify sources. Although numerous statistical methods have been employed for source identification, no widespread consensus exists as to which is most appropriate. A large-scale comparison of several MST methods, using identical fecal sources, presented a unique opportunity to assess the utility of several popular statistical methods. These included discriminant analysis, nearest neighbour analysis, maximum similarity and average similarity, along with several measures of distance or similarity. Threshold criteria for excluding uncertain or poorly matched isolates from final analysis were also examined for their ability to reduce false positives and increase prediction success. Six independent libraries used in the study were constructed from indicator bacteria isolated from fecal materials of humans, seagulls, cows and dogs. Three of these libraries were constructed using the rep-PCR technique and three relied on antibiotic resistance analysis (ARA). Five of the libraries were constructed using Escherichia coli and one using Enterococcus spp. (ARA). Overall, the outcome of this study suggests a high degree of variability across statistical methods. Despite large differences in correct classification rates among the statistical methods, no single statistical approach emerged as superior. Thresholds failed to consistently increase rates of correct classification and improvement was often associated with substantial effective sample size reduction. Recommendations are provided to aid in selecting appropriate analyses for these types of data.

Measuring determinants of career satisfaction of anesthesiologists: validation of a survey instrument.

PubMed

Afonso, Anoushka M; Diaz, James H; Scher, Corey S; Beyl, Robbie A; Nair, Singh R; Kaye, Alan David

2013-06-01

To measure the parameter of job satisfaction among anesthesiologists. Survey instrument. Academic anesthesiology departments in the United States. 320 anesthesiologists who attended the annual meeting of the ASA in 2009 (95% response rate). The anonymous 50-item survey collected information on 26 independent demographic variables and 24 dependent ranked variables of career satisfaction among practicing anesthesiologists. Mean survey scores were calculated for each demographic variable and tested for statistically significant differences by analysis of variance. Questions within each domain that were internally consistent with each other within domains were identified by Cronbach's alpha ≥ 0.7. P-values ≤ 0.05 were considered statistically significant. Cronbach's alpha analysis showed strong internal consistency for 10 dependent outcome questions in the practice factor-related domain (α = 0.72), 6 dependent outcome questions in the peer factor-related domain (α = 0.71), and 8 dependent outcome questions in the personal factor-related domain (α = 0.81). Although age was not a variable, full-time status, early satisfaction within the first 5 years of practice, working with respected peers, and personal choice factors were all significantly associated with anesthesiologist job satisfaction. Improvements in factors related to job satisfaction among anesthesiologists may lead to higher early and current career satisfaction. Copyright © 2013 Elsevier Inc. All rights reserved.

Association between the Density of Physicians and Suicide Rates in Japan: Nationwide Ecological Study Using a Spatial Bayesian Model.

PubMed

Kawaguchi, Hideaki; Koike, Soichi

2016-01-01

Regional disparity in suicide rates is a serious problem worldwide. One possible cause is unequal distribution of the health workforce, especially psychiatrists. Research about the association between regional physician numbers and suicide rates is therefore important but studies are rare. The objective of this study was to evaluate the association between physician numbers and suicide rates in Japan, by municipality. The study included all the municipalities in Japan (n = 1,896). We estimated smoothed standardized mortality ratios of suicide rates for each municipality and evaluated the association between health workforce and suicide rates using a hierarchical Bayesian model accounting for spatially correlated random effects, a conditional autoregressive model. We assumed a Poisson distribution for the observed number of suicides and set the expected number of suicides as the offset variable. The explanatory variables were numbers of physicians, a binary variable for the presence of psychiatrists, and social covariates. After adjustment for socioeconomic factors, suicide rates in municipalities that had at least one psychiatrist were lower than those in the other municipalities. There was, however, a positive and statistically significant association between the number of physicians and suicide rates. Suicide rates in municipalities that had at least one psychiatrist were lower than those in other municipalities, but the number of physicians was positively and significantly related with suicide rates. To improve the regional disparity in suicide rates, the government should encourage psychiatrists to participate in community-based suicide prevention programs and to settle in municipalities that currently have no psychiatrists. The government and other stakeholders should also construct better networks between psychiatrists and non-psychiatrists to support sharing of information for suicide prevention.

Female homicide in Rio Grande do Sul, Brazil.

PubMed

Leites, Gabriela Tomedi; Meneghel, Stela Nazareth; Hirakata, Vania Noemi

2014-01-01

This study aimed to assess the female homicide rate due to aggression in Rio Grande do Sul, Brazil, using this as a "proxy" of femicide. This was an ecological study which correlated the female homicide rate due to aggression in Rio Grande do Sul, according to the 35 microregions defined by the Brazilian Institute of Geography and Statistics (IBGE), with socioeconomic and demographic variables access and health indicators. Pearson's correlation test was performed with the selected variables. After this, multiple linear regressions were performed with variables with p < 0.20. The standardized average of female homicide rate due to aggression in the period from 2003 to 2007 was 3.1 obits per 100 thousand. After multiple regression analysis, the final model included male mortality due to aggression (p = 0.016), the percentage of hospital admissions for alcohol (p = 0.005) and the proportion of ill-defined deaths (p = 0.015). The model have an explanatory power of 39% (adjusted r2 = 0.391). The results are consistent with other studies and indicate a strong relationship between structural violence in society and violence against women, in addition to a higher incidence of female deaths in places with high alcohol hospitalization.

Perceptions of work environment priorities: Are there any differences by company size? An ecological study.

PubMed

Nordlöf, Hasse; Wijk, Katarina; Westergren, Karl-Erik

2015-01-01

Earlier studies suggest that the quality of handling occupational health and safety (OHS) activities differs between companies of different sizes. Company size is a proxy variable for other variables affecting OHS performance. The objective of this study was to investigate if there is an association between company size and perceptions of work environment prioritizations. Data from 106 small- and medium-sized Swedish manufacturing companies was collected. One manager and one safety delegate at each company rated different aspects of their companies' work environment prioritizations with a 43-item questionnaire. Ratings were aggregated to a summary statistic for each company before analysis. No significant differences in perceptions of priority were found to be associated with company sizes. This is in contrast to earlier studies of objective differences. The respondents in small companies, however, showed significantly greater consensus in their ratings. Company size does not appear to be associated with perceptions of work environment prioritizations. Company size is an important proxy variable to study in order to understand what factors enable and obstruct safe and healthy workplaces. The work presented here should be viewed as an initial exploration to serve as direction for future academic work.

Feasibility of Estimating Constituent Concentrations and Loads Based on Data Recorded by Acoustic Instrumentation

USGS Publications Warehouse

Lietz, A.C.

2002-01-01

The acoustic Doppler current profiler (ADCP) and acoustic Doppler velocity meter (ADVM) were used to estimate constituent concentrations and loads at a sampling site along the Hendry-Collier County boundary in southwestern Florida. The sampling site is strategically placed within a highly managed canal system that exhibits low and rapidly changing water conditions. With the ADCP and ADVM, flow can be gaged more accurately rather than by conventional field-data collection methods. An ADVM velocity rating relates measured velocity determined by the ADCP (dependent variable) with the ADVM velocity (independent variable) by means of regression analysis techniques. The coefficient of determination (R2) for this rating is 0.99 at the sampling site. Concentrations and loads of total phosphorus, total Kjeldahl nitrogen, and total nitrogen (dependent variables) were related to instantaneous discharge, acoustic backscatter, stage, or water temperature (independent variables) recorded at the time of sampling. Only positive discharges were used for this analysis. Discharges less than 100 cubic feet per second generally are considered inaccurate (probably as a result of acoustic ray bending and vertical temperature gradients in the water column). Of the concentration models, only total phosphorus was statistically significant at the 95-percent confidence level (p-value less than 0.05). Total phosphorus had an adjusted R2 of 0.93, indicating most of the variation in the concentration can be explained by the discharge. All of the load models for total phosphorus, total Kjeldahl nitrogen, and total nitrogen were statistically significant. Most of the variation in load can be explained by the discharge as reflected in the adjusted R2 for total phosphorus (0.98), total Kjeldahl nitrogen (0.99), and total nitrogen (0.99).

[Comparison of health education and drug therapy monitoring interventions in patients with cardiovascular risk factors attending a community pharmacy (FISFTES-PM Study)].

PubMed

Bofí Martínez, Patricia; García Jiménez, Emilio; Martínez Martínez, Fernando

2015-03-01

To compare health education (HE) and drug therapy monitoring (DTM) interventions in patients with cardiovascular risk factors (CVRF). Randomised experimental studys: 100 patients per group. Playa-Miramar pharmacy (Valencia, Spain). March 2010-November 2011. Patients with one or more CVRF detected based on medication they were taking or questions they asked when drugs were dispensed. Patients were assigned to one of the two groups (HE or DTM) using a random number table. 100 patients by group were included. Six months of DTM (DTMG) or health education (HEG) per patient. The primary variables were modifiable CVRF: hypertension, dyslipidaemia, diabetes, smoking, obesity and low physical activity. Secondary variables were non modifiable CVRF (age, sex, cardiovascular disease), heart rate, body mass index, waist measurement, waist-to-hip ratio, waist-to-height ratio, body fat, treatment compliance. The differences in the reduction percentages were statistically greater in DTMG than in HEG for the following variables: systolic pressure 5.40% (p=0.001); heart rate 2.95%(p=0.015); weight 2.00% (p=0.002); BMI 2.24% (p=0.003); fasting glucose 8.65% (p=0.004); total cholesterol 6.45% (p=0.002); waist measurement 1.85% (p=0.010); and waist-to-height ratio 1.66% (p=0.002). Triglycerides and body fat were reduced by 12.78% (p<0.001) and 1.84% (p<0.001) more, respectively, in DTMG. These differences were not statistically significant. The reduction percentages were generally higher for all variables in DTMG except diastolic blood pressure, which decreased by 4.7% (P<.001) more in HEG because the baseline values were higher. Copyright © 2013 Elsevier España, S.L.U. All rights reserved.

An astronomer's guide to period searching

NASA Astrophysics Data System (ADS)

Schwarzenberg-Czerny, A.

2003-03-01

We concentrate on analysis of unevenly sampled time series, interrupted by periodic gaps, as often encountered in astronomy. While some of our conclusions may appear surprising, all are based on classical statistical principles of Fisher & successors. Except for discussion of the resolution issues, it is best for the reader to forget temporarily about Fourier transforms and to concentrate on problems of fitting of a time series with a model curve. According to their statistical content we divide the issues into several sections, consisting of: (ii) statistical numerical aspects of model fitting, (iii) evaluation of fitted models as hypotheses testing, (iv) the role of the orthogonal models in signal detection (v) conditions for equivalence of periodograms (vi) rating sensitivity by test power. An experienced observer working with individual objects would benefit little from formalized statistical approach. However, we demonstrate the usefulness of this approach in evaluation of performance of periodograms and in quantitative design of large variability surveys.

Factors influencing incidence and type of postmastectomy breast reconstruction in an urban multidisciplinary cancer center.

PubMed

Iskandar, Mazen E; Dayan, Erez; Lucido, David; Samson, William; Sultan, Mark; Dayan, Joseph H; Boolbol, Susan K; Smith, Mark L

2015-02-01

On January 1, 2011, New York State amended the Public Health Law to ensure that patients receive "information and access to breast reconstruction surgery." The purposes of this study were to investigate the early impact of this legislation on reconstruction rates and to evaluate the influence of patient variables versus physician variables on the incidence and type of breast reconstruction performed. A retrospective study was conducted on all patients who underwent mastectomy between January 1, 2010, and December 31, 2011. Reconstruction rates were analyzed in relation to timing of legislation, breast surgeon variables, plastic surgeon faculty status, type of reconstruction, and patient variables. Two hundred fifty-eight patients met inclusion criteria. The overall reconstruction rate was 56.59 percent. There was no statistically significant increase in reconstruction rate after the 2011 legislation (OR, 0.45; p = 0.057). Patients whose breast surgeon was female were more likely to undergo reconstruction (OR, 5.17; p = 0.001). Patients who were Asian (OR, 0.22; p = 0.002), older than 60 years (OR, 0.09; p = 0.001), or had stage 3 and 4 cancer (OR, 0.04; p = 0.03) were less likely to undergo reconstruction. Patients reconstructed by a hospital-employed plastic surgeon were significantly more likely to undergo autologous versus implant reconstruction (OR, 6.85; p = 0.001) and to undergo microsurgical versus nonmicrosurgical autologous reconstruction (78.2 percent versus 0 percent; p = 0.001). Breast surgeon sex and plastic surgeon faculty status were the factors that most affected the rate and type of reconstruction, respectively. Legislation mandating the discussion of breast reconstruction options had no impact on reconstruction rate. Risk, II.

Single-row, double-row, and transosseous equivalent techniques for isolated supraspinatus tendon tears with minimal atrophy: A retrospective comparative outcome and radiographic analysis at minimum 2-year followup

PubMed Central

McCormick, Frank; Gupta, Anil; Bruce, Ben; Harris, Josh; Abrams, Geoff; Wilson, Hillary; Hussey, Kristen; Cole, Brian J.

2014-01-01

Purpose: The purpose of this study was to measure and compare the subjective, objective, and radiographic healing outcomes of single-row (SR), double-row (DR), and transosseous equivalent (TOE) suture techniques for arthroscopic rotator cuff repair. Materials and Methods: A retrospective comparative analysis of arthroscopic rotator cuff repairs by one surgeon from 2004 to 2010 at minimum 2-year followup was performed. Cohorts were matched for age, sex, and tear size. Subjective outcome variables included ASES, Constant, SST, UCLA, and SF-12 scores. Objective outcome variables included strength, active range of motion (ROM). Radiographic healing was assessed by magnetic resonance imaging (MRI). Statistical analysis was performed using analysis of variance (ANOVA), Mann — Whitney and Kruskal — Wallis tests with significance, and the Fisher exact probability test <0.05. Results: Sixty-three patients completed the study requirements (20 SR, 21 DR, 22 TOE). There was a clinically and statistically significant improvement in outcomes with all repair techniques (ASES mean improvement P = <0.0001). The mean final ASES scores were: SR 83; (SD 21.4); DR 87 (SD 18.2); TOE 87 (SD 13.2); (P = 0.73). There was a statistically significant improvement in strength for each repair technique (P < 0.001). There was no significant difference between techniques across all secondary outcome assessments: ASES improvement, Constant, SST, UCLA, SF-12, ROM, Strength, and MRI re-tear rates. There was a decrease in re-tear rates from single row (22%) to double-row (18%) to transosseous equivalent (11%); however, this difference was not statistically significant (P = 0.6). Conclusions: Compared to preoperatively, arthroscopic rotator cuff repair, using SR, DR, or TOE techniques, yielded a clinically and statistically significant improvement in subjective and objective outcomes at a minimum 2-year follow-up. Level of Evidence: Therapeutic level 3. PMID:24926159

Statistics of Stokes variables for correlated Gaussian fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eliyahu, D.

1994-09-01

The joint and marginal probability distribution functions of the Stokes variables are derived for correlated Gaussian fields [an extension of D. Eliyahu, Phys. Rev. E 47, 2881 (1993)]. The statistics depend only on the first moment (averaged) Stokes variables and have a universal form for [ital S][sub 1], [ital S][sub 2], and [ital S][sub 3]. The statistics of the variables describing the Cartesian coordinates of the Poincare sphere are given also.

Statistical optics

NASA Astrophysics Data System (ADS)

Goodman, J. W.

This book is based on the thesis that some training in the area of statistical optics should be included as a standard part of any advanced optics curriculum. Random variables are discussed, taking into account definitions of probability and random variables, distribution functions and density functions, an extension to two or more random variables, statistical averages, transformations of random variables, sums of real random variables, Gaussian random variables, complex-valued random variables, and random phasor sums. Other subjects examined are related to random processes, some first-order properties of light waves, the coherence of optical waves, some problems involving high-order coherence, effects of partial coherence on imaging systems, imaging in the presence of randomly inhomogeneous media, and fundamental limits in photoelectric detection of light. Attention is given to deterministic versus statistical phenomena and models, the Fourier transform, and the fourth-order moment of the spectrum of a detected speckle image.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Poyer, D.A.

In this report, tests of statistical significance of five sets of variables with household energy consumption (at the point of end-use) are described. Five models, in sequence, were empirically estimated and tested for statistical significance by using the Residential Energy Consumption Survey of the US Department of Energy, Energy Information Administration. Each model incorporated additional information, embodied in a set of variables not previously specified in the energy demand system. The variable sets were generally labeled as economic variables, weather variables, household-structure variables, end-use variables, and housing-type variables. The tests of statistical significance showed each of the variable sets tomore » be highly significant in explaining the overall variance in energy consumption. The findings imply that the contemporaneous interaction of different types of variables, and not just one exclusive set of variables, determines the level of household energy consumption.« less

A Novel Genome-Information Content-Based Statistic for Genome-Wide Association Analysis Designed for Next-Generation Sequencing Data

PubMed Central

Luo, Li; Zhu, Yun

2012-01-01

Abstract The genome-wide association studies (GWAS) designed for next-generation sequencing data involve testing association of genomic variants, including common, low frequency, and rare variants. The current strategies for association studies are well developed for identifying association of common variants with the common diseases, but may be ill-suited when large amounts of allelic heterogeneity are present in sequence data. Recently, group tests that analyze their collective frequency differences between cases and controls shift the current variant-by-variant analysis paradigm for GWAS of common variants to the collective test of multiple variants in the association analysis of rare variants. However, group tests ignore differences in genetic effects among SNPs at different genomic locations. As an alternative to group tests, we developed a novel genome-information content-based statistics for testing association of the entire allele frequency spectrum of genomic variation with the diseases. To evaluate the performance of the proposed statistics, we use large-scale simulations based on whole genome low coverage pilot data in the 1000 Genomes Project to calculate the type 1 error rates and power of seven alternative statistics: a genome-information content-based statistic, the generalized T2, collapsing method, multivariate and collapsing (CMC) method, individual χ2 test, weighted-sum statistic, and variable threshold statistic. Finally, we apply the seven statistics to published resequencing dataset from ANGPTL3, ANGPTL4, ANGPTL5, and ANGPTL6 genes in the Dallas Heart Study. We report that the genome-information content-based statistic has significantly improved type 1 error rates and higher power than the other six statistics in both simulated and empirical datasets. PMID:22651812

A novel genome-information content-based statistic for genome-wide association analysis designed for next-generation sequencing data.

PubMed

Luo, Li; Zhu, Yun; Xiong, Momiao

2012-06-01

The genome-wide association studies (GWAS) designed for next-generation sequencing data involve testing association of genomic variants, including common, low frequency, and rare variants. The current strategies for association studies are well developed for identifying association of common variants with the common diseases, but may be ill-suited when large amounts of allelic heterogeneity are present in sequence data. Recently, group tests that analyze their collective frequency differences between cases and controls shift the current variant-by-variant analysis paradigm for GWAS of common variants to the collective test of multiple variants in the association analysis of rare variants. However, group tests ignore differences in genetic effects among SNPs at different genomic locations. As an alternative to group tests, we developed a novel genome-information content-based statistics for testing association of the entire allele frequency spectrum of genomic variation with the diseases. To evaluate the performance of the proposed statistics, we use large-scale simulations based on whole genome low coverage pilot data in the 1000 Genomes Project to calculate the type 1 error rates and power of seven alternative statistics: a genome-information content-based statistic, the generalized T(2), collapsing method, multivariate and collapsing (CMC) method, individual χ(2) test, weighted-sum statistic, and variable threshold statistic. Finally, we apply the seven statistics to published resequencing dataset from ANGPTL3, ANGPTL4, ANGPTL5, and ANGPTL6 genes in the Dallas Heart Study. We report that the genome-information content-based statistic has significantly improved type 1 error rates and higher power than the other six statistics in both simulated and empirical datasets.

Climate impact on suicide rates in Finland from 1971 to 2003

NASA Astrophysics Data System (ADS)

Ruuhela, Reija; Hiltunen, Laura; Venäläinen, Ari; Pirinen, Pentti; Partonen, Timo

2009-03-01

Seasonal patterns of death from suicide are well-documented and have been attributed to climatic factors such as solar radiation and ambient temperature. However, studies on the impact of weather and climate on suicide are not consistent, and conflicting data have been reported. In this study, we performed a correlation analysis between nationwide suicide rates and weather variables in Finland during the period 1971-2003. The weather parameters studied were global solar radiation, temperature and precipitation, and a range of time spans from 1 month to 1 year were used in order to elucidate the dose-response relationship, if any, between weather variables and suicide. Single and multiple linear regression models show weak associations using 1-month and 3-month time spans, but robust associations using a 12-month time span. Cumulative global solar radiation had the best explanatory power, while average temperature and cumulative precipitation had only a minor impact on suicide rates. Our results demonstrate that winters with low global radiation may increase the risk of suicide. The best correlation found was for the 5-month period from November to March; the inter-annual variability in the cumulative global radiation for that period explained 40 % of the variation in the male suicide rate and 14 % of the variation in the female suicide rate, both at a statistically significant level. Long-term variations in global radiation may also explain, in part, the observed increasing trend in the suicide rate until 1990 and the decreasing trend since then in Finland.

Prediction of slant path rain attenuation statistics at various locations

NASA Technical Reports Server (NTRS)

Goldhirsh, J.

1977-01-01

The paper describes a method for predicting slant path attenuation statistics at arbitrary locations for variable frequencies and path elevation angles. The method involves the use of median reflectivity factor-height profiles measured with radar as well as the use of long-term point rain rate data and assumed or measured drop size distributions. The attenuation coefficient due to cloud liquid water in the presence of rain is also considered. Absolute probability fade distributions are compared for eight cases: Maryland (15 GHz), Texas (30 GHz), Slough, England (19 and 37 GHz), Fayetteville, North Carolina (13 and 18 GHz), and Cambridge, Massachusetts (13 and 18 GHz).

Designed experiment evaluation of key variables affecting the cutting performance of rotary instruments.

PubMed

Funkenbusch, Paul D; Rotella, Mario; Ercoli, Carlo

2015-04-01

Laboratory studies of tooth preparation are often performed under a limited range of conditions involving single values for all variables other than the 1 being tested. In contrast, in clinical settings not all variables can be tightly controlled. For example, a new dental rotary cutting instrument may be tested in the laboratory by making a specific cut with a fixed force, but in clinical practice, the instrument must make different cuts with individual dentists applying a range of different forces. Therefore, the broad applicability of laboratory results to diverse clinical conditions is uncertain and the comparison of effects across studies is difficult. The purpose of this study was to examine the effect of 9 process variables on dental cutting in a single experiment, allowing each variable to be robustly tested over a range of values for the other 8 and permitting a direct comparison of the relative importance of each on the cutting process. The effects of 9 key process variables on the efficiency of a simulated dental cutting operation were measured. A fractional factorial experiment was conducted by using a computer-controlled, dedicated testing apparatus to simulate dental cutting procedures and Macor blocks as the cutting substrate. Analysis of Variance (ANOVA) was used to judge the statistical significance (α=.05). Five variables consistently produced large, statistically significant effects (target applied load, cut length, starting rpm, diamond grit size, and cut type), while 4 variables produced relatively small, statistically insignificant effects (number of cooling ports, rotary cutting instrument diameter, disposability, and water flow rate). The control exerted by the dentist, simulated in this study by targeting a specific level of applied force, was the single most important factor affecting cutting efficiency. Cutting efficiency was also significantly affected by factors simulating patient/clinical circumstances as well as hardware choices. These results highlight the importance of local clinical conditions (procedure, dentist) in understanding dental cutting procedures and in designing adequate experimental methodologies for future studies. Copyright © 2015 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

Paced respiration with end-expiration technique offers superior BOLD signal repeatability for breath-hold studies.

PubMed

Scouten, A; Schwarzbauer, C

2008-11-01

As a simple, non-invasive method of blood oxygenation level-dependent (BOLD) signal calibration, the breath-hold task offers considerable potential for the quantification of neuronal activity from functional magnetic resonance imaging (fMRI) measurements. With an aim to improve the precision of this calibration method, the impact of respiratory rate control on the BOLD signal achieved with the breath-hold task was investigated. In addition to self-paced breathing, three different computer-paced breathing rates were imposed during the periods between end-expiration breath-hold blocks. The resulting BOLD signal timecourses and statistical activation maps were compared in eleven healthy human subjects. Results indicate that computer-paced respiration produces a larger peak BOLD signal increase with breath-hold than self-paced breathing, in addition to lower variability between trials. This is due to the more significant post-breath-hold signal undershoot present in self-paced runs, a characteristic which confounds the definition of baseline and is difficult to accurately model. Interestingly, the specific respiratory rate imposed between breath-hold periods generally does not have a statistically significant impact on the BOLD signal change. This result can be explained by previous reports of humans adjusting their inhalation depth to compensate for changes in rate, with the end-goal of maintaining homeostatic ventilation. The advantage of using end-expiration relative to end-inspiration breath-hold is apparent in view of the high repeatability of the BOLD signal in the present study, which does not suffer from the previously reported high variability associated with uncontrolled inspiration depth when using the end-inspiration technique.

Masters theses from a university medical college: Publication in indexed scientific journals

PubMed Central

Dhaliwal, Upreet; Singh, Navjeevan; Bhatia, Arati

2010-01-01

Background: The thesis is an integral part of postgraduate medical education in India. Publication of the results of the thesis in an indexed journal is desirable; it validates the research and makes results available to researchers worldwide. Aims: To determine publication rates in indexed journals, of works derived from theses, and factors affecting publication. Settings and Design: Postgraduate theses submitted over a five-year period (2001-05) in a university medical college were analyzed in a retrospective, observational study. Materials and Methods: Data retrieved included name and gender of postgraduate student, names, department and hierarchy of supervisor and co-supervisor(s), year submitted, study design, sample size, and statistically significant difference between groups. To determine subsequent publication in an indexed journal, Medline search was performed up to December 2007. Statistical Analysis: Chi square test was used to compare publication rates based on categorical variables; Student's t-test was used to compare differences based on continuous variables. Results: One hundred and sixty theses were retrieved, forty-eight (30%) were published. Papers were published 8-74 (33.7 ± 17.33) months after thesis submission; the postgraduate student was first author in papers from 26 (54%) of the published theses. Gender of the student, department of origin, year of thesis submission, hierarchy of the supervisor, number and department of co-supervisors, and thesis characteristics did not influence publication rates. Conclusions: Rate of publication in indexed journals, of papers derived from postgraduate theses is 30%. In this study we were unable to identify factors that promote publication. PMID:20195030

The influence of base rates on correlations: An evaluation of proposed alternative effect sizes with real-world data.

PubMed

Babchishin, Kelly M; Helmus, Leslie-Maaike

2016-09-01

Correlations are the simplest and most commonly understood effect size statistic in psychology. The purpose of the current paper was to use a large sample of real-world data (109 correlations with 60,415 participants) to illustrate the base rate dependence of correlations when applied to dichotomous or ordinal data. Specifically, we examined the influence of the base rate on different effect size metrics. Correlations decreased when the dichotomous variable did not have a 50 % base rate. The higher the deviation from a 50 % base rate, the smaller the observed Pearson's point-biserial and Kendall's tau correlation coefficients. In contrast, the relationship between base rate deviations and the more commonly proposed alternatives (i.e., polychoric correlation coefficients, AUCs, Pearson/Thorndike adjusted correlations, and Cohen's d) were less remarkable, with AUCs being most robust to attenuation due to base rates. In other words, the base rate makes a marked difference in the magnitude of the correlation. As such, when using dichotomous data, the correlation may be more sensitive to base rates than is optimal for the researcher's goals. Given the magnitude of the association between the base rate and point-biserial correlations (r = -.81) and Kendall's tau (r = -.80), we recommend that AUCs, Pearson/Thorndike adjusted correlations, Cohen's d, or polychoric correlations should be considered as alternate effect size statistics in many contexts.

Documenting a significant relationship between macroevolutionary origination rates and Phanerozoic pCO2 levels.

PubMed

Cornette, James L; Lieberman, Bruce S; Goldstein, Robert H

2002-06-11

We show that the rates of diversification of the marine fauna and the levels of atmospheric CO(2) have been closely correlated for the past 545 million years. These results, using two of the fundamental databases of the Earth's biota and the Earth's atmospheric composition, respectively, are highly statistically significant (P < 0.001). The strength of the correlation suggests that one or more environmental variables controlling CO(2) levels have had a profound impact on evolution throughout the history of metazoan life. Comparing our work with highly significant correlations described by D. H. Rothman [Rothman, D. H. (2001) Proc. Natl. Acad. Sci. USA 98, 4305-4310] between total biological diversity and a measure of stable carbon isotope fractionation, we find that the rates of diversification rather than total diversification correlate with environmental variables, and that the rate of diversification follows the record of CO(2) projected by R. A. Berner and Z. Kothavala [Berner, R. A. & Kothavala, Z. (2001) Am. J. Sci. 301, 182-204] more closely than that predicted by Rothman.

Variability of individual genetic load: consequences for the detection of inbreeding depression.

PubMed

Restoux, Gwendal; Huot de Longchamp, Priscille; Fady, Bruno; Klein, Etienne K

2012-03-01

Inbreeding depression is a key factor affecting the persistence of natural populations, particularly when they are fragmented. In species with mixed mating systems, inbreeding depression can be estimated at the population level by regressing the average progeny fitness by the selfing rate of their mothers. We applied this method using simulated populations to investigate how population genetic parameters can affect the detection power of inbreeding depression. We simulated individual selfing rates and genetic loads from which we computed fitness values. The regression method yielded high statistical power, inbreeding depression being detected as significant (5 % level) in 92 % of the simulations. High individual variation in selfing rate and high mean genetic load led to better detection of inbreeding depression while high among-individual variation in genetic load made it more difficult to detect inbreeding depression. For a constant sampling effort, increasing the number of progenies while decreasing the number of individuals per progeny enhanced the detection power of inbreeding depression. We discuss the implication of among-mother variability of genetic load and selfing rate on inbreeding depression studies.

Exploring models for the roles of health systems’ responsiveness and social determinants in explaining universal health coverage and health outcomes

PubMed Central

Bonsel, Gouke J.

2016-01-01

Background Intersectoral perspectives of health are present in the rhetoric of the sustainable development goals. Yet its descriptions of systematic approaches for an intersectoral monitoring vision, joining determinants of health, and barriers or facilitators to accessing healthcare services are lacking. Objective To explore models of associations between health outcomes and health service coverage, and health determinants and health systems responsiveness, and thereby to contribute to monitoring, analysis, and assessment approaches informed by an intersectoral vision of health. Design The study is designed as a series of ecological, cross-country regression analyses, covering between 23 and 57 countries with dependent health variables concentrated on the years 2002–2003. Countries cover a range of development contexts. Health outcome and health service coverage dependent variables were derived from World Health Organization (WHO) information sources. Predictor variables representing determinants are derived from the WHO and World Bank databases; variables used for health systems’ responsiveness are derived from the WHO World Health Survey. Responsiveness is a measure of acceptability of health services to the population, complementing financial health protection. Results Health determinants’ indicators – access to improved drinking sources, accountability, and average years of schooling – were statistically significant in particular health outcome regressions. Statistically significant coefficients were more common for mortality rate regressions than for coverage rate regressions. Responsiveness was systematically associated with poorer health and health service coverage. With respect to levels of inequality in health, the indicator of responsiveness problems experienced by the unhealthy poor groups in the population was statistically significant for regressions on measles vaccination inequalities between rich and poor. For the broader determinants, the Gini mattered most for inequalities in child mortality; education mattered more for inequalities in births attended by skilled personnel. Conclusions This paper adds to the literature on comparative health systems research. National and international health monitoring frameworks need to incorporate indicators on trends in and impacts of other policy sectors on health. This will empower the health sector to carry out public health practices that promote health and health equity. PMID:26942516

Exploring models for the roles of health systems' responsiveness and social determinants in explaining universal health coverage and health outcomes.

PubMed

Valentine, Nicole Britt; Bonsel, Gouke J

2016-01-01

Intersectoral perspectives of health are present in the rhetoric of the sustainable development goals. Yet its descriptions of systematic approaches for an intersectoral monitoring vision, joining determinants of health, and barriers or facilitators to accessing healthcare services are lacking. To explore models of associations between health outcomes and health service coverage, and health determinants and health systems responsiveness, and thereby to contribute to monitoring, analysis, and assessment approaches informed by an intersectoral vision of health. The study is designed as a series of ecological, cross-country regression analyses, covering between 23 and 57 countries with dependent health variables concentrated on the years 2002-2003. Countries cover a range of development contexts. Health outcome and health service coverage dependent variables were derived from World Health Organization (WHO) information sources. Predictor variables representing determinants are derived from the WHO and World Bank databases; variables used for health systems' responsiveness are derived from the WHO World Health Survey. Responsiveness is a measure of acceptability of health services to the population, complementing financial health protection. Health determinants' indicators - access to improved drinking sources, accountability, and average years of schooling - were statistically significant in particular health outcome regressions. Statistically significant coefficients were more common for mortality rate regressions than for coverage rate regressions. Responsiveness was systematically associated with poorer health and health service coverage. With respect to levels of inequality in health, the indicator of responsiveness problems experienced by the unhealthy poor groups in the population was statistically significant for regressions on measles vaccination inequalities between rich and poor. For the broader determinants, the Gini mattered most for inequalities in child mortality; education mattered more for inequalities in births attended by skilled personnel. This paper adds to the literature on comparative health systems research. National and international health monitoring frameworks need to incorporate indicators on trends in and impacts of other policy sectors on health. This will empower the health sector to carry out public health practices that promote health and health equity.

Population activity statistics dissect subthreshold and spiking variability in V1.

PubMed

Bányai, Mihály; Koman, Zsombor; Orbán, Gergő

2017-07-01

Response variability, as measured by fluctuating responses upon repeated performance of trials, is a major component of neural responses, and its characterization is key to interpret high dimensional population recordings. Response variability and covariability display predictable changes upon changes in stimulus and cognitive or behavioral state, providing an opportunity to test the predictive power of models of neural variability. Still, there is little agreement on which model to use as a building block for population-level analyses, and models of variability are often treated as a subject of choice. We investigate two competing models, the doubly stochastic Poisson (DSP) model assuming stochasticity at spike generation, and the rectified Gaussian (RG) model tracing variability back to membrane potential variance, to analyze stimulus-dependent modulation of both single-neuron and pairwise response statistics. Using a pair of model neurons, we demonstrate that the two models predict similar single-cell statistics. However, DSP and RG models have contradicting predictions on the joint statistics of spiking responses. To test the models against data, we build a population model to simulate stimulus change-related modulations in pairwise response statistics. We use single-unit data from the primary visual cortex (V1) of monkeys to show that while model predictions for variance are qualitatively similar to experimental data, only the RG model's predictions are compatible with joint statistics. These results suggest that models using Poisson-like variability might fail to capture important properties of response statistics. We argue that membrane potential-level modeling of stochasticity provides an efficient strategy to model correlations. NEW & NOTEWORTHY Neural variability and covariability are puzzling aspects of cortical computations. For efficient decoding and prediction, models of information encoding in neural populations hinge on an appropriate model of variability. Our work shows that stimulus-dependent changes in pairwise but not in single-cell statistics can differentiate between two widely used models of neuronal variability. Contrasting model predictions with neuronal data provides hints on the noise sources in spiking and provides constraints on statistical models of population activity. Copyright © 2017 the American Physiological Society.

The relationship between procrastination, learning strategies and statistics anxiety among Iranian college students: a canonical correlation analysis.

PubMed

Vahedi, Shahrum; Farrokhi, Farahman; Gahramani, Farahnaz; Issazadegan, Ali

2012-01-01

Approximately 66-80%of graduate students experience statistics anxiety and some researchers propose that many students identify statistics courses as the most anxiety-inducing courses in their academic curriculums. As such, it is likely that statistics anxiety is, in part, responsible for many students delaying enrollment in these courses for as long as possible. This paper proposes a canonical model by treating academic procrastination (AP), learning strategies (LS) as predictor variables and statistics anxiety (SA) as explained variables. A questionnaire survey was used for data collection and 246-college female student participated in this study. To examine the mutually independent relations between procrastination, learning strategies and statistics anxiety variables, a canonical correlation analysis was computed. Findings show that two canonical functions were statistically significant. The set of variables (metacognitive self-regulation, source management, preparing homework, preparing for test and preparing term papers) helped predict changes of statistics anxiety with respect to fearful behavior, Attitude towards math and class, Performance, but not Anxiety. These findings could be used in educational and psychological interventions in the context of statistics anxiety reduction.

Beyond the conventional understanding of water-rock reactivity

NASA Astrophysics Data System (ADS)

Fischer, Cornelius; Luttge, Andreas

2017-01-01

A common assumption is that water-rock reaction rates should converge to a mean value. There is, however, an emerging consensus on the genuine nature of reaction rate variations under identical chemical conditions. Thus, the further use of mean reaction rates for the prediction of material fluxes is environmentally and economically risky, manifest for example in the management of nuclear waste or the evolution of reservoir rocks. Surface-sensitive methods and resulting information about heterogeneous surface reactivity illustrate the inherent rate variability. Consequently, a statistical analysis was developed in order to quantify the heterogeneity of surface rates. We show how key components of the rate combine to give an overall rate and how the identification of those individual rate contributors provide mechanistic insight into complex heterogeneous reactions. This generates a paradigm change by proposing a new pathway to reaction model parameterization and for the prediction of reaction rates.

Consolidation of fatigue and fatigue-crack-propagation data for design use

NASA Technical Reports Server (NTRS)

Rice, R. C.; Davies, K. B.; Jaske, C. E.; Feddersen, C. E.

1975-01-01

Analytical methods developed for consolidation of fatigue and fatigue-crack-propagation data for use in design of metallic aerospace structural components are evaluated. A comprehensive file of data on 2024 and 7075 aluminums, Ti-6Al-4V alloy, and 300M steel was established by obtaining information from both published literature and reports furnished by aerospace companies. Analyses are restricted to information obtained from constant-amplitude load or strain cycling of specimens in air at room temperature. Both fatigue and fatigue-crack-propagation data are analyzed on a statistical basis using a least-squares regression approach. For fatigue, an equivalent strain parameter is used to account for mean stress or stress ratio effects and is treated as the independent variable; cyclic fatigue life is considered to be the dependent variable. An effective stress-intensity factor is used to account for the effect of load ratio on fatigue-crack-propagation and treated as the independent variable. In this latter case, crack-growth rate is considered to be the dependent variable. A two term power function is used to relate equivalent strain to fatigue life, and an arc-hyperbolic-tangent function is used to relate effective stress intensity to crack-growth rate.

Evidence Integration in Natural Acoustic Textures during Active and Passive Listening

PubMed Central

Rupp, Andre; Celikel, Tansu

2018-01-01

Abstract Many natural sounds can be well described on a statistical level, for example, wind, rain, or applause. Even though the spectro-temporal profile of these acoustic textures is highly dynamic, changes in their statistics are indicative of relevant changes in the environment. Here, we investigated the neural representation of change detection in natural textures in humans, and specifically addressed whether active task engagement is required for the neural representation of this change in statistics. Subjects listened to natural textures whose spectro-temporal statistics were modified at variable times by a variable amount. Subjects were instructed to either report the detection of changes (active) or to passively listen to the stimuli. A subset of passive subjects had performed the active task before (passive-aware vs passive-naive). Psychophysically, longer exposure to pre-change statistics was correlated with faster reaction times and better discrimination performance. EEG recordings revealed that the build-up rate and size of parieto-occipital (PO) potentials reflected change size and change time. Reduced effects were observed in the passive conditions. While P2 responses were comparable across conditions, slope and height of PO potentials scaled with task involvement. Neural source localization identified a parietal source as the main contributor of change-specific potentials, in addition to more limited contributions from auditory and frontal sources. In summary, the detection of statistical changes in natural acoustic textures is predominantly reflected in parietal locations both on the skull and source level. The scaling in magnitude across different levels of task involvement suggests a context-dependent degree of evidence integration. PMID:29662943

A stochastic fractional dynamics model of space-time variability of rain

NASA Astrophysics Data System (ADS)

Kundu, Prasun K.; Travis, James E.

2013-09-01

varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, which allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and time scales. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and on the Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to fit the second moment statistics of radar data at the smaller spatiotemporal scales. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well at these scales without any further adjustment.

Evidence Integration in Natural Acoustic Textures during Active and Passive Listening.

PubMed

Górska, Urszula; Rupp, Andre; Boubenec, Yves; Celikel, Tansu; Englitz, Bernhard

2018-01-01

Many natural sounds can be well described on a statistical level, for example, wind, rain, or applause. Even though the spectro-temporal profile of these acoustic textures is highly dynamic, changes in their statistics are indicative of relevant changes in the environment. Here, we investigated the neural representation of change detection in natural textures in humans, and specifically addressed whether active task engagement is required for the neural representation of this change in statistics. Subjects listened to natural textures whose spectro-temporal statistics were modified at variable times by a variable amount. Subjects were instructed to either report the detection of changes (active) or to passively listen to the stimuli. A subset of passive subjects had performed the active task before (passive-aware vs passive-naive). Psychophysically, longer exposure to pre-change statistics was correlated with faster reaction times and better discrimination performance. EEG recordings revealed that the build-up rate and size of parieto-occipital (PO) potentials reflected change size and change time. Reduced effects were observed in the passive conditions. While P2 responses were comparable across conditions, slope and height of PO potentials scaled with task involvement. Neural source localization identified a parietal source as the main contributor of change-specific potentials, in addition to more limited contributions from auditory and frontal sources. In summary, the detection of statistical changes in natural acoustic textures is predominantly reflected in parietal locations both on the skull and source level. The scaling in magnitude across different levels of task involvement suggests a context-dependent degree of evidence integration.

Point and interval estimation of pollinator importance: a study using pollination data of Silene caroliniana.

PubMed

Reynolds, Richard J; Fenster, Charles B

2008-05-01

Pollinator importance, the product of visitation rate and pollinator effectiveness, is a descriptive parameter of the ecology and evolution of plant-pollinator interactions. Naturally, sources of its variation should be investigated, but the SE of pollinator importance has never been properly reported. Here, a Monte Carlo simulation study and a result from mathematical statistics on the variance of the product of two random variables are used to estimate the mean and confidence limits of pollinator importance for three visitor species of the wildflower, Silene caroliniana. Both methods provided similar estimates of mean pollinator importance and its interval if the sample size of the visitation and effectiveness datasets were comparatively large. These approaches allowed us to determine that bumblebee importance was significantly greater than clearwing hawkmoth, which was significantly greater than beefly. The methods could be used to statistically quantify temporal and spatial variation in pollinator importance of particular visitor species. The approaches may be extended for estimating the variance of more than two random variables. However, unless the distribution function of the resulting statistic is known, the simulation approach is preferable for calculating the parameter's confidence limits.

Homicides by Police: Comparing Counts From the National Violent Death Reporting System, Vital Statistics, and Supplementary Homicide Reports.

PubMed

Barber, Catherine; Azrael, Deborah; Cohen, Amy; Miller, Matthew; Thymes, Deonza; Wang, David Enze; Hemenway, David

2016-05-01

To evaluate the National Violent Death Reporting System (NVDRS) as a surveillance system for homicides by law enforcement officers. We assessed sensitivity and positive predictive value of the NVDRS "type of death" variable against our study count of homicides by police, which we derived from NVDRS coded and narrative data for states participating in NVDRS 2005 to 2012. We compared state counts of police homicides from NVDRS, Vital Statistics, and Federal Bureau of Investigation Supplementary Homicide Reports. We identified 1552 police homicides in the 16 states. Positive predictive value and sensitivity of the NVDRS "type of death" variable for police homicides were high (98% and 90%, respectively). Counts from Vital Statistics and Supplementary Homicide Reports were 58% and 48%, respectively, of our study total; gaps varied widely by state. The annual rate of police homicide (0.24/100,000) varied 5-fold by state and 8-fold by race/ethnicity. NVDRS provides more complete data on police homicides than do existing systems. Expanding NVDRS to all 50 states and making 2 improvements we identify will be an efficient way to provide the nation with more accurate, detailed data on homicides by law enforcement.

Nonequilibrium thermodynamics in sheared hard-sphere materials.

PubMed

Lieou, Charles K C; Langer, J S

2012-06-01

We combine the shear-transformation-zone (STZ) theory of amorphous plasticity with Edwards' statistical theory of granular materials to describe shear flow in a disordered system of thermalized hard spheres. The equations of motion for this system are developed within a statistical thermodynamic framework analogous to that which has been used in the analysis of molecular glasses. For hard spheres, the system volume V replaces the internal energy U as a function of entropy S in conventional statistical mechanics. In place of the effective temperature, the compactivity X=∂V/∂S characterizes the internal state of disorder. We derive the STZ equations of motion for a granular material accordingly, and predict the strain rate as a function of the ratio of the shear stress to the pressure for different values of a dimensionless, temperature-like variable near a jamming transition. We use a simplified version of our theory to interpret numerical simulations by Haxton, Schmiedeberg, and Liu, and in this way are able to obtain useful insights about internal rate factors and relations between jamming and glass transitions.

A statistical method for the conservative adjustment of false discovery rate (q-value).

PubMed

Lai, Yinglei

2017-03-14

q-value is a widely used statistical method for estimating false discovery rate (FDR), which is a conventional significance measure in the analysis of genome-wide expression data. q-value is a random variable and it may underestimate FDR in practice. An underestimated FDR can lead to unexpected false discoveries in the follow-up validation experiments. This issue has not been well addressed in literature, especially in the situation when the permutation procedure is necessary for p-value calculation. We proposed a statistical method for the conservative adjustment of q-value. In practice, it is usually necessary to calculate p-value by a permutation procedure. This was also considered in our adjustment method. We used simulation data as well as experimental microarray or sequencing data to illustrate the usefulness of our method. The conservativeness of our approach has been mathematically confirmed in this study. We have demonstrated the importance of conservative adjustment of q-value, particularly in the situation that the proportion of differentially expressed genes is small or the overall differential expression signal is weak.

Addiction treatment dropout: exploring patients' characteristics.

PubMed

López-Goñi, José J; Fernández-Montalvo, Javier; Arteaga, Alfonso

2012-01-01

This study explored the characteristics associated with treatment dropout in substance dependence patients. A sample of 122 addicted patients (84 treatment completers and 38 treatment dropouts) who sought outpatient treatment was assessed to collect information on sociodemographic, consumption (assessed by EuropASI), psychopathological (assessed by SCL-90-R), and personality variables (assessed by MCMI-II). Completers and dropouts were compared on all studied variables. According to the results, dropouts scored significantly higher on the EuropASI variables measuring employment/support, alcohol consumption, and family/social problems, as well as on the schizotypal scale of MCMI-II. Because most of the significant differences were found in EuropASI variables, three clusters analyses (2, 3, and 4 groups) based on EuropASI mean scores were carried out to determine clinically relevant information predicting dropout. The most relevant results were obtained when four groups were used. Comparisons between the four groups derived from cluster analysis showed statistically significant differences in the rate of dropout, with one group exhibiting the highest dropout rate. The distinctive characteristics of the group with highest dropout rate included the presence of an increased labor problem combined with high alcohol consumption. Furthermore, this group had the highest scores on three scales of the MCMI-II: phobic, dependent, and schizotypal. The implications of these results for further research and clinical practice are discussed.  Copyright © American Academy of Addiction Psychiatry.

Sensorimotor abilities predict on-field performance in professional baseball.

PubMed

Burris, Kyle; Vittetoe, Kelly; Ramger, Benjamin; Suresh, Sunith; Tokdar, Surya T; Reiter, Jerome P; Appelbaum, L Gregory

2018-01-08

Baseball players must be able to see and react in an instant, yet it is hotly debated whether superior performance is associated with superior sensorimotor abilities. In this study, we compare sensorimotor abilities, measured through 8 psychomotor tasks comprising the Nike Sensory Station assessment battery, and game statistics in a sample of 252 professional baseball players to evaluate the links between sensorimotor skills and on-field performance. For this purpose, we develop a series of Bayesian hierarchical latent variable models enabling us to compare statistics across professional baseball leagues. Within this framework, we find that sensorimotor abilities are significant predictors of on-base percentage, walk rate and strikeout rate, accounting for age, position, and league. We find no such relationship for either slugging percentage or fielder-independent pitching. The pattern of results suggests performance contributions from both visual-sensory and visual-motor abilities and indicates that sensorimotor screenings may be useful for player scouting.

Using scan statistics for congenital anomalies surveillance: the EUROCAT methodology.

PubMed

Teljeur, Conor; Kelly, Alan; Loane, Maria; Densem, James; Dolk, Helen

2015-11-01

Scan statistics have been used extensively to identify temporal clusters of health events. We describe the temporal cluster detection methodology adopted by the EUROCAT (European Surveillance of Congenital Anomalies) monitoring system. Since 2001, EUROCAT has implemented variable window width scan statistic for detecting unusual temporal aggregations of congenital anomaly cases. The scan windows are based on numbers of cases rather than being defined by time. The methodology is imbedded in the EUROCAT Central Database for annual application to centrally held registry data. The methodology was incrementally adapted to improve the utility and to address statistical issues. Simulation exercises were used to determine the power of the methodology to identify periods of raised risk (of 1-18 months). In order to operationalize the scan methodology, a number of adaptations were needed, including: estimating date of conception as unit of time; deciding the maximum length (in time) and recency of clusters of interest; reporting of multiple and overlapping significant clusters; replacing the Monte Carlo simulation with a lookup table to reduce computation time; and placing a threshold on underlying population change and estimating the false positive rate by simulation. Exploration of power found that raised risk periods lasting 1 month are unlikely to be detected except when the relative risk and case counts are high. The variable window width scan statistic is a useful tool for the surveillance of congenital anomalies. Numerous adaptations have improved the utility of the original methodology in the context of temporal cluster detection in congenital anomalies.

The Return of Rate Dependence.

PubMed

Quisenberry, Amanda J; Snider, Sarah E; Bickel, Warren K

2016-11-01

Rate dependence, a well-known phenomenon in behavioral pharmacology, appears to have declined as a topic of interest, perhaps, as a result of being viewed pertinent to only the preclinical investigation of drugs on schedule-controlled performance. Obstacles to data interpretation due to conflation with regression to the mean also appear to have contributed to the topic's decline. Despite this reduction in exposure, rate dependence is a useful concept and tool that can be used to determine sources of variability, predict therapeutic outcomes, and identify individuals that are most likely to respond therapeutically. Armed with new statistical methods and an understanding of the broad range of conditions under which rate dependence can be observed, we urge researchers to revisit the concept, use the appropriate analysis methods, and to design empirical studies a priori to further explore rate dependence.

Heart rate, rate-pressure product, and oxygen uptake during four sexual activities.

PubMed

Bohlen, J G; Held, J P; Sanderson, M O; Patterson, R P

1984-09-01

Heart rate, rate-pressure product, and VO2 were measured in ten healthy men during four specified sexual activities: coitus with husband on top, coitus with wife on top, noncoital stimulation of husband by wife, and self-stimulation by husband. Foreplay generated slight, but statistically significant, increases above resting baseline in cardiac and metabolic variables. From stimulation through orgasm, average effort was modest for relatively short spans. Maximum exercise values occurred during the brief spans of orgasm, then returned quickly to near baseline levels. The two noncoital activities required lower expenditures than the two coital positions, with man-on-top coitus rating the highest. Large variations among subjects and among activities discourage use of a general equivalent activity for comparison, such as "two flights of stairs," to represent "sexual activity."

Appending Limited Clinical Data to an Administrative Database for Acute Myocardial Infarction Patients: The Impact on the Assessment of Hospital Quality.

PubMed

Hannan, Edward L; Samadashvili, Zaza; Cozzens, Kimberly; Jacobs, Alice K; Venditti, Ferdinand J; Holmes, David R; Berger, Peter B; Stamato, Nicholas J; Hughes, Suzanne; Walford, Gary

2016-05-01

Hospitals' risk-standardized mortality rates and outlier status (significantly higher/lower rates) are reported by the Centers for Medicare and Medicaid Services (CMS) for acute myocardial infarction (AMI) patients using Medicare claims data. New York now has AMI claims data with blood pressure and heart rate added. The objective of this study was to see whether the appended database yields different hospital assessments than standard claims data. New York State clinically appended claims data for AMI were used to create 2 different risk models based on CMS methods: 1 with and 1 without the added clinical data. Model discrimination was compared, and differences between the models in hospital outlier status and tertile status were examined. Mean arterial pressure and heart rate were both significant predictors of mortality in the clinically appended model. The C statistic for the model with the clinical variables added was significantly higher (0.803 vs. 0.773, P<0.001). The model without clinical variables identified 10 low outliers and all of them were percutaneous coronary intervention hospitals. When clinical variables were included in the model, only 6 of those 10 hospitals were low outliers, but there were 2 new low outliers. The model without clinical variables had only 3 high outliers, and the model with clinical variables included identified 2 new high outliers. Appending even a small number of clinical data elements to administrative data resulted in a difference in the assessment of hospital mortality outliers for AMI. The strategy of adding limited but important clinical data elements to administrative datasets should be considered when evaluating hospital quality for procedures and other medical conditions.

Regional differences of standardised mortality rates for ischemic heart diseases in the Slovak Republic for the period 1996-2013 in the context of income inequality.

PubMed

Gavurová, Beáta; Vagašová, Tatiana

2016-12-01

The aim of paper is to analyse the development of standardised mortality rates for ischemic heart diseases in relation to the income inequality in the regions of Slovakia. This paper assesses different types of income indicators, such as mean equivalised net income per household, Gini coefficient, unemployment rate, at risk of poverty threshold (60 % of national median), S80/S20 and their effect on mortality. Using data from the Slovak mortality database 1996-2013, the method of direct standardisation was applied to eliminate variances resulted from differences in age structures of the population across regions and over time. To examine the relationships between income indicators and standardised mortality rates, we used the tools of descriptive statistics and methods of correlation and regression analysis. At first, we show that Slovakia has the worst values of standardised mortality rates for ischemic heart diseases in EU countries. Secondly, mortality rates are significantly higher for males compared with females. Thirdly, mortality rates are improving from Eastern Slovakia to Western Slovakia; additionally, high differences in the results of variability are seen among Slovak regions. Finally, the unemployment rate, the poverty rate and equivalent disposable income were statistically significant income indicators. Main contribution of paper is to demonstrate regional differences between mortality and income inequality, and to point out the long-term unsatisfactory health outcomes.

A Study of Persistence in the Northeast State Community College Health-Related Programs of Study

NASA Astrophysics Data System (ADS)

Hamilton, Allana R.

2011-12-01

The purpose of the study was to identify factors that were positively associated with persistence to graduation by students who were admitted to Health-Related Programs leading to the degree associate of applied science at Northeast State Community College. The criterion variable in this study was persistence, which was categorized into two groups the persister group (program completers) and the nonpersister (program noncompleters) group. The predictor variables included gender, ethnic origin, first- (or nonfirst-) generation-student status, age, specific major program of study, number of remedial and/or developmental courses taken, grades in selected courses (human anatomy and physiology I and II, microbiology, probability and statistics, composition I, clinical I, clinical II), and number of mathematics and science credit hours earned prior to program admission. The data for this ex post facto nonexperimental design were located in Northeast State's student records database, Banner Information System. The subjects of the study were students who had been admitted into Health-Related Programs of study at a 2-year public community college between the years of 1999 and 2008. The population size was 761. Health-Related Programs of study included Dental Assisting, Cardiovascular Technology, Emergency Medical Technology -- Paramedic, Medical Laboratory Technology, Nursing, and Surgical Technology. A combination of descriptive and inferential statistics was used in the analysis of the data. Descriptive statistics included measures of central tendency, standard deviations, and percentages, as appropriate. Independent samples t-tests were used to determine if the mean of a variable on one group of subjects was different from the mean of the same variable with a different group of subjects. It was found that gender, ethnic origin, first-generation status, and age were not significantly associated with persistence to graduation. However, findings did reveal a statistically significant difference in persistence rates among the specific Health-Related Programs of study. Academic data including grades in human anatomy and physiology I, probability and statistics, and composition I, suggested a relationship between the course grade and persistence to graduation. Findings also revealed a relationship between the number of math and science courses completed and students' persistence to graduation.

Prevalence of hepatitis-C virus genotypes and potential transmission risks in Malakand Khyber Pakhtunkhwa, Pakistan.

PubMed

Nazir, Nausheen; Jan, Muhammad Rasul; Ali, Amjad; Asif, Muhammad; Idrees, Muhammad; Nisar, Mohammad; Zahoor, Muhammad; Abd El-Salam, Naser M

2017-08-22

Hepatitis C virus (HCV) is a leading cause of chronic liver disease and frequently progresses towards liver cirrhosis and Hepatocellular Carcinoma (HCC). This study aimed to determine the prevalence of HCV genotypes and their association with possible transmission risks in the general population of Malakand Division. Sum of 570 serum samples were collected during March 2011 to January 2012 from suspected patients visited to different hospitals of Malakand. The suspected sera were tested using qualitative PCR and were then subjected to molecular genotype specific assay. Quantitative PCR was also performed for determination of pre-treatment viral load in confirmed positive patients. Out of 570 serum samples 316 sera were seen positive while 254 sera were found negative using qualitative PCR. The positive samples were then subjected to genotyping assay out of 316, type-specific PCR fragments were seen in 271 sera while 45 samples were found untypable genotypes. Genotype 3a was seen as a predominant genotype (63.3%) with a standard error of ±2.7%. Cramer's V statistic and Liklihood-Ratio statistical procedures are used to measure the strength and to test the association, respectively, between the dependent variable, genotype, and explanatory variables (e.g. gender, risk, age and area/districts). The dependent variable, genotype, is observed statistically significant association with variable risk factors. This implies that the genotype is highly dependent on how the patient was infected. In contrast, the other covariates, for example, gender, age, and district (area) no statistical significant association are observed. The association between gender-age indicates that the mean age of female was older by 10.5 ± 2.3 years with 95% confidence level using t-statistic. It was concluded from the present study that the predominant genotype was 3a in the infected population of Malakand. This study also highlights the high prevalence rate of untypable genotypes which an important issue of health care setup in Malakand and create complications in therapy of infected patients. Major mode of HCV transmission is multiple uses and re-uses of needles/injections. ISRCTN ISRCTN73824458. Registered: 28 September 2014.

Heart rate variability changes during stroop color and word test among genders.

PubMed

Satish, Priyanka; Muralikrishnan, Krishnan; Balasubramanian, Kabali; Shanmugapriya

2015-01-01

Stress is the reaction of the body to a change that requires physical, mental or emotional adjustments. Individual differences in stress reactivity are a potentially important risk factor for gender-specific health problems in men and women. The Autonomic regulation of the cardiovascular system is most commonly affected by stress and is assessed by means of short term heart rate variability (HRV).The present study was undertaken to investigate the difference in the cardiovascular Autonomic Nervous System response to mental stress between the genders using HRV as tool. We compared the mean RR interval, Blood pressure and indices of HRV during the StroopColor Word Test (SCWT).Twenty five male (Age 19.52±0.714, BMI 22.73±2 kg/m2) and twenty five female subjects (Age 19.80±0.65, BMI 22.39±1.9) performed SCWT for five minutes. Blood Pressure (SBP p<0.01, DBP p<0.042) & Mean HR (p<0.010) values showed statistically significant difference among the genders. HRV indices like LFms2 (p<0.051), HF nu (p<0.029) and LF/HF ratio (p<0.025, p<0.052) show statistically significant difference among the genders. The response by the cardiovascular system to a simple mental stressor exhibits difference among the genders.

Remote sensing and implications for variable-rate application using agricultural aircraft

NASA Astrophysics Data System (ADS)

Thomson, Steven J.; Smith, Lowrey A.; Ray, Jeffrey D.; Zimba, Paul V.

2004-01-01

Aircraft routinely used for agricultural spray application are finding utility for remote sensing. Data obtained from remote sensing can be used for prescription application of pesticides, fertilizers, cotton growth regulators, and water (the latter with the assistance of hyperspectral indices and thermal imaging). Digital video was used to detect weeds in early cotton, and preliminary data were obtained to see if nitrogen status could be detected in early soybeans. Weeds were differentiable from early cotton at very low altitudes (65-m), with the aid of supervised classification algorithms in the ENVI image analysis software. The camera was flown at very low altitude for acceptable pixel resolution. Nitrogen status was not detectable by statistical analysis of digital numbers (DNs) obtained from images, but soybean cultivar differences were statistically discernable (F=26, p=0.01). Spectroradiometer data are being analyzed to identify narrow spectral bands that might aid in selecting camera filters for determination of plant nitrogen status. Multiple camera configurations are proposed to allow vegetative indices to be developed more readily. Both remotely sensed field images and ground data are to be used for decision-making in a proposed variable-rate application system for agricultural aircraft. For this system, prescriptions generated from digital imagery and data will be coupled with GPS-based swath guidance and programmable flow control.

Kinesio Taping effects on knee extension force among soccer players

PubMed Central

Serra, Maysa V. G. B.; Vieira, Edgar R.; Brunt, Denis; Goethel, Márcio F.; Gonçalves, Mauro; Quemelo, Paulo R. V.

2015-01-01

Background: Kinesio Taping (KT) is widely used, however the effects of KT on muscle activation and force are contradictory. Objective: To evaluate the effects of KT on knee extension force in soccer players. Method: This is a clinical trial study design. Thirty-four subjects performed two maximal isometric voluntary contractions of the lower limbs pre, immediately post, and 24 hours after tape application on the lower limbs. Both lower limbs were taped, using K-Tape and 3M Micropore tape randomly on the right and left thighs of the participants. Isometric knee extension force was measured for dominant side using a strain gauge. The following variables were assessed: peak force, time to peak force, rate of force development until peak force, time to peak rate of force development, and 200 ms pulse. Results: There were no statistically significant differences in the variables assessed between KT and Micropore conditions (F=0.645, p=0.666) or among testing sessions (pre, post, and 24h after) (F=0.528, p=0.868), and there was no statistical significance (F=0.271, p=0.986) for interaction between tape conditions and testing session. Conclusion: KT did not affect the force-related measures assessed immediately and 24 hours after the KT application compared with Micropore application, during maximal isometric voluntary knee extension. PMID:25789557

Kinesio Taping effects on knee extension force among soccer players.

PubMed

Serra, Maysa V G B; Vieira, Edgar R; Brunt, Denis; Goethel, Márcio F; Gonçalves, Mauro; Quemelo, Paulo R V

2015-01-01

Kinesio Taping (KT) is widely used, however the effects of KT on muscle activation and force are contradictory. To evaluate the effects of KT on knee extension force in soccer players. This is a clinical trial study design. Thirty-four subjects performed two maximal isometric voluntary contractions of the lower limbs pre, immediately post, and 24 hours after tape application on the lower limbs. Both lower limbs were taped, using K-Tape and 3M Micropore tape randomly on the right and left thighs of the participants. Isometric knee extension force was measured for dominant side using a strain gauge. The following variables were assessed: peak force, time to peak force, rate of force development until peak force, time to peak rate of force development, and 200 ms pulse. There were no statistically significant differences in the variables assessed between KT and Micropore conditions (F=0.645, p=0.666) or among testing sessions (pre, post, and 24h after) (F=0.528, p=0.868), and there was no statistical significance (F=0.271, p=0.986) for interaction between tape conditions and testing session. KT did not affect the force-related measures assessed immediately and 24 hours after the KT application compared with Micropore application, during maximal isometric voluntary knee extension.

Factors Influencing Watershed Average Erosion Rates Calculated from Reservoir Sedimentation in Eastern USA

NASA Astrophysics Data System (ADS)

Ahamed, A.; Snyder, N. P.; David, G. C.

2014-12-01

The Reservoir Sedimentation Database (ResSed), a catalogue of reservoirs and depositional data that has recently become publically available, allows for rapid calculation of sedimentation rates and rates of capacity loss over short (annual to decadal) timescales. This study is a statistical investigation of factors controlling watershed average erosion rates (E) in eastern United States watersheds. We develop an ArcGIS-based model that delineates watersheds upstream of ResSed dams and calculate drainage areas to determine E for 191 eastern US watersheds. Geomorphic, geologic, regional, climatic, and land use variables are quantified within study watersheds using GIS. Erosion rates exhibit a large amount of scatter, ranging from 0.001 to 1.25 mm/yr. A weak inverse power law relationship between drainage area (A) and E (R2 = 0.09) is evident, similar to other studies (e.g. Milliman and Syvitski, 1992; Koppes and Montgomery, 2009). Linear regressions reveal no relationship between mean watershed slope (S) and E, possibly due to the relatively low relief of the region (mean S for all watersheds is 6°). Analysis of Variance shows that watersheds in formerly glaciated regions exhibit a statistically significant lower mean E (0.06 mm/year) than watersheds in unglaciated regions (0.12 mm/year), but that watersheds with different dam purposes show no significant differences in mean E. Linear regressions reveal no relationships between E and land use parameters like percent agricultural land and percent impervious surfaces (I), but classification and regression trees indicate that watersheds in highly developed regions (I > 34%) exhibit mean E (0.36 mm/year) that is four times higher than watersheds in less developed (I < 34%) regions (0.09 mm/year). Further, interactions between land use variables emerge in formerly glaciated regions, where increased agricultural land results in higher rates of annual capacity loss in reservoirs (R2 = 0.56). Plots of E versus timescale of measurement (e.g., Sadler and Jerolmack, 2014) show that nearly the full range of observed E, including the highest values, are seen over short survey intervals (< 20 years), suggesting that whether or not large sedimentation events (such as floods) occur between two surveys may explain the high degree of variability in measured rates.

The Effect of Community Uninsurance Rates on Access to Health Care

PubMed Central

Sabik, Lindsay M

2012-01-01

Objective To investigate the effect of local uninsurance rates on access to health care for the uninsured and insured and improve on recent studies by controlling for time-invariant differences across markets. Data Sources Individual-level data from the 1996 and 2003 Community Tracking Study, and market-level data from other sources, including the Area Resource File and the Bureau of Primary Healthcare. Study Design Market-level fixed effects models estimate the effect of changes in uninsurance rates within markets on access to care, measured by whether individuals report forgoing necessary care. Instrumental variables models are also estimated. Principal Findings Increases in the rate of uninsurance are associated with poorer access to necessary care among the uninsured. In contrast with recent evidence, increases in uninsurance had no effect on access to care among the insured. Instrumental variables results are similar, although not statistically significant. Conclusions Changes in rates of insurance coverage are likely to affect access to care for both previously and continuously uninsured. In contrast with earlier studies, there is no evidence of spillover effects on the insured, suggesting that such policy changes may have little effect on access for those who are already insured. PMID:22172046

Managing fish habitat for flow and temperature extremes ...

EPA Pesticide Factsheets

Summer low flows and stream temperature maxima are key drivers affecting the sustainability of fish populations. Thus, it is critical to understand both the natural templates of spatiotemporal variability, how these are shifting due to anthropogenic influences of development and climate change, and how these impacts can be moderated by natural and constructed green infrastructure. Low flow statistics of New England streams have been characterized using a combination of regression equations to describe long-term averages as a function of indicators of hydrologic regime (rain- versus snow-dominated), precipitation, evapotranspiration or temperature, surface water storage, baseflow recession rates, and impervious cover. Difference equations have been constructed to describe interannual variation in low flow as a function of changing air temperature, precipitation, and ocean-atmospheric teleconnection indices. Spatial statistical network models have been applied to explore fine-scale variability of thermal regimes along stream networks in New England as a function of variables describing natural and altered energy inputs, groundwater contributions, and retention time. Low flows exacerbate temperature impacts by reducing thermal inertia of streams to energy inputs. Based on these models, we can construct scenarios of fish habitat suitability using current and projected future climate and the potential for preservation and restoration of historic habitat regimes th

Relating N2O emissions during biological nitrogen removal with operating conditions using multivariate statistical techniques.

PubMed

Vasilaki, V; Volcke, E I P; Nandi, A K; van Loosdrecht, M C M; Katsou, E

2018-04-26

Multivariate statistical analysis was applied to investigate the dependencies and underlying patterns between N 2 O emissions and online operational variables (dissolved oxygen and nitrogen component concentrations, temperature and influent flow-rate) during biological nitrogen removal from wastewater. The system under study was a full-scale reactor, for which hourly sensor data were available. The 15-month long monitoring campaign was divided into 10 sub-periods based on the profile of N 2 O emissions, using Binary Segmentation. The dependencies between operating variables and N 2 O emissions fluctuated according to Spearman's rank correlation. The correlation between N 2 O emissions and nitrite concentrations ranged between 0.51 and 0.78. Correlation >0.7 between N 2 O emissions and nitrate concentrations was observed at sub-periods with average temperature lower than 12 °C. Hierarchical k-means clustering and principal component analysis linked N 2 O emission peaks with precipitation events and ammonium concentrations higher than 2 mg/L, especially in sub-periods characterized by low N 2 O fluxes. Additionally, the highest ranges of measured N 2 O fluxes belonged to clusters corresponding with NO 3 -N concentration less than 1 mg/L in the upstream plug-flow reactor (middle of oxic zone), indicating slow nitrification rates. The results showed that the range of N 2 O emissions partially depends on the prior behavior of the system. The principal component analysis validated the findings from the clustering analysis and showed that ammonium, nitrate, nitrite and temperature explained a considerable percentage of the variance in the system for the majority of the sub-periods. The applied statistical methods, linked the different ranges of emissions with the system variables, provided insights on the effect of operating conditions on N 2 O emissions in each sub-period and can be integrated into N 2 O emissions data processing at wastewater treatment plants. Copyright © 2018. Published by Elsevier Ltd.

The Relationship between Resettlement and Birth Rates: The Case of Gambella, Ethiopia.

PubMed

Adugna, Aynalem; Kloos, Helmut

2016-07-01

This study aims to examine the possible impacts of resettlement on birth rates by using the length of stay variable in the 2000 Demographic and Health Survey (DHS). Data in all three rounds of Gambella Administrative Region's Demographic and Health Surveys (DHS) are analyzed. The neighboring administrative region of Benishangul-Gumuz is used as a control. The multivariate analysis of variance (MANOVA) is applied with duration of residence as a categorical independent variable. The statistical software SAS is used. In a univariate analysis of Gambella's DHS 2000, duration of residence has a significant effect on mothers' age at first birth (p < 0.001), the number of children born within the five years of the survey (p<0.001), and the total number of children ever born (P<0.001). In the MANOVA analysis, the duration effect on all three is also statistically significant (p<0.001). Resettlement had a disruptive effect on birth rates among females who were just coming into marriageable ages in places of origin but were resettled to Gambella. Although the disruptive effects waned over time, the initial shortfall resulted in reduced overall lifetime births for settler women who were not past the midpoint of their reproductive years at arrival. Based on the reproductive history of female settlers with different duration of residence in the resettlement schemes, we recommend the reinstatement of the length of residence question in future DHS surveys in Ethiopia to allow a longitudinal tracking of demographic trends among nonnative populations.

Economic crisis and suicides in Spain. Socio-demographic and regional variability.

PubMed

Isabel, Ruiz-Perez; Miguel, Rodriguez-Barranco; Antonio, Rojas-Garcia; Oscar, Mendoza-Garcia

2017-04-01

Evidence from previous recessions suggests that at times of economic deterioration, suicides increase. Spain has been one of the European countries hardest hit by the financial crisis that started in 2008. The aim of this paper is to examine the impact of the double-dip recession in Spain on the most recent trends in suicide. Suicide data from the years 2002-2012 were obtained from the 'Death Statistic according to Cause of Death' of the National Statistics Institute (NSI). Population figures were obtained from the population estimates of the NSI. While the suicide rate decreased between 2002 and 2012, the downward trend has reversed twice, in 2008-2009, and in 2012. This rise was particularly pronounced in males, with the rate ratio of 1.12 (95 % CI 1.05-1.20) in 2008 and 1.10 (95 % CI 1.03-1.18) in 2009. Following a decrease in 2010 and 2011, suicides among males have increased again in 2012-with RR of 1.10 (95 % CI 1.03-1.18) compared to 2007, however the difference between 2011 amounted to 14 % rise-the biggest interannual change in a decade. There was a similar but less pronounced pattern in females. Regional data showed variable results. These results suggest that the Spanish economic crisis has been associated with suicide rates in 2008, 2009, and 2012. These findings are consistent with the double-dip recession that Spain experienced.

Towards an automatic statistical model for seasonal precipitation prediction and its application to Central and South Asian headwater catchments

NASA Astrophysics Data System (ADS)

Gerlitz, Lars; Gafurov, Abror; Apel, Heiko; Unger-Sayesteh, Katy; Vorogushyn, Sergiy; Merz, Bruno

2016-04-01

Statistical climate forecast applications typically utilize a small set of large scale SST or climate indices, such as ENSO, PDO or AMO as predictor variables. If the predictive skill of these large scale modes is insufficient, specific predictor variables such as customized SST patterns are frequently included. Hence statistically based climate forecast models are either based on a fixed number of climate indices (and thus might not consider important predictor variables) or are highly site specific and barely transferable to other regions. With the aim of developing an operational seasonal forecast model, which is easily transferable to any region in the world, we present a generic data mining approach which automatically selects potential predictors from gridded SST observations and reanalysis derived large scale atmospheric circulation patterns and generates robust statistical relationships with posterior precipitation anomalies for user selected target regions. Potential predictor variables are derived by means of a cellwise correlation analysis of precipitation anomalies with gridded global climate variables under consideration of varying lead times. Significantly correlated grid cells are subsequently aggregated to predictor regions by means of a variability based cluster analysis. Finally for every month and lead time, an individual random forest based forecast model is automatically calibrated and evaluated by means of the preliminary generated predictor variables. The model is exemplarily applied and evaluated for selected headwater catchments in Central and South Asia. Particularly the for winter and spring precipitation (which is associated with westerly disturbances in the entire target domain) the model shows solid results with correlation coefficients up to 0.7, although the variability of precipitation rates is highly underestimated. Likewise for the monsoonal precipitation amounts in the South Asian target areas a certain skill of the model could be detected. The skill of the model for the dry summer season in Central Asia and the transition seasons over South Asia is found to be low. A sensitivity analysis by means on well known climate indices reveals the major large scale controlling mechanisms for the seasonal precipitation climate of each target area. For the Central Asian target areas, both, the El Nino Southern Oscillation and the North Atlantic Oscillation are identified as important controlling factors for precipitation totals during moist spring season. Drought conditions are found to be triggered by a warm ENSO phase in combination with a positive phase of the NAO. For the monsoonal summer precipitation amounts over Southern Asia, the model suggests a distinct negative response to El Nino events.

Individual and social determinants of multiple chronic disease behavioral risk factors among youth.

PubMed

Alamian, Arsham; Paradis, Gilles

2012-03-22

Behavioral risk factors are known to co-occur among youth, and to increase risks of chronic diseases morbidity and mortality later in life. However, little is known about determinants of multiple chronic disease behavioral risk factors, particularly among youth. Previous studies have been cross-sectional and carried out without a sound theoretical framework. Using longitudinal data (n = 1135) from Cycle 4 (2000-2001), Cycle 5 (2002-2003) and Cycle 6 (2004-2005) of the National Longitudinal Survey of Children and Youth, a nationally representative sample of Canadian children who are followed biennially, the present study examines the influence of a set of conceptually-related individual/social distal variables (variables situated at an intermediate distance from behaviors), and individual/social ultimate variables (variables situated at an utmost distance from behaviors) on the rate of occurrence of multiple behavioral risk factors (physical inactivity, sedentary behavior, tobacco smoking, alcohol drinking, and high body mass index) in a sample of children aged 10-11 years at baseline. Multiple behavioral risk factors were assessed using a multiple risk factor score. All statistical analyses were performed using SAS, version 9.1, and SUDAAN, version 9.01. Multivariate longitudinal Poisson models showed that social distal variables including parental/peer smoking and peer drinking (Log-likelihood ratio (LLR) = 187.86, degrees of freedom (DF) = 8, p < .001), as well as individual distal variables including low self-esteem (LLR = 76.94, DF = 4, p < .001) increased the rate of occurrence of multiple behavioral risk factors. Individual ultimate variables including age, sex, and anxiety (LLR = 9.34, DF = 3, p < .05), as well as social ultimate variables including family socioeconomic status, and family structure (LLR = 10.93, DF = 5, p = .05) contributed minimally to the rate of co-occurrence of behavioral risk factors. The results suggest targeting individual/social distal variables in prevention programs of multiple chronic disease behavioral risk factors among youth.

The Impact of Soil Sampling Errors on Variable Rate Fertilization

DOE Office of Scientific and Technical Information (OSTI.GOV)

R. L. Hoskinson; R C. Rope; L G. Blackwood

2004-07-01

Variable rate fertilization of an agricultural field is done taking into account spatial variability in the soil’s characteristics. Most often, spatial variability in the soil’s fertility is the primary characteristic used to determine the differences in fertilizers applied from one point to the next. For several years the Idaho National Engineering and Environmental Laboratory (INEEL) has been developing a Decision Support System for Agriculture (DSS4Ag) to determine the economically optimum recipe of various fertilizers to apply at each site in a field, based on existing soil fertility at the site, predicted yield of the crop that would result (and amore » predicted harvest-time market price), and the current costs and compositions of the fertilizers to be applied. Typically, soil is sampled at selected points within a field, the soil samples are analyzed in a lab, and the lab-measured soil fertility of the point samples is used for spatial interpolation, in some statistical manner, to determine the soil fertility at all other points in the field. Then a decision tool determines the fertilizers to apply at each point. Our research was conducted to measure the impact on the variable rate fertilization recipe caused by variability in the measurement of the soil’s fertility at the sampling points. The variability could be laboratory analytical errors or errors from variation in the sample collection method. The results show that for many of the fertility parameters, laboratory measurement error variance exceeds the estimated variability of the fertility measure across grid locations. These errors resulted in DSS4Ag fertilizer recipe recommended application rates that differed by up to 138 pounds of urea per acre, with half the field differing by more than 57 pounds of urea per acre. For potash the difference in application rate was up to 895 pounds per acre and over half the field differed by more than 242 pounds of potash per acre. Urea and potash differences accounted for almost 87% of the cost difference. The sum of these differences could result in a $34 per acre cost difference for the fertilization. Because of these differences, better analysis or better sampling methods may need to be done, or more samples collected, to ensure that the soil measurements are truly representative of the field’s spatial variability.« less

Comparing a single case to a control group - Applying linear mixed effects models to repeated measures data.

PubMed

Huber, Stefan; Klein, Elise; Moeller, Korbinian; Willmes, Klaus

2015-10-01

In neuropsychological research, single-cases are often compared with a small control sample. Crawford and colleagues developed inferential methods (i.e., the modified t-test) for such a research design. In the present article, we suggest an extension of the methods of Crawford and colleagues employing linear mixed models (LMM). We first show that a t-test for the significance of a dummy coded predictor variable in a linear regression is equivalent to the modified t-test of Crawford and colleagues. As an extension to this idea, we then generalized the modified t-test to repeated measures data by using LMMs to compare the performance difference in two conditions observed in a single participant to that of a small control group. The performance of LMMs regarding Type I error rates and statistical power were tested based on Monte-Carlo simulations. We found that starting with about 15-20 participants in the control sample Type I error rates were close to the nominal Type I error rate using the Satterthwaite approximation for the degrees of freedom. Moreover, statistical power was acceptable. Therefore, we conclude that LMMs can be applied successfully to statistically evaluate performance differences between a single-case and a control sample. Copyright © 2015 Elsevier Ltd. All rights reserved.

Adaptive variable-length coding for efficient compression of spacecraft television data.

NASA Technical Reports Server (NTRS)

Rice, R. F.; Plaunt, J. R.

1971-01-01

An adaptive variable length coding system is presented. Although developed primarily for the proposed Grand Tour missions, many features of this system clearly indicate a much wider applicability. Using sample to sample prediction, the coding system produces output rates within 0.25 bit/picture element (pixel) of the one-dimensional difference entropy for entropy values ranging from 0 to 8 bit/pixel. This is accomplished without the necessity of storing any code words. Performance improvements of 0.5 bit/pixel can be simply achieved by utilizing previous line correlation. A Basic Compressor, using concatenated codes, adapts to rapid changes in source statistics by automatically selecting one of three codes to use for each block of 21 pixels. The system adapts to less frequent, but more dramatic, changes in source statistics by adjusting the mode in which the Basic Compressor operates on a line-to-line basis. Furthermore, the compression system is independent of the quantization requirements of the pulse-code modulation system.

Estimation of Cell Proliferation Dynamics Using CFSE Data

PubMed Central

Banks, H.T.; Sutton, Karyn L.; Thompson, W. Clayton; Bocharov, Gennady; Roose, Dirk; Schenkel, Tim; Meyerhans, Andreas

2010-01-01

Advances in fluorescent labeling of cells as measured by flow cytometry have allowed for quantitative studies of proliferating populations of cells. The investigations (Luzyanina et al. in J. Math. Biol. 54:57–89, 2007; J. Math. Biol., 2009; Theor. Biol. Med. Model. 4:1–26, 2007) contain a mathematical model with fluorescence intensity as a structure variable to describe the evolution in time of proliferating cells labeled by carboxyfluorescein succinimidyl ester (CFSE). Here, this model and several extensions/modifications are discussed. Suggestions for improvements are presented and analyzed with respect to statistical significance for better agreement between model solutions and experimental data. These investigations suggest that the new decay/label loss and time dependent effective proliferation and death rates do indeed provide improved fits of the model to data. Statistical models for the observed variability/noise in the data are discussed with implications for uncertainty quantification. The resulting new cell dynamics model should prove useful in proliferation assay tracking and modeling, with numerous applications in the biomedical sciences. PMID:20195910

A Selective Overview of Variable Selection in High Dimensional Feature Space

PubMed Central

Fan, Jianqing

2010-01-01

High dimensional statistical problems arise from diverse fields of scientific research and technological development. Variable selection plays a pivotal role in contemporary statistical learning and scientific discoveries. The traditional idea of best subset selection methods, which can be regarded as a specific form of penalized likelihood, is computationally too expensive for many modern statistical applications. Other forms of penalized likelihood methods have been successfully developed over the last decade to cope with high dimensionality. They have been widely applied for simultaneously selecting important variables and estimating their effects in high dimensional statistical inference. In this article, we present a brief account of the recent developments of theory, methods, and implementations for high dimensional variable selection. What limits of the dimensionality such methods can handle, what the role of penalty functions is, and what the statistical properties are rapidly drive the advances of the field. The properties of non-concave penalized likelihood and its roles in high dimensional statistical modeling are emphasized. We also review some recent advances in ultra-high dimensional variable selection, with emphasis on independence screening and two-scale methods. PMID:21572976

Nonlinear heart rate variability measures under electromagnetic fields produced by GSM cellular phones.

PubMed

Parazzini, Marta; Ravazzani, Paolo; Thuroczy, György; Molnar, Ferenc B; Ardesi, Gianluca; Sacchettini, Alessio; Mainardi, Luca Tommaso

2013-06-01

This study was designed to assess the nonlinear dynamics of heart rate variability (HRV) during exposure to low-intensity EMFs. Twenty-six healthy young volunteers were subjected to a rest-to-stand protocol to evaluate autonomic nervous system in quiet condition (rest, vagal prevalence) and after a sympathetic activation (stand). The procedure was conducted twice in a double-blind design: once with a genuine EMFs exposure (GSM cellular phone at 900 MHz, 2 W) and once with a sham exposure (at least 24 h apart). During each session, three-lead electrocardiograms were recorded and RR series extracted off-line. The RR series were analyzed by nonlinear deterministic techniques in every phase of the protocol and during the different exposures. The analysis of the data shows there was no statistically significant effect due to GSM exposure on the nonlinear dynamics of HRV.

The late Holocene kauri chronology: assessing the potential of a 4500-year record for palaeoclimate reconstruction

NASA Astrophysics Data System (ADS)

Boswijk, G.; Fowler, A. M.; Palmer, J. G.; Fenwick, P.; Hogg, A.; Lorrey, A.; Wunder, J.

2014-04-01

Millennial and multi-millennial tree-ring chronologies can provide useful proxy records of past climate, giving insight into a more complete range of natural climate variability prior to the 20th century. Since the 1980s a multi-millennial tree-ring chronology has been developed from kauri (Agathis australis) from the upper North Island, New Zealand. Previous work has demonstrated the sensitivity of kauri to the El Niño-Southern Oscillation (ENSO). Here we present recent additions and extensions to the late Holocene kauri chronology (LHKC), and assess the potential of a composite master chronology, AGAUc13, for palaeoclimate reconstruction. The updated composite kauri chronology now spans 4491 years (2488 BCE-2002 CE) and includes data from 18 modern sites, 25 archaeological sites, and 18 sub-fossil (swamp) kauri sites. Consideration of the composition and statistical quality of AGAUc13 suggests the LHKC has utility for palaeoclimate reconstruction but there are caveats. These include: (a) differences in character between the three assemblages including growth rate and sensitivity; (b) low sample depth and low statistical quality in the 10th-13th century CE, when the record transitions from modern and archaeological material to the swamp kauri; (c) a potential difference in amplitude of the signal in the swamp kauri; (d) a westerly bias in site distribution prior to 911 CE; (e) variable statistical quality across the entire record associated with variable replication; and (f) complex changes in sample depth and tree age and size which may influence centennial scale trends in the data. Further tree ring data are required to improve statistical quality, particularly in the first half of the second millennium CE.

Does body fat percentage predict post-exercise heart rate response in non-obese children and adolescents?

PubMed

Jezdimirovic, Tatjana; Stajer, Valdemar; Semeredi, Sasa; Calleja-Gonzalez, Julio; Ostojic, Sergej M

2017-05-24

A correlation between adiposity and post-exercise autonomic regulation has been established in overweight and obese children. However, little information exists about this link in non-obese youth. The main purpose of this cross-sectional study was to describe the relationship between body fat percentage (BFP) and heart rate recovery after exercise [post-exercise heart rate (PEHR)], a marker of autonomic regulation, in normal-weight children and adolescents. We evaluated the body composition of 183 children and adolescents (age 15.0±2.3 years; 132 boys and 51 girls) who performed a maximal graded exercise test on a treadmill, with the heart rate monitored during and immediately after exercise. A strong positive trend was observed in the association between BFP and PEHR (r=0.14; p=0.06). Hierarchical multiple regression revealed that our model explained 18.3% of the variance in PEHR (p=0.00), yet BFP accounted for only 0.9% of the variability in PEHR (p=0.16). The evaluation of the contribution of each independent variable revealed that only two variables made a unique statistically significant contribution to our model (p<0.01), with age contributing 38.7% to our model (p=0.00) while gender accounted for an additional 25.5% (p=0.01). Neither BFP (14.4%; p=0.16) nor cardiorespiratory endurance (5.0%, p=0.60) made a significant unique contribution to the model. Body fatness seems to poorly predict PEHR in our sample of non-obese children and adolescents, while non-modifiable variables (age and gender) were demonstrated as strong predictors of heart rate recovery. The low amount of body fat reported in non-obese young participants was perhaps too small to cause disturbances in autonomic nervous system regulation.

Influence of continuous haemofiltration-related hypothermia on haemodynamic variables and gas exchange in septic patients.

PubMed

Matamis, D; Tsagourias, M; Koletsos, K; Riggos, D; Mavromatidis, K; Sombolos, K; Bursztein, S

1994-07-01

To investigate the influence of continuous haemofiltration (CHF) on haemodynamics, gas exchange and core temperature in critically ill septic patients with acute renal failure. In 20 patients (17 male, 3 female) ultrafiltration rate, core temperature, gas exchange and haemodynamic variables were measured at regular intervals during the first 48 h of haemofiltration. Baseline data were compared to those obtained 30 min after initiating CHF and also to those during hypothermia (if observed). Haemodynamic variables remained remarkably constant throughout the study period. In patients with a relatively low ultrafiltration rate (855 +/- 278 ml/h) temperature did not change, while in patients with a high ultrafiltration rate (1468 +/- 293 ml/h) core temperature significantly decreased from 37.6 +/- 0.9 degrees C to 34.8 +/- 0.8 degrees C (p < 0.001). There was a statistically significant correlation between temperature decrease and ultrafiltration rate (r = -0.68, Y = 1.8-0.003 X, p < 0.01). Hypothermic patients also showed a mean decrease in VO2 from 141 +/- 22 ml/min/m2 to 112 +/- 22 ml/min/m2 (p < 0.01) with a concomitant increase in PaO2 from 103 +/- 37 mmHg to 140 +/- 42 mmHg (p < 0.001) and in PvO2 from 35 +/- 4 mmHg to 41 +/- 5 mmHg (p < 0.001). 1) Continuous haemofiltration does not cause significant alternations in haemodynamic variables. 2) Hypothermia frequently occurs in patients undergoing continuous haemofiltration with high ultrafiltration rates. These hypothermic patients show a reduction in VO2 leading to an increase in PvO2 and PaO2. This mild hypothermia in these circumstances has no evident deleterious effects.

[Path analysis of lifestyle habits to the metabolic syndrome].

PubMed

Zhu, Zhen-xin; Zhang, Cheng-qi; Tang, Fang; Song, Xin-hong; Xue, Fu-zhong

2013-04-01

To evaluate the relationship between lifestyle habits and the components of metabolic syndrome (MS). Based on the routine health check-up system in a certain Center for Health Management of Shandong Province, a longitudinal surveillance health check-up cohort from 2005 to 2010 was set up. There were 13 225 urban workers in Jinan included in the analysis. The content of the survey included demographic information, medical history, lifestyle habits, body mass index (BMI) and the level of blood pressure, fasting blood-glucose, and blood lipid, etc. The distribution of BMI, blood pressure, fasting blood-glucose, blood lipid and lifestyle habits between MS patients and non-MS population was compared, latent variables were extracted by exploratory factor analysis to determine the structure model, and then a partial least squares path model was constructed between lifestyle habits and the components of MS. Participants'age was (46.62 ± 12.16) years old. The overall prevalence of the MS was 22.43% (2967/13 225), 26.49% (2535/9570) in males and 11.82% (432/3655) in females. The prevalence of the MS was statistically different between males and females (χ(2) = 327.08, P < 0.01). Between MS patients and non-MS population, the difference of dietary habits was statistically significant (χ(2) = 166.31, P < 0.01) in MS patients, the rate of vegetarian, mixed and animal food was 23.39% (694/2967), 42.50% (1261/2967) and 34.11% (1012/2967) respectively, while in non-MS population was 30.80% (3159/10 258), 46.37% (4757/10 258), 22.83% (2342/10 258) respectively. Their alcohol consumption has statistical difference (χ(2) = 374.22, P < 0.01) in MS patients, the rate of never or past, occasional and regular drinking was 27.37% (812/2967), 24.71% (733/2967), 47.93% (1422/2967) respectively, and in non-MS population was 39.60% (4062/10 258), 31.36% (3217/10 258), 29.04% (2979/10 258) respectively. The difference of their smoking status was statistically significant (χ(2) = 115.86, P < 0.01) in MS patients, the rate of never or past, occasional and regular smoking was 59.72% (1772/2967), 6.24% (185/2967), 34.04% (1010/2967) respectively, while in non-MS population was 70.03% (7184/10 258), 5.35% (549/10 258), 24.61% (2525/10 258) respectively. Both lifestyle habits and the components of MS were attributable to only one latent variable. After adjustment for age and gender, the path coefficient between the latent component of lifestyle habits and the latent component of MS was 0.22 with statistical significance (t = 6.46, P < 0.01) through bootstrap test. Reliability and validity of the model:the lifestyle latent variable: average variance extracted was 0.53, composite reliability was 0.77 and Cronbach's a was 0.57. The MS latent variable: average variance extracted was 0.45, composite reliability was 0.76 and Cronbach's a was 0.59. Unhealthy lifestyle habits are closely related to MS. Meat diet, excessive drinking and smoking are risk factors for MS.

Age estimation using pulp/tooth area ratio in maxillary canines-A digital image analysis.

PubMed

Juneja, Manjushree; Devi, Yashoda B K; Rakesh, N; Juneja, Saurabh

2014-09-01

Determination of age of a subject is one of the most important aspects of medico-legal cases and anthropological research. Radiographs can be used to indirectly measure the rate of secondary dentine deposition which is depicted by reduction in the pulp area. In this study, 200 patients of Karnataka aged between 18-72 years were selected for the study. Panoramic radiographs were made and indirectly digitized. Radiographic images of maxillary canines (RIC) were processed using a computer-aided drafting program (ImageJ). The variables pulp/root length (p), pulp/tooth length (r), pulp/root width at enamel-cementum junction (ECJ) level (a), pulp/root width at mid-root level (c), pulp/root width at midpoint level between ECJ level and mid-root level (b) and pulp/tooth area ratio (AR) were recorded. All the morphological variables including gender were statistically analyzed to derive regression equation for estimation of age. It was observed that 2 variables 'AR' and 'b' contributed significantly to the fit and were included in the regression model, yielding the formula: Age = 87.305-480.455(AR)+48.108(b). Statistical analysis indicated that the regression equation with selected variables explained 96% of total variance with the median of the residuals of 0.1614 years and standard error of estimate of 3.0186 years. There is significant correlation between age and morphological variables 'AR' and 'b' and the derived population specific regression equation can be potentially used for estimation of chronological age of individuals of Karnataka origin.

The Relationship Between Procrastination, Learning Strategies and Statistics Anxiety Among Iranian College Students: A Canonical Correlation Analysis

PubMed Central

Vahedi, Shahrum; Farrokhi, Farahman; Gahramani, Farahnaz; Issazadegan, Ali

2012-01-01

Objective: Approximately 66-80%of graduate students experience statistics anxiety and some researchers propose that many students identify statistics courses as the most anxiety-inducing courses in their academic curriculums. As such, it is likely that statistics anxiety is, in part, responsible for many students delaying enrollment in these courses for as long as possible. This paper proposes a canonical model by treating academic procrastination (AP), learning strategies (LS) as predictor variables and statistics anxiety (SA) as explained variables. Methods: A questionnaire survey was used for data collection and 246-college female student participated in this study. To examine the mutually independent relations between procrastination, learning strategies and statistics anxiety variables, a canonical correlation analysis was computed. Results: Findings show that two canonical functions were statistically significant. The set of variables (metacognitive self-regulation, source management, preparing homework, preparing for test and preparing term papers) helped predict changes of statistics anxiety with respect to fearful behavior, Attitude towards math and class, Performance, but not Anxiety. Conclusion: These findings could be used in educational and psychological interventions in the context of statistics anxiety reduction. PMID:24644468

Statistical downscaling of mean temperature, maximum temperature, and minimum temperature on the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Jiang, L.

2017-12-01

Climate change is considered to be one of the greatest environmental threats. Global climate models (GCMs) are the primary tool used for studying climate change. However, GCMs are limited because of their coarse spatial resolution and inability to resolve important sub-grid scale features such as terrain and clouds. Statistical downscaling methods can be used to downscale large-scale variables to local-scale. In this study, we assess the applicability of the Statistical Downscaling Model (SDSM) in downscaling the outputs from Beijing Normal University Earth System Model (BNU-ESM). The study focus on the the Loess Plateau, China, and the variables for downscaling include daily mean temperature (TMEAN), maximum temperature (TMAX) and minimum temperature (TMIN). The results show that SDSM performs well for these three climatic variables on the Loess Plateau. After downscaling, the root mean square errors for TMEAN, TMAX, TMIN for BNU-ESM were reduced by 70.9%, 75.1%, and 67.2%, respectively. All the rates of change in TMEAN, TMAX and TMIN during the 21st century decreased after SDSM downscaling. We also show that SDSM can effectively reduce uncertainty, compared with the raw model outputs. TMEAN uncertainty was reduced by 27.1%, 26.8%, and 16.3% for the future scenarios of RCP 2.6, RCP 4.5 and RCP 8.5, respectively. The corresponding reductions in uncertainty were 23.6%, 30.7%, and 18.7% for TMAX; 37.6%, 31.8%, and 23.2% for TMIN.

Examination of two methods for statistical analysis of data with magnitude and direction emphasizing vestibular research applications

NASA Technical Reports Server (NTRS)

Calkins, D. S.

1998-01-01

When the dependent (or response) variable response variable in an experiment has direction and magnitude, one approach that has been used for statistical analysis involves splitting magnitude and direction and applying univariate statistical techniques to the components. However, such treatment of quantities with direction and magnitude is not justifiable mathematically and can lead to incorrect conclusions about relationships among variables and, as a result, to flawed interpretations. This note discusses a problem with that practice and recommends mathematically correct procedures to be used with dependent variables that have direction and magnitude for 1) computation of mean values, 2) statistical contrasts of and confidence intervals for means, and 3) correlation methods.

School Context Matters: The Impacts of Concentrated Poverty and Racial Segregation on Childhood Obesity.

PubMed

Piontak, Joy Rayanne; Schulman, Michael D

2016-12-01

Schools are important sites for interventions to prevent childhood obesity. This study examines how variables measuring the socioeconomic and racial composition of schools and counties affect the likelihood of obesity among third to fifth grade children. Body mass index data were collected from third to fifth grade public school students by teachers from 317 urban and rural North Carolina schools in 38 counties. Multilevel models are used to examine county-, school-, and individual-level effects. Low concentrations of poverty at the school level are associated with lower odds of obesity. Schools in rural counties had significantly higher rates of obesity, net the other variables in the model. Students in minority-segregated schools had higher rates of obesity than those in more racially diverse schools, but the effect was not statistically significant once school-level poverty was controlled. Place-based inequalities are important determinants of health inequalities. The results of this study show that school-level variables related to poverty are important for understanding and confronting childhood obesity. © 2016, American School Health Association.

Detection, attribution, and sensitivity of trends toward earlier streamflow in the Sierra Nevada

USGS Publications Warehouse

Maurer, E.P.; Stewart, I.T.; Bonfils, Celine; Duffy, P.B.; Cayan, D.

2007-01-01

Observed changes in the timing of snowmelt dominated streamflow in the western United States are often linked to anthropogenic or other external causes. We assess whether observed streamflow timing changes can be statistically attributed to external forcing, or whether they still lie within the bounds of natural (internal) variability for four large Sierra Nevada (CA) basins, at inflow points to major reservoirs. Streamflow timing is measured by "center timing" (CT), the day when half the annual flow has passed a given point. We use a physically based hydrology model driven by meteorological input from a global climate model to quantify the natural variability in CT trends. Estimated 50-year trends in CT due to natural climate variability often exceed estimated actual CT trends from 1950 to 1999. Thus, although observed trends in CT to date may be statistically significant, they cannot yet be statistically attributed to external influences on climate. We estimate that projected CT changes at the four major reservoir inflows will, with 90% confidence, exceed those from natural variability within 1-4 decades or 4-8 decades, depending on rates of future greenhouse gas emissions. To identify areas most likely to exhibit CT changes in response to rising temperatures, we calculate changes in CT under temperature increases from 1 to 5??. We find that areas with average winter temperatures between -2??C and -4??C are most likely to respond with significant CT shifts. Correspondingly, elevations from 2000 to 2800 in are most sensitive to temperature increases, with CT changes exceeding 45 days (earlier) relative to 1961-1990. Copyright 2007 by the American Geophysical Union.

VoxelStats: A MATLAB Package for Multi-Modal Voxel-Wise Brain Image Analysis.

PubMed

Mathotaarachchi, Sulantha; Wang, Seqian; Shin, Monica; Pascoal, Tharick A; Benedet, Andrea L; Kang, Min Su; Beaudry, Thomas; Fonov, Vladimir S; Gauthier, Serge; Labbe, Aurélie; Rosa-Neto, Pedro

2016-01-01

In healthy individuals, behavioral outcomes are highly associated with the variability on brain regional structure or neurochemical phenotypes. Similarly, in the context of neurodegenerative conditions, neuroimaging reveals that cognitive decline is linked to the magnitude of atrophy, neurochemical declines, or concentrations of abnormal protein aggregates across brain regions. However, modeling the effects of multiple regional abnormalities as determinants of cognitive decline at the voxel level remains largely unexplored by multimodal imaging research, given the high computational cost of estimating regression models for every single voxel from various imaging modalities. VoxelStats is a voxel-wise computational framework to overcome these computational limitations and to perform statistical operations on multiple scalar variables and imaging modalities at the voxel level. VoxelStats package has been developed in Matlab(®) and supports imaging formats such as Nifti-1, ANALYZE, and MINC v2. Prebuilt functions in VoxelStats enable the user to perform voxel-wise general and generalized linear models and mixed effect models with multiple volumetric covariates. Importantly, VoxelStats can recognize scalar values or image volumes as response variables and can accommodate volumetric statistical covariates as well as their interaction effects with other variables. Furthermore, this package includes built-in functionality to perform voxel-wise receiver operating characteristic analysis and paired and unpaired group contrast analysis. Validation of VoxelStats was conducted by comparing the linear regression functionality with existing toolboxes such as glim_image and RMINC. The validation results were identical to existing methods and the additional functionality was demonstrated by generating feature case assessments (t-statistics, odds ratio, and true positive rate maps). In summary, VoxelStats expands the current methods for multimodal imaging analysis by allowing the estimation of advanced regional association metrics at the voxel level.

Characterization of Noise Signatures of Involuntary Head Motion in the Autism Brain Imaging Data Exchange Repository

PubMed Central

Caballero, Carla; Mistry, Sejal; Vero, Joe; Torres, Elizabeth B

2018-01-01

The variability inherently present in biophysical data is partly contributed by disparate sampling resolutions across instrumentations. This poses a potential problem for statistical inference using pooled data in open access repositories. Such repositories combine data collected from multiple research sites using variable sampling resolutions. One example is the Autism Brain Imaging Data Exchange repository containing thousands of imaging and demographic records from participants in the spectrum of autism and age-matched neurotypical controls. Further, statistical analyses of groups from different diagnoses and demographics may be challenging, owing to the disparate number of participants across different clinical subgroups. In this paper, we examine the noise signatures of head motion data extracted from resting state fMRI data harnessed under different sampling resolutions. We characterize the quality of the noise in the variability of the raw linear and angular speeds for different clinical phenotypes in relation to age-matched controls. Further, we use bootstrapping methods to ensure compatible group sizes for statistical comparison and report the ranges of physical involuntary head excursions of these groups. We conclude that different sampling rates do affect the quality of noise in the variability of head motion data and, consequently, the type of random process appropriate to characterize the time series data. Further, given a qualitative range of noise, from pink to brown noise, it is possible to characterize different clinical subtypes and distinguish them in relation to ranges of neurotypical controls. These results may be of relevance to the pre-processing stages of the pipeline of analyses of resting state fMRI data, whereby head motion enters the criteria to clean imaging data from motion artifacts. PMID:29556179

The effect of low force chiropractic adjustments for 4 weeks on body surface electromagnetic field.

PubMed

Zhang, John; Snyder, Brian J

2005-01-01

To study the effects of 4 weeks of low-force chiropractic adjustments on body surface electromagnetic fields (EMFs). Thirty-five chiropractic students randomly assigned into control (17 subjects) and experimental groups (28 subjects). A triaxial fluxgate magnetometer was used for EMF detection. The subjects' body surface EMF was determined in the prone position before and after the chiropractic adjustment. A Toftness low-force chiropractic adjustment was applied to the cervical, thoracic, lumbar, and sacral areas as determined by the practitioner. Heart rate variability analysis was recorded once a week to determine autonomic nervous system activity in both the control and experimental groups. The EMF on the subjects' body surface decreased after chiropractic adjustment at the cervical, thoracic, lumbar, and sacral regions in all 6 visits during the 4-week treatment period. The EMF showed a downtrend over the 4-week period after the low-force adjustment. The same changes were not observed in the control group. The chiropractic adjustment group had a slight decrease in heart rate over the 4-week treatment period, and no significant change was observed in the control group. Heart rate variability analysis did not show consistent changes before and after the low-force adjustments during the treatment period. Low-force chiropractic adjustment in the cervical and thoracic areas resulted in a consistent reduction of the body surface EMF after 4 weeks of active treatment. No statistically significant differences were found in the heart rate and heart rate variability in the 4-week study.

Social inequalities in alcohol consumption in the Czech Republic: a multilevel analysis.

PubMed

Dzúrová, Dagmara; Spilková, Jana; Pikhart, Hynek

2010-05-01

Czech Republic traditionally ranks among the countries with the highest alcohol, consumption. This paper examines both risk and protective factors for frequent of alcohol, consumption in the Czech population using multilevel analysis. Risk factors were measured at the, individual level and at the area level. The individual-level data were obtained from a survey for a, sample of 3526 respondents aged 18-64 years. The area-level data were obtained from the Czech, Statistical Office. The group most inclinable to risk alcohol consumption and binge drinking are mainly, men, who live as single, with low education and also unemployed. Only the variable for divorce rate, showed statistical significance at both levels, thus the individual and the aggregated one. No cross-level interactions were found to be statistically significant. Copyright 2010 Elsevier Ltd. All rights reserved.

Does mental health staffing level affect antipsychotic prescribing? Analysis of Italian national statistics.

PubMed

Starace, Fabrizio; Mungai, Francesco; Barbui, Corrado

2018-01-01

In mental healthcare, one area of major concern identified by health information systems is variability in antipsychotic prescribing. While most studies have investigated patient- and prescriber-related factors as possible reasons for such variability, no studies have investigated facility-level characteristics. The present study ascertained whether staffing level is associated with antipsychotic prescribing in community mental healthcare. A cross-sectional analysis of data extracted from the Italian national mental health information system was carried out. For each Italian region, it collects data on the availability and use of mental health facilities. The rate of individuals exposed to antipsychotic drugs was tested for evidence of association with the rate of mental health staff availability by means of univariate and multivariate analyses. In Italy there were on average nearly 60 mental health professionals per 100,000 inhabitants, with wide regional variations (range 21 to 100). The average rate of individuals prescribed antipsychotic drugs was 2.33%, with wide regional variations (1.04% to 4.01%). Univariate analysis showed that the rate of individuals prescribed antipsychotic drugs was inversely associated with the rate of mental health professionals available in Italian regions (Kendall's tau -0.438, p = 0.006), with lower rates of antipsychotic prescriptions in regions with higher rates of mental health professionals. After adjustment for possible confounders, the total availability of mental health professionals was still inversely associated with the rate of individuals exposed to antipsychotic drugs. The evidence that staffing level was inversely associated with antipsychotic prescribing indicates that any actions aimed at decreasing variability in antipsychotic prescribing need to take into account aspects related to the organization of the mental health system.

Heart Rate and Systolic Blood Pressure Variability in the Time Domain in Patients with Recent and Long-Standing Diabetes Mellitus

PubMed Central

Rivera, Ana Leonor; Estañol, Bruno; Sentíes-Madrid, Horacio; Fossion, Ruben; Toledo-Roy, Juan C.; Mendoza-Temis, Joel; Morales, Irving O.; Landa, Emmanuel; Robles-Cabrera, Adriana; Moreno, Rene; Frank, Alejandro

2016-01-01

Diabetes Mellitus (DM) affects the cardiovascular response of patients. To study this effect, interbeat intervals (IBI) and beat-to-beat systolic blood pressure (SBP) variability of patients during supine, standing and controlled breathing tests were analyzed in the time domain. Simultaneous noninvasive measurements of IBI and SBP for 30 recently diagnosed and 15 long-standing DM patients were compared with the results for 30 rigorously screened healthy subjects (control). A statistically significant distinction between control and diabetic subjects was provided by the standard deviation and the higher moments of the distributions (skewness, and kurtosis) with respect to the median. To compare IBI and SBP for different populations, we define a parameter, α, that combines the variability of the heart rate and the blood pressure, as the ratio of the radius of the moments for IBI and the same radius for SBP. As diabetes evolves, α decreases, standard deviation of the IBI detrended signal diminishes (heart rate signal becomes more “rigid”), skewness with respect to the median approaches zero (signal fluctuations gain symmetry), and kurtosis increases (fluctuations concentrate around the median). Diabetes produces not only a rigid heart rate, but also increases symmetry and has leptokurtic distributions. SBP time series exhibit the most variable behavior for recently diagnosed DM with platykurtic distributions. Under controlled breathing, SBP has symmetric distributions for DM patients, while control subjects have non-zero skewness. This may be due to a progressive decrease of parasympathetic and sympathetic activity to the heart and blood vessels as diabetes evolves. PMID:26849653

Heart Rate and Systolic Blood Pressure Variability in the Time Domain in Patients with Recent and Long-Standing Diabetes Mellitus.

PubMed

Rivera, Ana Leonor; Estañol, Bruno; Sentíes-Madrid, Horacio; Fossion, Ruben; Toledo-Roy, Juan C; Mendoza-Temis, Joel; Morales, Irving O; Landa, Emmanuel; Robles-Cabrera, Adriana; Moreno, Rene; Frank, Alejandro

2016-01-01

Diabetes Mellitus (DM) affects the cardiovascular response of patients. To study this effect, interbeat intervals (IBI) and beat-to-beat systolic blood pressure (SBP) variability of patients during supine, standing and controlled breathing tests were analyzed in the time domain. Simultaneous noninvasive measurements of IBI and SBP for 30 recently diagnosed and 15 long-standing DM patients were compared with the results for 30 rigorously screened healthy subjects (control). A statistically significant distinction between control and diabetic subjects was provided by the standard deviation and the higher moments of the distributions (skewness, and kurtosis) with respect to the median. To compare IBI and SBP for different populations, we define a parameter, α, that combines the variability of the heart rate and the blood pressure, as the ratio of the radius of the moments for IBI and the same radius for SBP. As diabetes evolves, α decreases, standard deviation of the IBI detrended signal diminishes (heart rate signal becomes more "rigid"), skewness with respect to the median approaches zero (signal fluctuations gain symmetry), and kurtosis increases (fluctuations concentrate around the median). Diabetes produces not only a rigid heart rate, but also increases symmetry and has leptokurtic distributions. SBP time series exhibit the most variable behavior for recently diagnosed DM with platykurtic distributions. Under controlled breathing, SBP has symmetric distributions for DM patients, while control subjects have non-zero skewness. This may be due to a progressive decrease of parasympathetic and sympathetic activity to the heart and blood vessels as diabetes evolves.

Variability in ADHD care in community-based pediatrics.

PubMed

Epstein, Jeffery N; Kelleher, Kelly J; Baum, Rebecca; Brinkman, William B; Peugh, James; Gardner, William; Lichtenstein, Phil; Langberg, Joshua

2014-12-01

Although many efforts have been made to improve the quality of care delivered to children with attention-deficit/hyperactivity disorder (ADHD) in community-based pediatric settings, little is known about typical ADHD care in these settings other than rates garnered through pediatrician self-report. Rates of evidence-based ADHD care and sources of variability (practice-level, pediatrician-level, patient-level) were determined by chart reviews of a random sample of 1594 patient charts across 188 pediatricians at 50 different practices. In addition, the associations of Medicaid-status and practice setting (ie, urban, suburban, and rural) with the quality of ADHD care were examined. Parent- and teacher-rating scales were used during ADHD assessment with approximately half of patients. The use of Diagnostic and Statistical Manual of Mental Disorders criteria was documented in 70.4% of patients. The vast majority (93.4%) of patients with ADHD were receiving medication and only 13.0% were receiving psychosocial treatment. Parent- and teacher-ratings were rarely collected to monitor treatment response or side effects. Further, fewer than half (47.4%) of children prescribed medication had contact with their pediatrician within the first month of prescribing. Most variability in pediatrician-delivered ADHD care was accounted for at the patient level; however, pediatricians and practices also accounted for significant variability on specific ADHD care behaviors. There is great need to improve the quality of ADHD care received by children in community-based pediatric settings. Improvements will likely require systematic interventions at the practice and policy levels to promote change. Copyright © 2014 by the American Academy of Pediatrics.

THE PEDIATRIC RHEUMATOLOGY INTERNATIONAL TRIALS ORGANIZATION PROVISIONAL CRITERIA FOR THE EVALUATION OF RESPONSE TO THERAPY IN JUVENILE DERMATOMYOSITIS

PubMed Central

Ruperto, Nicolino; Pistorio, Angela; Ravelli, Angelo; Rider, Lisa G.; Pilkington, Clarissa; Oliveira, Sheila; Wulffraat, Nico; Espada, Graciela; Garay, Stella; Cuttica, Ruben; Hofer, Michael; Quartier, Pierre; Melo-Gomes, Jose; Reed, Ann M.; Wierzbowska, Malgorzata; Feldman, Brian M.; Harjacek, Miroslav; Huppertz, Hans-Iko; Nielsen, Susan; Flato, Berit; Lahdenne, Pekka; Michels, Harmut; Murray, Kevin J.; Punaro, Lynn; Rennebohm, Robert; Russo, Ricardo; Balogh, Zsolt; Rooney, Madeleine; Pachman, Lauren M.; Wallace, Carol; Hashkes, Philip; Lovell, Daniel J.; Giannini, Edward H.; Martini, Alberto

2010-01-01

Objective To develop a provisional definition for the evaluation of response to therapy in juvenile dermatomyositis (JDM) based on the PRINTO JDM core set of variables. Methods Thirty-seven experienced pediatric rheumatologists from 27 countries, achieved consensus on 128 difficult patient profiles as clinically improved or not improved using a stepwise approach (patients rating, statistical analysis, definition selection). Using the physicians’ consensus ratings as the “gold-standard measure”, chi-square, sensitivity, specificity, false positive and negative rate, area under the ROC, and kappa agreement for candidate definitions of improvement were calculated. Definitions with kappa >0.8 were multiplied with the face validity score to select the top definitions. Results The top definition of improvement was: at least 20% improvement from baseline in 3/6 core set variables with no more than 1 of the remaining worsening by more than 30%, which cannot be muscle strength. The second highest scoring definition was at least 20% improvement from baseline in 3/6 core set variables with no more than 2 of the remaining worsening by more than 25%, which cannot be muscle strength which is definition P1 selected by the IMACS group. The third is similar to the second with the maximum amount of worsening set to 30%. This indicates convergent validity of the process. Conclusion we proposes a provisional data driven definition of improvement that reflects well the consensus rating of experienced clinicians, which incorporates clinically meaningful change in core set variables in a composite endpoint for the evaluation of global response to therapy in JDM. PMID:20583105

Driving factors of interactions between the exchange rate market and the commodity market: A wavelet-based complex network perspective

NASA Astrophysics Data System (ADS)

Wen, Shaobo; An, Haizhong; Chen, Zhihua; Liu, Xueyong

2017-08-01

In traditional econometrics, a time series must be in a stationary sequence. However, it usually shows time-varying fluctuations, and it remains a challenge to execute a multiscale analysis of the data and discover the topological characteristics of conduction in different scales. Wavelet analysis and complex networks in physical statistics have special advantages in solving these problems. We select the exchange rate variable from the Chinese market and the commodity price index variable from the world market as the time series of our study. We explore the driving factors behind the behavior of the two markets and their topological characteristics in three steps. First, we use the Kalman filter to find the optimal estimation of the relationship between the two markets. Second, wavelet analysis is used to extract the scales of the relationship that are driven by different frequency wavelets. Meanwhile, we search for the actual economic variables corresponding to different frequency wavelets. Finally, a complex network is used to search for the transfer characteristics of the combination of states driven by different frequency wavelets. The results show that statistical physics have a unique advantage over traditional econometrics. The Chinese market has time-varying impacts on the world market: it has greater influence when the world economy is stable and less influence in times of turmoil. The process of forming the state combination is random. Transitions between state combinations have a clustering feature. Based on these characteristics, we can effectively reduce the information burden on investors and correctly respond to the government's policy mix.

Variability in Rheumatology day care hospitals in Spain: VALORA study.

PubMed

Hernández Miguel, María Victoria; Martín Martínez, María Auxiliadora; Corominas, Héctor; Sanchez-Piedra, Carlos; Sanmartí, Raimon; Fernandez Martinez, Carmen; García-Vicuña, Rosario

To describe the variability of the day care hospital units (DCHUs) of Rheumatology in Spain, in terms of structural resources and operating processes. Multicenter descriptive study with data from a self-completed questionnaire of DCHUs self-assessment based on DCHUs quality standards of the Spanish Society of Rheumatology. Structural resources and operating processes were analyzed and stratified by hospital complexity (regional, general, major and complex). Variability was determined using the coefficient of variation (CV) of the variable with clinical relevance that presented statistically significant differences when was compared by centers. A total of 89 hospitals (16 autonomous regions and Melilla) were included in the analysis. 11.2% of hospitals are regional, 22,5% general, 27%, major and 39,3% complex. A total of 92% of DCHUs were polyvalent. The number of treatments applied, the coordination between DCHUs and hospital pharmacy and the post graduate training process were the variables that showed statistically significant differences depending on the complexity of hospital. The highest rate of rheumatologic treatments was found in complex hospitals (2.97 per 1,000 population), and the lowest in general hospitals (2.01 per 1,000 population). The CV was 0.88 in major hospitals; 0.86 in regional; 0.76 in general, and 0.72 in the complex. there was variability in the number of treatments delivered in DCHUs, being greater in major hospitals and then in regional centers. Nonetheless, the variability in terms of structure and function does not seem due to differences in center complexity. Copyright © 2016 Elsevier España, S.L.U. and Sociedad Española de Reumatología y Colegio Mexicano de Reumatología. All rights reserved.

Under-Five Mortality in High Focus States in India: A District Level Geospatial Analysis

PubMed Central

Kumar, Chandan; Singh, Prashant Kumar; Rai, Rajesh Kumar

2012-01-01

Background This paper examines if, when controlling for biophysical and geographical variables (including rainfall, productivity of agricultural lands, topography/temperature, and market access through road networks), socioeconomic and health care indicators help to explain variations in the under-five mortality rate across districts from nine high focus states in India. The literature on this subject is inconclusive because the survey data, upon which most studies of child mortality rely, rarely include variables that measure these factors. This paper introduces these variables into an analysis of 284 districts from nine high focus states in India. Methodology/Principal Findings Information on the mortality indicator was accessed from the recently conducted Annual Health Survey of 2011 and other socioeconomic and geographic variables from Census 2011, District Level Household and Facility Survey (2007–08), Department of Economics and Statistics Divisions of the concerned states. Displaying high spatial dependence (spatial autocorrelation) in the mortality indicator (outcome variable) and its possible predictors used in the analysis, the paper uses the Spatial-Error Model in an effort to negate or reduce the spatial dependence in model parameters. The results evince that the coverage gap index (a mixed indicator of district wise coverage of reproductive and child health services), female literacy, urbanization, economic status, the number of newborn care provided in Primary Health Centers in the district transpired as significant correlates of under-five mortality in the nine high focus states in India. The study identifies three clusters with high under-five mortality rate including 30 districts, and advocates urgent attention. Conclusion Even after controlling the possible biophysical and geographical variables, the study reveals that the health program initiatives have a major role to play in reducing under-five mortality rate in the high focus states in India. PMID:22629412

Exact statistical results for binary mixing and reaction in variable density turbulence

NASA Astrophysics Data System (ADS)

Ristorcelli, J. R.

2017-02-01

We report a number of rigorous statistical results on binary active scalar mixing in variable density turbulence. The study is motivated by mixing between pure fluids with very different densities and whose density intensity is of order unity. Our primary focus is the derivation of exact mathematical results for mixing in variable density turbulence and we do point out the potential fields of application of the results. A binary one step reaction is invoked to derive a metric to asses the state of mixing. The mean reaction rate in variable density turbulent mixing can be expressed, in closed form, using the first order Favre mean variables and the Reynolds averaged density variance, ⟨ρ2⟩ . We show that the normalized density variance, ⟨ρ2⟩ , reflects the reduction of the reaction due to mixing and is a mix metric. The result is mathematically rigorous. The result is the variable density analog, the normalized mass fraction variance ⟨c2⟩ used in constant density turbulent mixing. As a consequence, we demonstrate that use of the analogous normalized Favre variance of the mass fraction, c″ ⁣2˜ , as a mix metric is not theoretically justified in variable density turbulence. We additionally derive expressions relating various second order moments of the mass fraction, specific volume, and density fields. The central role of the density specific volume covariance ⟨ρ v ⟩ is highlighted; it is a key quantity with considerable dynamical significance linking various second order statistics. For laboratory experiments, we have developed exact relations between the Reynolds scalar variance ⟨c2⟩ its Favre analog c″ ⁣2˜ , and various second moments including ⟨ρ v ⟩ . For moment closure models that evolve ⟨ρ v ⟩ and not ⟨ρ2⟩ , we provide a novel expression for ⟨ρ2⟩ in terms of a rational function of ⟨ρ v ⟩ that avoids recourse to Taylor series methods (which do not converge for large density differences). We have derived analytic results relating several other second and third order moments and see coupling between odd and even order moments demonstrating a natural and inherent skewness in the mixing in variable density turbulence. The analytic results have applications in the areas of isothermal material mixing, isobaric thermal mixing, and simple chemical reaction (in progress variable formulation).

Incorporating Stroke Severity Into Hospital Measures of 30-Day Mortality After Ischemic Stroke Hospitalization.

PubMed

Schwartz, Jennifer; Wang, Yongfei; Qin, Li; Schwamm, Lee H; Fonarow, Gregg C; Cormier, Nicole; Dorsey, Karen; McNamara, Robert L; Suter, Lisa G; Krumholz, Harlan M; Bernheim, Susannah M

2017-11-01

The Centers for Medicare & Medicaid Services publicly reports a hospital-level stroke mortality measure that lacks stroke severity risk adjustment. Our objective was to describe novel measures of stroke mortality suitable for public reporting that incorporate stroke severity into risk adjustment. We linked data from the American Heart Association/American Stroke Association Get With The Guidelines-Stroke registry with Medicare fee-for-service claims data to develop the measures. We used logistic regression for variable selection in risk model development. We developed 3 risk-standardized mortality models for patients with acute ischemic stroke, all of which include the National Institutes of Health Stroke Scale score: one that includes other risk variables derived only from claims data (claims model); one that includes other risk variables derived from claims and clinical variables that could be obtained from electronic health record data (hybrid model); and one that includes other risk variables that could be derived only from electronic health record data (electronic health record model). The cohort used to develop and validate the risk models consisted of 188 975 hospital admissions at 1511 hospitals. The claims, hybrid, and electronic health record risk models included 20, 21, and 9 risk-adjustment variables, respectively; the C statistics were 0.81, 0.82, and 0.79, respectively (as compared with the current publicly reported model C statistic of 0.75); the risk-standardized mortality rates ranged from 10.7% to 19.0%, 10.7% to 19.1%, and 10.8% to 20.3%, respectively; the median risk-standardized mortality rate was 14.5% for all measures; and the odds of mortality for a high-mortality hospital (+1 SD) were 1.51, 1.52, and 1.52 times those for a low-mortality hospital (-1 SD), respectively. We developed 3 quality measures that demonstrate better discrimination than the Centers for Medicare & Medicaid Services' existing stroke mortality measure, adjust for stroke severity, and could be implemented in a variety of settings. © 2017 American Heart Association, Inc.

Sleep variability and cardiac autonomic modulation in adolescents – Penn State Child Cohort (PSCC) study

PubMed Central

Rodríguez-Colón, Sol M.; He, Fan; Bixler, Edward O.; Fernandez-Mendoza, Julio; Vgontzas, Alexandros N.; Calhoun, Susan; Zheng, Zhi-Jie; Liao, Duanping

2015-01-01

Objective To investigate the effects of objectively measured habitual sleep patterns on cardiac autonomic modulation (CAM) in a population-based sample of adolescents. Methods We used data from 421 adolescents who completed the follow-up examination in the Penn State Children Cohort study. CAM was assessed by heart rate (HR) variability (HRV) analysis of beat-to-beat normal R-R intervals from a 39-h electrocardiogram, on a 30-min basis. The HRV indices included frequency domain (HF, LF, and LF/HF ratio), and time domain (SDNN, RMSSD, and heart rate or HR) variables. Actigraphy was used for seven consecutive nights to estimate nightly sleep duration and time in bed. The seven-night mean (SD) of sleep duration and sleep efficiency were used to represent sleep duration, duration variability, sleep efficiency, and efficiency variability, respectively. HF and LF were log-transformed for statistical analysis. Linear mixed-effect models were used to analyze the association between sleep patterns and CAM. Results After adjusting for major confounders, increased sleep duration variability and efficiency variability were significantly associated with lower HRV and higher HR during the 39-h, as well as separated by daytime and nighttime. For instance, a 1-h increase in sleep duration variability is associated with −0.14(0.04), −0.12(0.06), and −0.16(0.05) ms2 decrease in total, daytime, and nighttime HF, respectively. No associations were found between sleep duration, or sleep efficiency and HRV. Conclusion Higher habitual sleep duration variability and efficiency variability are associated with lower HRV and higher HR, suggesting that an irregular sleep pattern has an adverse impact on CAM, even in healthy adolescents. PMID:25555635

On the Importance of "Front-Side Mechanics" in Athletics Sprinting.

PubMed

Haugen, Thomas; Danielsen, Jørgen; Alnes, Leif Olav; McGhie, David; Sandbakk, Øyvind; Ettema, Gertjan

2018-05-16

Practitioners have, for many years, argued that athletic sprinters should optimize front-side mechanics (leg motions occurring in front of the extended line through the torso) and minimize back-side mechanics. This study aimed to investigate if variables related to front- and back-side mechanics can be distinguished from other previously highlighted kinematic variables (spatiotemporal variables and variables related to segment configuration and velocities at touchdown) in how they statistically predict performance. A total of 24 competitive sprinters (age: 23.1 [3.4] y, height: 1.81 [0.06] m, body mass: 75.7 [5.6] kg, and 100-m personal best: 10.86 [0.22] s) performed two 20-m starts from block and 2 to 3 flying sprints over 20 m. Kinematics were recorded in 3D using a motion tracking system with 21 cameras at a 250 Hz sampling rate. Several front- and back-side variables, including thigh (r = .64) and knee angle (r = .51) at lift-off and maximal thigh extension (r = .66), were largely correlated (P < .05) with accelerated running performance, and these variables displayed significantly higher correlations (P < .05) to accelerated running performance than nearly all the other analyzed variables. However, the relationship directions for most front- and back-side variables during accelerated running were opposite in comparison to how the theoretical concept has been described. Horizontal ankle velocity, contact time, and step rate displayed significantly higher correlation values to maximal velocity sprinting than the other variables (P < .05), and neither of the included front- and back-side variables were significantly associated with maximal velocity sprinting. Overall, the present findings did not support that front-side mechanics were crucial for sprint performance among the investigated sprinters.

Exploring the Connection Between Sampling Problems in Bayesian Inference and Statistical Mechanics

NASA Technical Reports Server (NTRS)

Pohorille, Andrew

2006-01-01

The Bayesian and statistical mechanical communities often share the same objective in their work - estimating and integrating probability distribution functions (pdfs) describing stochastic systems, models or processes. Frequently, these pdfs are complex functions of random variables exhibiting multiple, well separated local minima. Conventional strategies for sampling such pdfs are inefficient, sometimes leading to an apparent non-ergodic behavior. Several recently developed techniques for handling this problem have been successfully applied in statistical mechanics. In the multicanonical and Wang-Landau Monte Carlo (MC) methods, the correct pdfs are recovered from uniform sampling of the parameter space by iteratively establishing proper weighting factors connecting these distributions. Trivial generalizations allow for sampling from any chosen pdf. The closely related transition matrix method relies on estimating transition probabilities between different states. All these methods proved to generate estimates of pdfs with high statistical accuracy. In another MC technique, parallel tempering, several random walks, each corresponding to a different value of a parameter (e.g. "temperature"), are generated and occasionally exchanged using the Metropolis criterion. This method can be considered as a statistically correct version of simulated annealing. An alternative approach is to represent the set of independent variables as a Hamiltonian system. Considerab!e progress has been made in understanding how to ensure that the system obeys the equipartition theorem or, equivalently, that coupling between the variables is correctly described. Then a host of techniques developed for dynamical systems can be used. Among them, probably the most powerful is the Adaptive Biasing Force method, in which thermodynamic integration and biased sampling are combined to yield very efficient estimates of pdfs. The third class of methods deals with transitions between states described by rate constants. These problems are isomorphic with chemical kinetics problems. Recently, several efficient techniques for this purpose have been developed based on the approach originally proposed by Gillespie. Although the utility of the techniques mentioned above for Bayesian problems has not been determined, further research along these lines is warranted

Does gender modify associations between self rated health and the social and economic characteristics of local environments?

PubMed

Kavanagh, Anne M; Bentley, Rebecca; Turrell, Gavin; Broom, Dorothy H; Subramanian, S V

2006-06-01

To examine whether area level socioeconomic disadvantage and social capital have different relations with women's and men's self rated health. The study used data from 15 112 respondents to the 1998 Tasmanian (Australia) healthy communities study (60% response rate) nested within 41 statistical local areas. Gender stratified analyses were conducted of the associations between the index of relative socioeconomic disadvantage (IRSD) and social capital (neighbourhood integration, neighbourhood alienation, neighbourhood safety, political participation, social trust, trust in institutions) and individual level self rated health using multilevel logistic regression analysis before (age only) and after adjustment for individual level confounders (marital status, indigenous status, income, education, occupation, smoking). The study also tested for interactions between gender and area level variables. IRSD was associated with poor self rated health for women (age adjusted p<0.001) and men (age adjusted p<0.001), however, the estimates attenuated when adjusted for individual level variables. Political participation and neighbourhood safety were protective for women's self rated health but not for men's. Interactions between gender and political participation (p = 0.010) and neighbourhood safety (p = 0.023) were significant. These finding suggest that women may benefit more than men from higher levels of area social capital.

Weight-elimination neural networks applied to coronary surgery mortality prediction.

PubMed

Ennett, Colleen M; Frize, Monique

2003-06-01

The objective was to assess the effectiveness of the weight-elimination cost function in improving classification performance of artificial neural networks (ANNs) and to observe how changing the a priori distribution of the training set affects network performance. Backpropagation feedforward ANNs with and without weight-elimination estimated mortality for coronary artery surgery patients. The ANNs were trained and tested on cases with 32 input variables describing the patient's medical history; the output variable was in-hospital mortality (mortality rates: training 3.7%, test 3.8%). Artificial training sets with mortality rates of 20%, 50%, and 80% were created to observe the impact of training with a higher-than-normal prevalence. When the results were averaged, weight-elimination networks achieved higher sensitivity rates than those without weight-elimination. Networks trained on higher-than-normal prevalence achieved higher sensitivity rates at the cost of lower specificity and correct classification. The weight-elimination cost function can improve the classification performance when the network is trained with a higher-than-normal prevalence. A network trained with a moderately high artificial mortality rate (artificial mortality rate of 20%) can improve the sensitivity of the model without significantly affecting other aspects of the model's performance. The ANN mortality model achieved comparable performance as additive and statistical models for coronary surgery mortality estimation in the literature.

Patient characteristics and variability in adherence and competence in cognitive-behavioral therapy for panic disorder.

PubMed

Boswell, James F; Gallagher, Matthew W; Sauer-Zavala, Shannon E; Bullis, Jacqueline; Gorman, Jack M; Shear, M Katherine; Woods, Scott; Barlow, David H

2013-06-01

Although associations with outcome have been inconsistent, therapist adherence and competence continues to garner attention, particularly within the context of increasing interest in the dissemination, implementation, and sustainability of evidence-based treatments. To date, research on therapist adherence and competence has focused on average levels across therapists. With a few exceptions, research has failed to address multiple sources of variability in adherence and competence, identify important factors that might account for variability, or take these sources of variability into account when examining associations with symptom change. (a) statistically demonstrate between- and within-therapist variability in adherence and competence ratings and examine patient characteristics as predictors of this variability and (b) examine the relationship between adherence/competence and symptom change. Randomly selected audiotaped sessions from a randomized controlled trial of cognitive-behavioral therapy for panic disorder were rated for therapist adherence and competence. Patients completed a self-report measure of panic symptom severity prior to each session and the Inventory of Interpersonal Problems-Personality Disorder Scale prior to the start of treatment. Significant between- and within-therapist variability in adherence and competence were observed. Adherence and competence deteriorated significantly over the course of treatment. Higher patient interpersonal aggression was associated with decrements in both adherence and competence. Neither adherence nor competence predicted subsequent panic severity. Variability and "drift" in adherence and competence can be observed in controlled trials. Training and implementation efforts should involve continued consultation over multiple cases in order to account for relevant patient factors and promote sustainability across sessions and patients.

Royalty, Racing, and Rolling Pigs

ERIC Educational Resources Information Center

Groth, Randall E.

2015-01-01

Some statisticians have pointed out that the field of statistics essentially exists to study the variability seen in everyday life. Because variability is so foundational, the "Guidelines for Assessment and Instruction in Statistics Education" (GAISE 2007), published by the American Statistical Association (ASA), recommend that teachers…

The effect of teacher quality on the achievement of students in Integrated Physics and Chemistry

NASA Astrophysics Data System (ADS)

Alexander, Rima

For many years, researchers, policy makers, and the education community have explored various school variables and their impact on student achievement (Darling-Hammond, 2000; Ferguson and Womack 1993; Ferguson and Ladd 1996; Rice, 2003; Rockoff, 2003; Rowan, Chiang, and Miller 1997; Sanders and Horn, 1996; Wright Horn and Sanders, 1997). Invariably, the issue of teacher quality arises. Teacher quality is the single most influential factor under school control that affects student achievement (Darling-Hammond, 2000; Rice, 2003; Rockoff, 2003; Sanders and Horn, 1996; Wright Horn and Sanders, 1997). Generally, students taught by highly qualified teachers perform better on standardized tests than students with less qualified teachers (Ferguson and Womack 1993; Ferguson and Ladd 1996; Rowan, Chiang, and Miller 1997). Previous research indicates that teachers indeed matter for the improvement of student achievement, but getting good measures of what is meant by teacher quality is a continuing challenge (Goldhaber, 2002). The purpose of this study was to describe the effect of teacher quality on the achievement of students in Integrated Physics and Chemistry (IPC). In order to achieve this purpose, this study addressed the following research question: chemistry and physics teachers compare to the achievement of students taught by less-qualified IPC teachers? A causal-comparative methodology was employed to address this research question. The independent variable was teacher quality---highly-qualified or less qualified. The teacher attributes that were examined in this study are: (1) teachers' educational background; (2) content knowledge; (3) pedagogical knowledge; and (4) certification. The dependent variable was student achievement in integrated physics and chemistry, as measured by an end-of-course IPC District Assessment of Curriculum, IPC DAC. Descriptive statistics were computed for the independent variable in the study. A Chi Square was performed on the data, utilizing SPSS version 12.0.1 software. Next a test of statistical significance was done to determine whether the null hypothesis could be rejected; and whether or not the research hypothesis could be accepted. Since this is a causal comparative design with only two groups in which student achievement was measured by a test that will yield raw scores, a Chi Square was conducted to determine whether the pass rates of the two groups of students based on obtained and expected percentages were statistically significantly different A Chi Square value of 4.29 was obtained, which indicates that the pass rate for students of highly-qualified teachers was statistically significantly higher than for students of less-qualified teachers. For the purpose of this study a criterion value of (p<.05) was used.

Do State-Based Policies Have an Impact on Teen Birth Rates and Teen Abortion Rates in the United States?

PubMed

Chevrette, Marianne; Abenhaim, Haim Arie

2015-10-01

The United States has one of the highest teen birth rates among developed countries. Interstate birth rates and abortion rates vary widely, as do policies on abortion and sex education. The objective of our study is to assess whether US state-level policies regarding abortion and sexual education are associated with different teen birth and teen abortion rates. We carried out a state-level (N = 51 [50 states plus the District of Columbia]) retrospective observational cross-sectional study, using data imported from the National Vital Statistics System. State policies were obtained from the Guttmacher Institute. We used descriptive statistics and regression analysis to study the association of different state policies with teen birth and teen abortion rates. The state-level mean birth rates, when stratifying between policies protective and nonprotective of teen births, were not statistically different-for sex education policies, 39.8 of 1000 vs 45.1 of 1000 (P = .2187); for mandatory parents' consent to abortion 45 of 1000, vs 38 of 1000 when the minor could consent (P = .0721); and for deterrents to abortion, 45.4 of 1000 vs 37.4 of 1000 (P = .0448). Political affiliation (35.1 of 1000 vs 49.6 of 1000, P < .0001) and ethnic distribution of the population were the only variables associated with a difference between mean teen births. Lower teen abortion rates were, however, associated with restrictive abortion policies, specifically lower in states with financial barriers, deterrents to abortion, and requirement for parental consent. While teen birth rates do not appear to be influenced by state-level sex education policies, state-level policies that restrict abortion appear to be associated with lower state teen abortion rates. Copyright © 2015 North American Society for Pediatric and Adolescent Gynecology. Published by Elsevier Inc. All rights reserved.

Physical restraints in an Italian psychiatric ward: clinical reasons and staff organization problems.

PubMed

Di Lorenzo, Rosaria; Baraldi, Sara; Ferrara, Maria; Mimmi, Stefano; Rigatelli, Marco

2012-04-01

To analyze physical restraint use in an Italian acute psychiatric ward, where mechanical restraint by belt is highly discouraged but allowed. Data were retrospectively collected from medical and nursing charts, from January 1, 2005, to December 31, 2008. Physical restraint rate and relationships between restraints and selected variables were statistically analyzed. Restraints were statistically significantly more frequent in compulsory or voluntary admissions of patients with an altered state of consciousness, at night, to control aggressive behavior, and in patients with "Schizophrenia and other Psychotic Disorders" during the first 72 hr of hospitalization. Analysis of clinical and organizational factors conditioning restraints may limit its use. © 2011 Wiley Periodicals, Inc.

Perceptions of work environment priorities: Are there any differences by company size? An ecological study

PubMed Central

Nordlöf, Hasse; Wijk, Katarina; Westergren, Karl-Erik

2015-01-01

BACKGROUND: Earlier studies suggest that the quality of handling occupational health and safety (OHS) activities differs between companies of different sizes. Company size is a proxy variable for other variables affecting OHS performance. OBJECTIVE: The objective of this study was to investigate if there is an association between company size and perceptions of work environment prioritizations. METHODS: Data from 106 small- and medium-sized Swedish manufacturing companies was collected. One manager and one safety delegate at each company rated different aspects of their companies’ work environment prioritizations with a 43-item questionnaire. Ratings were aggregated to a summary statistic for each company before analysis. RESULTS: No significant differences in perceptions of priority were found to be associated with company sizes. This is in contrast to earlier studies of objective differences. The respondents in small companies, however, showed significantly greater consensus in their ratings. CONCLUSIONS: Company size does not appear to be associated with perceptions of work environment prioritizations. Company size is an important proxy variable to study in order to understand what factors enable and obstruct safe and healthy workplaces. The work presented here should be viewed as an initial exploration to serve as direction for future academic work. PMID:26409368

Investigation of visually induced motion sickness in dynamic 3D contents based on subjective judgment, heart rate variability, and depth gaze behavior.

PubMed

Wibirama, Sunu; Hamamoto, Kazuhiko

2014-01-01

Visually induced motion sickness (VIMS) is an important safety issue in stereoscopic 3D technology. Accompanying subjective judgment of VIMS with objective measurement is useful to identify not only biomedical effects of dynamic 3D contents, but also provoking scenes that induce VIMS, duration of VIMS, and user behavior during VIMS. Heart rate variability and depth gaze behavior are appropriate physiological indicators for such objective observation. However, there is no information about relationship between subjective judgment of VIMS, heart rate variability, and depth gaze behavior. In this paper, we present a novel investigation of VIMS based on simulator sickness questionnaire (SSQ), electrocardiography (ECG), and 3D gaze tracking. Statistical analysis on SSQ data shows that nausea and disorientation symptoms increase as amount of dynamic motions increases (nausea: p<;0.005; disorientation: p<;0.05). To reduce VIMS, SSQ and ECG data suggest that user should perform voluntary gaze fixation at one point when experiencing vertical motion (up or down) and horizontal motion (turn left and right) in dynamic 3D contents. Observation of 3D gaze tracking data reveals that users who experienced VIMS tended to have unstable depth gaze than ones who did not experience VIMS.

Cross-cultural variation of memory colors of familiar objects.

PubMed

Smet, Kevin A G; Lin, Yandan; Nagy, Balázs V; Németh, Zoltan; Duque-Chica, Gloria L; Quintero, Jesús M; Chen, Hung-Shing; Luo, Ronnier M; Safi, Mahdi; Hanselaer, Peter

2014-12-29

The effect of cross-regional or cross-cultural differences on color appearance ratings and memory colors of familiar objects was investigated in seven different countries/regions - Belgium, Hungary, Brazil, Colombia, Taiwan, China and Iran. In each region the familiar objects were presented on a calibrated monitor in over 100 different colors to a test panel of observers that were asked to rate the similarity of the presented object color with respect to what they thought the object looks like in reality (memory color). For each object and region the mean observer ratings were modeled by a bivariate Gaussian function. A statistical analysis showed significant (p < 0.001) differences between the region average observers and the global average observer obtained by pooling the data from all regions. However, the effect size of geographical region or culture was found to be small. In fact, the differences between the region average observers and the global average observer were found to of the same magnitude or smaller than the typical within region inter-observer variability. Thus, although statistical differences in color appearance ratings and memory between regions were found, regional impact is not likely to be of practical importance.

Racial disparities in diabetes mortality in the 50 most populous US cities.

PubMed

Rosenstock, Summer; Whitman, Steve; West, Joseph F; Balkin, Michael

2014-10-01

While studies have consistently shown that in the USA, non-Hispanic Blacks (Blacks) have higher diabetes prevalence, complication and death rates than non-Hispanic Whites (Whites), there are no studies that compare disparities in diabetes mortality across the largest US cities. This study presents and compares Black/White age-adjusted diabetes mortality rate ratios (RRs), calculated using national death files and census data, for the 50 most populous US cities. Relationships between city-level diabetes mortality RRs and 12 ecological variables were explored using bivariate correlation analyses. Multivariate analyses were conducted using negative binomial regression to examine how much of the disparity could be explained by these variables. Blacks had statistically significantly higher mortality rates compared to Whites in 39 of the 41 cities included in analyses, with statistically significant rate ratios ranging from 1.57 (95 % CI: 1.33-1.86) in Baltimore to 3.78 (95 % CI: 2.84-5.02) in Washington, DC. Analyses showed that economic inequality was strongly correlated with the diabetes mortality disparity, driven by differences in White poverty levels. This was followed by segregation. Multivariate analyses showed that adjusting for Black/White poverty alone explained 58.5 % of the disparity. Adjusting for Black/White poverty and segregation explained 72.6 % of the disparity. This study emphasizes the role that inequalities in social and economic determinants, rather than for example poverty on its own, play in Black/White diabetes mortality disparities. It also highlights how the magnitude of the disparity and the factors that influence it can vary greatly across cities, underscoring the importance of using local data to identify context specific barriers and develop effective interventions to eliminate health disparities.

A kinetic model for the synthesis of high-molecular-weight alcohols over a sulfided Co-K-Mo/C catalyst

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gunturu, A.K.; Kugler, E.L.; Cropley, J.B.

A statistically designed set of experiments was run in a recycle reactor to evaluate the kinetics of the formation of higher-molecular-weight alcohols (higher alcohols) and total hydrocarbon byproducts from synthesis gas (hydrogen and carbon monoxide) in a range of experimental conditions that mirrors the limits of commercial production. The alkali-promoted, C-supported Co-Mo sulfide catalyst that was employed in this study is well known for its sulfur resistance. The reaction was carried out in a gradientless Berty-type recycle reactor. A two-level fractional-factorial set consisting of 16 experiments was performed. Five independent variables were selected for this study, namely, temperature, partial pressuremore » of carbon monoxide, partial pressure of hydrogen, partial pressure of inerts, and methanol concentration in the feed. The major oxygenated products were linear alcohols up to n-butanol, but alcohols of higher carbon number were also detected, and analysis of the liquid product revealed the presence of trace amounts of ethers also. Yields of hydrocarbons were non-negligible. The alcohol product followed an Anderson-Schultz-Flory distribution. From the results of the factorial experiments, a preliminary power-law model was developed, and the statistically significant variables in the rate expression for the production of each alcohol were found. Based on the results of the power-law models, rate expressions of the Langmuir-Hinshelwood type were fitted. The observed kinetics are consistent with the rate-limiting step for the production of each higher alcohol being a surface reaction of the alcohol of next-lower carbon number. All other steps, including CO-insertion, H{sub 2}-cleavage, and hydrogenation steps, do not appear to affect the rate correlations.« less

Theoretical and experimental researches on the operating costs of a wastewater treatment plant

NASA Astrophysics Data System (ADS)

Panaitescu, M.; Panaitescu, F.-V.; Anton, I.-A.

2015-11-01

Purpose of the work: The total cost of a sewage plants is often determined by the present value method. All of the annual operating costs for each process are converted to the value of today's correspondence and added to the costs of investment for each process, which leads to getting the current net value. The operating costs of the sewage plants are subdivided, in general, in the premises of the investment and operating costs. The latter can be stable (normal operation and maintenance, the establishment of power) or variables (chemical and power sludge treatment and disposal, of effluent charges). For the purpose of evaluating the preliminary costs so that an installation can choose between different alternatives in an incipient phase of a project, can be used cost functions. In this paper will be calculated the operational cost to make several scenarios in order to optimize its. Total operational cost (fixed and variable) is dependent global parameters of wastewater treatment plant. Research and methodology: The wastewater treatment plant costs are subdivided in investment and operating costs. We can use different cost functions to estimate fixed and variable operating costs. In this study we have used the statistical formulas for cost functions. The method which was applied to study the impact of the influent characteristics on the costs is economic analysis. Optimization of plant design consist in firstly, to assess the ability of the smallest design to treat the maximum loading rates to a given effluent quality and, secondly, to compare the cost of the two alternatives for average and maximum loading rates. Results: In this paper we obtained the statistical values for the investment cost functions, operational fixed costs and operational variable costs for wastewater treatment plant and its graphical representations. All costs were compared to the net values. Finally we observe that it is more economical to build a larger plant, especially if maximum loading rates are reached. The actual target of operational management is to directly implement the presented cost functions in a software tool, in which the design of a plant and the simulation of its behaviour are evaluated simultaneously.

Effectiveness of Hypnosis in Combination with Conventional Techniques of Behavior Management in Anxiety/Pain Reduction during Dental Anesthetic Infiltration.

PubMed

Ramírez-Carrasco, A; Butrón-Téllez Girón, C; Sanchez-Armass, O; Pierdant-Pérez, M

2017-01-01

Background and Objective . Anxiety/pain are experiences that make dental treatment difficult for children, especially during the time of anesthesia. Hypnosis is used in pediatric clinical situations to modify thinking, behavior, and perception as well as, recently, in dentistry; therefore the aim of this study was to evaluate the effectiveness of hypnosis combined with conventional behavior management techniques during infiltration anesthetic. Methods . Anxiety/pain were assessed with the FLACC scale during the anesthetic moment, as well as heart rate variability and skin conductance before and during the anesthetic moment, between the control and experimental group. Results . A marginal statistical difference ( p = 0.05) was found in the heart rate between baseline and anesthetic moment, being lower in the hypnosis group. No statistically significant differences were found with the FLACC scale or in the skin conductance ( p > 0.05). Conclusion . Hypnosis combined with conventional behavior management techniques decreases heart rate during anesthetic infiltration showing that there may be an improvement in anxiety/pain control through hypnotic therapy.

Effectiveness of Hypnosis in Combination with Conventional Techniques of Behavior Management in Anxiety/Pain Reduction during Dental Anesthetic Infiltration

PubMed Central

Ramírez-Carrasco, A.; Butrón-Téllez Girón, C.; Sanchez-Armass, O.

2017-01-01

Background and Objective. Anxiety/pain are experiences that make dental treatment difficult for children, especially during the time of anesthesia. Hypnosis is used in pediatric clinical situations to modify thinking, behavior, and perception as well as, recently, in dentistry; therefore the aim of this study was to evaluate the effectiveness of hypnosis combined with conventional behavior management techniques during infiltration anesthetic. Methods. Anxiety/pain were assessed with the FLACC scale during the anesthetic moment, as well as heart rate variability and skin conductance before and during the anesthetic moment, between the control and experimental group. Results. A marginal statistical difference (p = 0.05) was found in the heart rate between baseline and anesthetic moment, being lower in the hypnosis group. No statistically significant differences were found with the FLACC scale or in the skin conductance (p > 0.05). Conclusion. Hypnosis combined with conventional behavior management techniques decreases heart rate during anesthetic infiltration showing that there may be an improvement in anxiety/pain control through hypnotic therapy. PMID:28490941

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Kandler; Shi, Ying; Santhanagopalan, Shriram

Predictive models of Li-ion battery lifetime must consider a multiplicity of electrochemical, thermal, and mechanical degradation modes experienced by batteries in application environments. To complicate matters, Li-ion batteries can experience different degradation trajectories that depend on storage and cycling history of the application environment. Rates of degradation are controlled by factors such as temperature history, electrochemical operating window, and charge/discharge rate. We present a generalized battery life prognostic model framework for battery systems design and control. The model framework consists of trial functions that are statistically regressed to Li-ion cell life datasets wherein the cells have been aged under differentmore » levels of stress. Degradation mechanisms and rate laws dependent on temperature, storage, and cycling condition are regressed to the data, with multiple model hypotheses evaluated and the best model down-selected based on statistics. The resulting life prognostic model, implemented in state variable form, is extensible to arbitrary real-world scenarios. The model is applicable in real-time control algorithms to maximize battery life and performance. We discuss efforts to reduce lifetime prediction error and accommodate its inevitable impact in controller design.« less

Video pulse rate variability analysis in stationary and motion conditions.

PubMed

Melchor Rodríguez, Angel; Ramos-Castro, J

2018-01-29

In the last few years, some studies have measured heart rate (HR) or heart rate variability (HRV) parameters using a video camera. This technique focuses on the measurement of the small changes in skin colour caused by blood perfusion. To date, most of these works have obtained HRV parameters in stationary conditions, and there are practically no studies that obtain these parameters in motion scenarios and by conducting an in-depth statistical analysis. In this study, a video pulse rate variability (PRV) analysis is conducted by measuring the pulse-to-pulse (PP) intervals in stationary and motion conditions. Firstly, given the importance of the sampling rate in a PRV analysis and the low frame rate of commercial cameras, we carried out an analysis of two models to evaluate their performance in the measurements. We propose a selective tracking method using the Viola-Jones and KLT algorithms, with the aim of carrying out a robust video PRV analysis in stationary and motion conditions. Data and results of the proposed method are contrasted with those reported in the state of the art. The webcam achieved better results in the performance analysis of video cameras. In stationary conditions, high correlation values were obtained in PRV parameters with results above 0.9. The PP time series achieved an RMSE (mean ± standard deviation) of 19.45 ± 5.52 ms (1.70 ± 0.75 bpm). In the motion analysis, most of the PRV parameters also achieved good correlation results, but with lower values as regards stationary conditions. The PP time series presented an RMSE of 21.56 ± 6.41 ms (1.79 ± 0.63 bpm). The statistical analysis showed good agreement between the reference system and the proposed method. In stationary conditions, the results of PRV parameters were improved by our method in comparison with data reported in related works. An overall comparative analysis of PRV parameters in motion conditions was more limited due to the lack of studies or studies containing insufficient data analysis. Based on the results, the proposed method could provide a low-cost, contactless and reliable alternative for measuring HR or PRV parameters in non-clinical environments.

Assessing the determinants of evolutionary rates in the presence of noise.

PubMed

Plotkin, Joshua B; Fraser, Hunter B

2007-05-01

Although protein sequences are known to evolve at vastly different rates, little is known about what determines their rate of evolution. However, a recent study using principal component regression (PCR) has concluded that evolutionary rates in yeast are primarily governed by a single determinant related to translation frequency. Here, we demonstrate that noise in biological data can confound PCRs, leading to spurious conclusions. When equalizing noise levels across 7 predictor variables used in previous studies, we find no evidence that protein evolution is dominated by a single determinant. Our results indicate that a variety of factors--including expression level, gene dispensability, and protein-protein interactions--may independently affect evolutionary rates in yeast. More accurate measurements or more sophisticated statistical techniques will be required to determine which one, if any, of these factors dominates protein evolution.

The U.S. health production function: evidence from 2001 to 2009.

PubMed

Tseng, Hui-Kuan; Olsen, Reed

2016-03-01

This study estimates the impact of the 2007 financial crisis upon U.S. health as measured by age adjusted death rates. OLS regression results suggest that the average death rate was lower in the post-crisis period than the pre-crisis period. The majority of the average decline in the death rate was a result of the time period and not a result of changes in the values of the underlying explanatory variables. We continue to find this result even adding state fixed effects. Contrary to other research, we find that the unemployment rate has no statistically significant impact on death rates either for the U.S. as a whole or for any states individually. Rather, the impact of the financial crisis is felt via year fixed effects that increased over time during the post-crisis period.

Poisson Regression Analysis of Illness and Injury Surveillance Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Frome E.L., Watkins J.P., Ellis E.D.

2012-12-12

The Department of Energy (DOE) uses illness and injury surveillance to monitor morbidity and assess the overall health of the work force. Data collected from each participating site include health events and a roster file with demographic information. The source data files are maintained in a relational data base, and are used to obtain stratified tables of health event counts and person time at risk that serve as the starting point for Poisson regression analysis. The explanatory variables that define these tables are age, gender, occupational group, and time. Typical response variables of interest are the number of absences duemore » to illness or injury, i.e., the response variable is a count. Poisson regression methods are used to describe the effect of the explanatory variables on the health event rates using a log-linear main effects model. Results of fitting the main effects model are summarized in a tabular and graphical form and interpretation of model parameters is provided. An analysis of deviance table is used to evaluate the importance of each of the explanatory variables on the event rate of interest and to determine if interaction terms should be considered in the analysis. Although Poisson regression methods are widely used in the analysis of count data, there are situations in which over-dispersion occurs. This could be due to lack-of-fit of the regression model, extra-Poisson variation, or both. A score test statistic and regression diagnostics are used to identify over-dispersion. A quasi-likelihood method of moments procedure is used to evaluate and adjust for extra-Poisson variation when necessary. Two examples are presented using respiratory disease absence rates at two DOE sites to illustrate the methods and interpretation of the results. In the first example the Poisson main effects model is adequate. In the second example the score test indicates considerable over-dispersion and a more detailed analysis attributes the over-dispersion to extra-Poisson variation. The R open source software environment for statistical computing and graphics is used for analysis. Additional details about R and the data that were used in this report are provided in an Appendix. Information on how to obtain R and utility functions that can be used to duplicate results in this report are provided.« less

Post Hoc Analyses of ApoE Genotype-Defined Subgroups in Clinical Trials.

PubMed

Kennedy, Richard E; Cutter, Gary R; Wang, Guoqiao; Schneider, Lon S

2016-01-01

Many post hoc analyses of clinical trials in Alzheimer's disease (AD) and mild cognitive impairment (MCI) are in small Phase 2 trials. Subject heterogeneity may lead to statistically significant post hoc results that cannot be replicated in larger follow-up studies. We investigated the extent of this problem using simulation studies mimicking current trial methods with post hoc analyses based on ApoE4 carrier status. We used a meta-database of 24 studies, including 3,574 subjects with mild AD and 1,171 subjects with MCI/prodromal AD, to simulate clinical trial scenarios. Post hoc analyses examined if rates of progression on the Alzheimer's Disease Assessment Scale-cognitive (ADAS-cog) differed between ApoE4 carriers and non-carriers. Across studies, ApoE4 carriers were younger and had lower baseline scores, greater rates of progression, and greater variability on the ADAS-cog. Up to 18% of post hoc analyses for 18-month trials in AD showed greater rates of progression for ApoE4 non-carriers that were statistically significant but unlikely to be confirmed in follow-up studies. The frequency of erroneous conclusions dropped below 3% with trials of 100 subjects per arm. In MCI, rates of statistically significant differences with greater progression in ApoE4 non-carriers remained below 3% unless sample sizes were below 25 subjects per arm. Statistically significant differences for ApoE4 in post hoc analyses often reflect heterogeneity among small samples rather than true differential effect among ApoE4 subtypes. Such analyses must be viewed cautiously. ApoE genotype should be incorporated into the design stage to minimize erroneous conclusions.

An Empirical Study of Presage Variables in the Teaching-Learning of Statistics, in the Light of Research on Competencies

ERIC Educational Resources Information Center

Rodriguez, Clemente; Gutierrez-Perez, Jose; Pozo, Teresa

2010-01-01

Introduction: This research seeks to determine the influence exercised by a set of presage and process variables (students' pre-existing opinion towards statistics, their dedication to mastery of statistics content, assessment of the teaching materials, and the teacher's effort in the teaching of statistics) in students' resolution of activities…

Developing Students' Reasoning about Samples and Sampling Variability as a Path to Expert Statistical Thinking

ERIC Educational Resources Information Center

Garfield, Joan; Le, Laura; Zieffler, Andrew; Ben-Zvi, Dani

2015-01-01

This paper describes the importance of developing students' reasoning about samples and sampling variability as a foundation for statistical thinking. Research on expert-novice thinking as well as statistical thinking is reviewed and compared. A case is made that statistical thinking is a type of expert thinking, and as such, research…

An Update on Statistical Boosting in Biomedicine.

PubMed

Mayr, Andreas; Hofner, Benjamin; Waldmann, Elisabeth; Hepp, Tobias; Meyer, Sebastian; Gefeller, Olaf

2017-01-01

Statistical boosting algorithms have triggered a lot of research during the last decade. They combine a powerful machine learning approach with classical statistical modelling, offering various practical advantages like automated variable selection and implicit regularization of effect estimates. They are extremely flexible, as the underlying base-learners (regression functions defining the type of effect for the explanatory variables) can be combined with any kind of loss function (target function to be optimized, defining the type of regression setting). In this review article, we highlight the most recent methodological developments on statistical boosting regarding variable selection, functional regression, and advanced time-to-event modelling. Additionally, we provide a short overview on relevant applications of statistical boosting in biomedicine.

Generic Feature Selection with Short Fat Data

PubMed Central

Clarke, B.; Chu, J.-H.

2014-01-01

SUMMARY Consider a regression problem in which there are many more explanatory variables than data points, i.e., p ≫ n. Essentially, without reducing the number of variables inference is impossible. So, we group the p explanatory variables into blocks by clustering, evaluate statistics on the blocks and then regress the response on these statistics under a penalized error criterion to obtain estimates of the regression coefficients. We examine the performance of this approach for a variety of choices of n, p, classes of statistics, clustering algorithms, penalty terms, and data types. When n is not large, the discrimination over number of statistics is weak, but computations suggest regressing on approximately [n/K] statistics where K is the number of blocks formed by a clustering algorithm. Small deviations from this are observed when the blocks of variables are of very different sizes. Larger deviations are observed when the penalty term is an Lq norm with high enough q. PMID:25346546

Black-White Differences in Child Maltreatment Reports and Foster Care Placements: A Statistical Decomposition Using Linked Administrative Data.

PubMed

Maloney, Tim; Jiang, Nan; Putnam-Hornstein, Emily; Dalton, Erin; Vaithianathan, Rhema

2017-03-01

Introduction Official statistics have confirmed that relative to their presence in the population and relative to white children, black children have consistently higher rates of contact with child protective services (CPS). We used linked administrative data and statistical decomposition techniques to generate new insights into black and white differences in child maltreatment reports and foster care placements. Methods Birth records for all children born in Allegheny County, Pennsylvania, between 2008 and 2010 were linked to administrative service records originating in multiple county data systems. Differences in rates of involvement with child protective services between black and white children by age 4 were decomposed using nonlinear regression techniques. Results Black children had rates of CPS involvement that were 3 times higher than white children. Racial differences were explained solely by parental marital status (i.e., being unmarried) and age at birth (i.e., predominantly teenage mothers). Adding other covariates did not capture any further racial differences in maltreatment reporting or foster care placement rates, they simply shifted differences already explained by marital status and age to these other variables. Discussion Racial differences in rates of maltreatment reports and foster care placements can be explained by a basic model that adjusts only for parental marital status and age at the time of birth. Increasing access to early prevention services for vulnerable families may reduce disparities in child protective service involvement. Using birth records linked to other administrative data sources provides an important means to developing population-based research.

Environmental statistics and optimal regulation

NASA Astrophysics Data System (ADS)

Sivak, David; Thomson, Matt

2015-03-01

The precision with which an organism can detect its environment, and the timescale for and statistics of environmental change, will affect the suitability of different strategies for regulating protein levels in response to environmental inputs. We propose a general framework--here applied to the enzymatic regulation of metabolism in response to changing nutrient concentrations--to predict the optimal regulatory strategy given the statistics of fluctuations in the environment and measurement apparatus, and the costs associated with enzyme production. We find: (i) relative convexity of enzyme expression cost and benefit influences the fitness of thresholding or graded responses; (ii) intermediate levels of measurement uncertainty call for a sophisticated Bayesian decision rule; and (iii) in dynamic contexts, intermediate levels of uncertainty call for retaining memory of the past. Statistical properties of the environment, such as variability and correlation times, set optimal biochemical parameters, such as thresholds and decay rates in signaling pathways. Our framework provides a theoretical basis for interpreting molecular signal processing algorithms and a classification scheme that organizes known regulatory strategies and may help conceptualize heretofore unknown ones.

Facet-Dependent Oxidative Goethite Growth As a Function of Aqueous Solution Conditions.

PubMed

Strehlau, Jennifer H; Stemig, Melissa S; Penn, R Lee; Arnold, William A

2016-10-04

Nitroaromatic compounds are groundwater pollutants that can be degraded through reactions with Fe(II) adsorbed on iron oxide nanoparticles, although little is known about the evolving reactivity of the minerals with continuous pollutant exposure. In this work, Fe(II)/goethite reactivity toward 4-chloronitrobenzene (4-ClNB) as a function of pH, organic matter presence, and reactant concentrations was explored using sequential-spike batch reactors. Reaction rate constants were smaller with lower pH, introduction of organic matter, and diluted reactant concentrations as compared to a reference condition. Reaction rate constants did not change with the number of 4-ClNB spikes for all reaction conditions. Under all conditions, oxidative goethite growth was demonstrated through X-ray diffraction, magnetic characterization, and transmission electron microscopy. Nonparametric statistics were applied to compare histograms of lengths and widths of goethite nanoparticles as a function of varied solution conditions. The conditions that slowed the reaction also resulted in statistically shorter and wider particles than for the faster reactions. Additionally, added organic matter interfered with particle growth on the favorable {021} faces to a greater extent, with statistically reduced rate of growth on the tip facets and increased rate of growth on the side facets. These data demonstrate that oxidative growth of goethite in aqueous systems is dependent on major groundwater variables, such as pH and the presence of organic matter, which could lead to the evolving reactivity of goethite particles in natural environments.

Maximum likelihood methods for investigating reporting rates of rings on hunter-shot birds

USGS Publications Warehouse

Conroy, M.J.; Morgan, B.J.T.; North, P.M.

1985-01-01

It is well known that hunters do not report 100% of the rings that they find on shot birds. Reward studies can be used to estimate what this reporting rate is, by comparison of recoveries of rings offering a monetary reward, to ordinary rings. A reward study of American Black Ducks (Anas rubripes) is used to illustrate the design, and to motivate the development of statistical models for estimation and for testing hypotheses of temporal and geographic variation in reporting rates. The method involves indexing the data (recoveries) and parameters (reporting, harvest, and solicitation rates) by geographic and temporal strata. Estimates are obtained under unconstrained (e.g., allowing temporal variability in reporting rates) and constrained (e.g., constant reporting rates) models, and hypotheses are tested by likelihood ratio. A FORTRAN program, available from the author, is used to perform the computations.

Quantile regression applied to spectral distance decay

USGS Publications Warehouse

Rocchini, D.; Cade, B.S.

2008-01-01

Remotely sensed imagery has long been recognized as a powerful support for characterizing and estimating biodiversity. Spectral distance among sites has proven to be a powerful approach for detecting species composition variability. Regression analysis of species similarity versus spectral distance allows us to quantitatively estimate the amount of turnover in species composition with respect to spectral and ecological variability. In classical regression analysis, the residual sum of squares is minimized for the mean of the dependent variable distribution. However, many ecological data sets are characterized by a high number of zeroes that add noise to the regression model. Quantile regressions can be used to evaluate trend in the upper quantiles rather than a mean trend across the whole distribution of the dependent variable. In this letter, we used ordinary least squares (OLS) and quantile regressions to estimate the decay of species similarity versus spectral distance. The achieved decay rates were statistically nonzero (p < 0.01), considering both OLS and quantile regressions. Nonetheless, the OLS regression estimate of the mean decay rate was only half the decay rate indicated by the upper quantiles. Moreover, the intercept value, representing the similarity reached when the spectral distance approaches zero, was very low compared with the intercepts of the upper quantiles, which detected high species similarity when habitats are more similar. In this letter, we demonstrated the power of using quantile regressions applied to spectral distance decay to reveal species diversity patterns otherwise lost or underestimated by OLS regression. ?? 2008 IEEE.

Spectral distance decay: Assessing species beta-diversity by quantile regression

USGS Publications Warehouse

Rocchinl, D.; Nagendra, H.; Ghate, R.; Cade, B.S.

2009-01-01

Remotely sensed data represents key information for characterizing and estimating biodiversity. Spectral distance among sites has proven to be a powerful approach for detecting species composition variability. Regression analysis of species similarity versus spectral distance may allow us to quantitatively estimate how beta-diversity in species changes with respect to spectral and ecological variability. In classical regression analysis, the residual sum of squares is minimized for the mean of the dependent variable distribution. However, many ecological datasets are characterized by a high number of zeroes that can add noise to the regression model. Quantile regression can be used to evaluate trend in the upper quantiles rather than a mean trend across the whole distribution of the dependent variable. In this paper, we used ordinary least square (ols) and quantile regression to estimate the decay of species similarity versus spectral distance. The achieved decay rates were statistically nonzero (p < 0.05) considering both ols and quantile regression. Nonetheless, ols regression estimate of mean decay rate was only half the decay rate indicated by the upper quantiles. Moreover, the intercept value, representing the similarity reached when spectral distance approaches zero, was very low compared with the intercepts of upper quantiles, which detected high species similarity when habitats are more similar. In this paper we demonstrated the power of using quantile regressions applied to spectral distance decay in order to reveal species diversity patterns otherwise lost or underestimated by ordinary least square regression. ?? 2009 American Society for Photogrammetry and Remote Sensing.

Effects of music on patients undergoing a C-clamp procedure after percutaneous coronary interventions.

PubMed

Chan, Moon Fai; Wong, Oi Chi; Chan, Hoi Lam; Fong, Mei Chu; Lai, Suet Yan; Lo, Ching Wah; Ho, Siu Mei; Ng, Suk Ying; Leung, Suk Kit

2006-03-01

This paper reports a study to determine the effect of music on physiological parameters and level of pain in patients undergoing application of a C-clamp after percutaneous coronary interventions. Most percutaneous coronary interventions are performed through the femoral artery. In order to stop bleeding and achieve homeostasis, a C-clamp is used after percutaneous coronary interventions. However, the experience is painful for patients and they inevitably suffer discomfort. Pain may lead to stress responses and may affect the physical and mental health of patients. One potential beneficial practice is having the patient listen to relaxing music, which might have the effect of reducing situational discomfort and pain. A randomized controlled study was conducted during the period September 2004 to March 2005. Forty-three people (20 experimental and 23 control) were recruited from the intensive care units of two acute care hospitals in Hong Kong. Physiological and psychological variables were collected at baseline and at 15, 30 and 45 minutes. In the music group, there were statistically significant reductions (P=0.001) in heart rate, respiratory rate, and oxygen saturation than the control participants at 45 minutes. In the music group, statistically significant reductions (P=0.001) in systolic blood pressure, heart rate, respiratory rate and oxygen saturation were found at the four time points, but not in the control group. No statistically significant differences were found at baseline comparison of the two groups, but statistically significant differences in pain scores were found at 45 minutes for participants in the music group compared with the control group (P=0.003). Participants in the control group showed statistically significant increases in pain at 45 minutes compared with baseline (P<0.001). The benefits of preventing physiological reactions to pain were demonstrated. Music is a simple, safe and effective method of reducing potentially harmful physiological and psychological responses arising from pain.

Simulation of relationship between river discharge and sediment yield in the semi-arid river watersheds

NASA Astrophysics Data System (ADS)

Khaleghi, Mohammad Reza; Varvani, Javad

2018-02-01

Complex and variable nature of the river sediment yield caused many problems in estimating the long-term sediment yield and problems input into the reservoirs. Sediment Rating Curves (SRCs) are generally used to estimate the suspended sediment load of the rivers and drainage watersheds. Since the regression equations of the SRCs are obtained by logarithmic retransformation and have a little independent variable in this equation, they also overestimate or underestimate the true sediment load of the rivers. To evaluate the bias correction factors in Kalshor and Kashafroud watersheds, seven hydrometric stations of this region with suitable upstream watershed and spatial distribution were selected. Investigation of the accuracy index (ratio of estimated sediment yield to observed sediment yield) and the precision index of different bias correction factors of FAO, Quasi-Maximum Likelihood Estimator (QMLE), Smearing, and Minimum-Variance Unbiased Estimator (MVUE) with LSD test showed that FAO coefficient increases the estimated error in all of the stations. Application of MVUE in linear and mean load rating curves has not statistically meaningful effects. QMLE and smearing factors increased the estimated error in mean load rating curve, but that does not have any effect on linear rating curve estimation.

Economic Statistical Design of Integrated X-bar-S Control Chart with Preventive Maintenance and General Failure Distribution

PubMed Central

Caballero Morales, Santiago Omar

2013-01-01

The application of Preventive Maintenance (PM) and Statistical Process Control (SPC) are important practices to achieve high product quality, small frequency of failures, and cost reduction in a production process. However there are some points that have not been explored in depth about its joint application. First, most SPC is performed with the X-bar control chart which does not fully consider the variability of the production process. Second, many studies of design of control charts consider just the economic aspect while statistical restrictions must be considered to achieve charts with low probabilities of false detection of failures. Third, the effect of PM on processes with different failure probability distributions has not been studied. Hence, this paper covers these points, presenting the Economic Statistical Design (ESD) of joint X-bar-S control charts with a cost model that integrates PM with general failure distribution. Experiments showed statistically significant reductions in costs when PM is performed on processes with high failure rates and reductions in the sampling frequency of units for testing under SPC. PMID:23527082

Flame thickness and conditional scalar dissipation rate in a premixed temporal turbulent reacting jet

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chaudhuri, Swetaprovo; Kolla, Hemanth; Dave, Himanshu L.

The flame structure corresponding to lean hydrogen–air premixed flames in intense sheared turbulence in the thin reaction zone regime is quantified from flame thickness and conditional scalar dissipation rate statistics, obtained from recent direct numerical simulation data of premixed temporally-evolving turbulent slot jet flames. It is found that, on average, these sheared turbulent flames are thinner than their corresponding planar laminar flames. Extensive analysis is performed to identify the reason for this counter-intuitive thinning effect. The factors controlling the flame thickness are analyzed through two different routes i.e., the kinematic route, and the transport and chemical kinetics route. The kinematicmore » route is examined by comparing the statistics of the normal strain rate due to fluid motion with the statistics of the normal strain rate due to varying flame displacement speed or self-propagation. It is found that while the fluid normal straining is positive and tends to separate iso-scalar surfaces, the dominating normal strain rate due to self-propagation is negative and tends to bring the iso-scalar surfaces closer resulting in overall thinning of the flame. The transport and chemical kinetics route is examined by studying the non-unity Lewis number effect on the premixed flames. The effects from the kinematic route are found to couple with the transport and chemical kinetics route. In addition, the intermittency of the conditional scalar dissipation rate is also examined. It is found to exhibit a unique non-monotonicity of the exponent of the stretched exponential function, conventionally used to describe probability density function tails of such variables. As a result, the non-monotonicity is attributed to the detailed chemical structure of hydrogen-air flames in which heat release occurs close to the unburnt reactants at near free-stream temperatures.« less

Flame thickness and conditional scalar dissipation rate in a premixed temporal turbulent reacting jet

DOE PAGES

Chaudhuri, Swetaprovo; Kolla, Hemanth; Dave, Himanshu L.; ...

2017-07-07

The flame structure corresponding to lean hydrogen–air premixed flames in intense sheared turbulence in the thin reaction zone regime is quantified from flame thickness and conditional scalar dissipation rate statistics, obtained from recent direct numerical simulation data of premixed temporally-evolving turbulent slot jet flames. It is found that, on average, these sheared turbulent flames are thinner than their corresponding planar laminar flames. Extensive analysis is performed to identify the reason for this counter-intuitive thinning effect. The factors controlling the flame thickness are analyzed through two different routes i.e., the kinematic route, and the transport and chemical kinetics route. The kinematicmore » route is examined by comparing the statistics of the normal strain rate due to fluid motion with the statistics of the normal strain rate due to varying flame displacement speed or self-propagation. It is found that while the fluid normal straining is positive and tends to separate iso-scalar surfaces, the dominating normal strain rate due to self-propagation is negative and tends to bring the iso-scalar surfaces closer resulting in overall thinning of the flame. The transport and chemical kinetics route is examined by studying the non-unity Lewis number effect on the premixed flames. The effects from the kinematic route are found to couple with the transport and chemical kinetics route. In addition, the intermittency of the conditional scalar dissipation rate is also examined. It is found to exhibit a unique non-monotonicity of the exponent of the stretched exponential function, conventionally used to describe probability density function tails of such variables. As a result, the non-monotonicity is attributed to the detailed chemical structure of hydrogen-air flames in which heat release occurs close to the unburnt reactants at near free-stream temperatures.« less

Union rate of tibiotalocalcaneal nails with internal or external bone stimulation.

PubMed

De Vries, J George; Berlet, Gregory C; Hyer, Christopher F

2012-11-01

The use of bone growth stimulation has been reported in the application of hindfoot and ankle arthrodesis. Most studies have been retrospective case series with few patients. The authors present a comparative analysis of patients undergoing tibiotalocalcaneal (TTC) arthrodesis via a retrograde intramedullary arthrodesis nail to evaluate the influence of internal versus external bone stimulation in this population. One hundred fifty-four patients were treated with retrograde intramedullary nailing. A comprehensive chart and radiographic review was performed from a database of patients who underwent TTC fusion with or without bone stimulation. Ninety-one patients with retrograde TTC nailing were treated with direct current internal bone stimulation at the time of the index procedure (internal group) and 63 were treated with combined magnetic field external bone stimulation (external group). The primary end point was fusion with potential variables evaluated for influence on fusion rates. Demographically the cohorts were similar groups in age and comorbidities. Surgical and outcome data were examined, and there were few statistically significant differences between the two groups. There was no statistically significant difference in rate of union (52.7% and 57.1%, p = .63) or rate of complications between the internal and external groups. Overall, the success rate for achieving a stable, functional limb for the groups was 81.3% (74/91 patients) and 82.5% (52/63 patients) in the internal and external groups, respectively (p = .62). The authors demonstrated there were no statistically significant differences between the union and complication rate when comparing these types of internal and external bone stimulation in this patient population. Consideration of these results may help guide physicians when considering bone stimulation as an adjunct to TTC fusions with a retrograde intramedullary nail.

Interpreting the concordance statistic of a logistic regression model: relation to the variance and odds ratio of a continuous explanatory variable.

PubMed

Austin, Peter C; Steyerberg, Ewout W

2012-06-20

When outcomes are binary, the c-statistic (equivalent to the area under the Receiver Operating Characteristic curve) is a standard measure of the predictive accuracy of a logistic regression model. An analytical expression was derived under the assumption that a continuous explanatory variable follows a normal distribution in those with and without the condition. We then conducted an extensive set of Monte Carlo simulations to examine whether the expressions derived under the assumption of binormality allowed for accurate prediction of the empirical c-statistic when the explanatory variable followed a normal distribution in the combined sample of those with and without the condition. We also examine the accuracy of the predicted c-statistic when the explanatory variable followed a gamma, log-normal or uniform distribution in combined sample of those with and without the condition. Under the assumption of binormality with equality of variances, the c-statistic follows a standard normal cumulative distribution function with dependence on the product of the standard deviation of the normal components (reflecting more heterogeneity) and the log-odds ratio (reflecting larger effects). Under the assumption of binormality with unequal variances, the c-statistic follows a standard normal cumulative distribution function with dependence on the standardized difference of the explanatory variable in those with and without the condition. In our Monte Carlo simulations, we found that these expressions allowed for reasonably accurate prediction of the empirical c-statistic when the distribution of the explanatory variable was normal, gamma, log-normal, and uniform in the entire sample of those with and without the condition. The discriminative ability of a continuous explanatory variable cannot be judged by its odds ratio alone, but always needs to be considered in relation to the heterogeneity of the population.

Neighbourhood non-employment and daily smoking: a population-based study of women and men in Sweden.

PubMed

Ohlander, Emma; Vikström, Max; Lindström, Martin; Sundquist, Kristina

2006-02-01

To examine whether neighbourhood non-employment is associated with daily smoking after adjustment for individual characteristics, such as employment status. Cross-sectional study of a simple, random sample of 31,164 women and men aged 25-64, representative of the entire population in Sweden. Data were collected from the years 1993-2000. The individual variables included age, sex, employment status, occupation and housing tenure. Logistic regression was used in the analysis with neighbourhood non-employment rates measured at small area market statistics level. There was a significant association between neighbourhood non-employment rates and daily smoking for both women and men. After adjustment for employment status and housing tenure the odds ratios of daily smoking were 1.39 (95% CI = 1.22-1.58) for women and 1.41 (95% CI = 1.23-1.61) for men living in neighbourhoods with the highest non-employment rates. The individual variables of unemployment, low occupational level and renting were associated with daily smoking. Neighbourhood non-employment is associated with daily smoking. Smoking prevention in primary health care should address both individuals and neighbourhoods.

Effects of dance movement therapy on selected cardiovascular parameters and estimated maximum oxygen consumption in hypertensive patients.

PubMed

Aweto, H A; Owoeye, O B A; Akinbo, S R A; Onabajo, A A

2012-01-01

Objective:Arterial hypertension is a medical condition associated with increased risks of of death, cardiovascular mortality and cardiovascular morbidity including stroke, coronary heart disease, atrial fibrillation and renal insufficiency. Regular physical exercise is considered to be an important part of the non-pharmacologictreatment of hypertension. The purpose of this study was to investigate the effects of dance movement therapy (DMT) on selected cardiovascular parameters and estimated maximum oxygen consumption in hypertensive patients. Fifty (50) subjects with hypertension participated in the study. They were randomly assigned to 2 equal groups; A (DMT group) and B (Control group). Group A carried out dance movement therapy 2 times a week for 4 weeks while group B underwent some educational sessions 2 times a week for the same duration. All the subjects were on anti-hypertensive drugs. 38 subjects completed the study with the DMTgroup having a total of 23 subjects (10 males and 13 females) and the control group 15 subjects (6 males and 9 females). Descriptive statistics of mean, standard deviation and inferential statistics of paired and independentt-testwere used for data analysis. Following four weeks of dance movement therapy, paired t-test analysis showed that there was a statistically significant difference in the Resting systolic blood pressure (RSBP) (p < 0.001*), Resting diastolic blood pressure (RDBP) (p < 0.001*), Resting heart rate (RHR) (p = 0.024*), Maximum heart rate (MHR) (p=0.002*) and Estimated oxygen consumption (VO2max) (p = 0.023*) in subjects in group A (p < 0.05) while there was no significant difference observed in outcome variables of subjects in group B (p > 0.05). Independent t-test analysis between the differences in the pre and post intervention scores of groups A and B also showed statistically significant differences in all the outcome variables (p <0.05). DMT was effective in improving cardiovascular parameters and estimated maximum oxygen consumption in hypertensive patients.

Impact of obsessive-compulsive disorder comorbidity on the sociodemographic and clinical features of patients with bipolar disorder.

PubMed

Koyuncu, Ahmet; Tükel, Raşit; Ozyildirim, Ilker; Meteris, Handan; Yazici, Olcay

2010-01-01

In this study, our aim is to determine the prevalence rates of obsessive-compulsive disorder (OCD) comorbidity and to assess the impact of OCD comorbidity on the sociodemographic and clinical features of patients with bipolar disorder (BD). Using the Yale-Brown Obsessive Compulsive Scale Symptom Checklist and Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition-IV/Clinical Version on bipolar patients, 2 groups, BD with OCD comorbidity (BD-OCD) and BD without OCD comorbidity, were formed. These groups were compared for sociodemographic and clinical variables. Of 214 patients with BD, 21.9% of them had obsession and/or compulsion symptoms and 16.3% had symptoms at the OCD level. Although there was no statistically significant difference between the frequency of comorbid OCD in BD-I (22/185, 11.9%) and BD-II (3/13, 23.1%) patients, but OCD was found to be significantly high in BD not otherwise specified (10/16, %62.5) patients than BD-I (P < .001) and BD-II (P = .03). Six patients (17.1%) of the BD-OCD group had chronic course (the presence of at least 1 mood disorder episode with a duration of longer than 2 years), whereas the BD without OCD group had none, which was statistically significant. There were no statistically significant differences between BD-OCD and BD without OCD groups in terms of age, sex, education, marital status, polarity, age of BD onset, presence of psychotic symptoms, presence of rapid cycling, history of suicide attempts, first episode type, and predominant episode type. Main limitation of our study was the assessment of some variables based on retrospective recall. Our study confirms the high comorbidity rates for OCD in BD patients. Future studies that examine the relationship between OCD and BD using a longitudinal design may be helpful in improving our understanding of the mechanism of this association. 2010 Elsevier Inc. All rights reserved.

An Easy Tool to Predict Survival in Patients Receiving Radiation Therapy for Painful Bone Metastases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Westhoff, Paulien G., E-mail: p.g.westhoff@umcutrecht.nl; Graeff, Alexander de; Monninkhof, Evelyn M.

2014-11-15

Purpose: Patients with bone metastases have a widely varying survival. A reliable estimation of survival is needed for appropriate treatment strategies. Our goal was to assess the value of simple prognostic factors, namely, patient and tumor characteristics, Karnofsky performance status (KPS), and patient-reported scores of pain and quality of life, to predict survival in patients with painful bone metastases. Methods and Materials: In the Dutch Bone Metastasis Study, 1157 patients were treated with radiation therapy for painful bone metastases. At randomization, physicians determined the KPS; patients rated general health on a visual analogue scale (VAS-gh), valuation of life on amore » verbal rating scale (VRS-vl) and pain intensity. To assess the predictive value of the variables, we used multivariate Cox proportional hazard analyses and C-statistics for discriminative value. Of the final model, calibration was assessed. External validation was performed on a dataset of 934 patients who were treated with radiation therapy for vertebral metastases. Results: Patients had mainly breast (39%), prostate (23%), or lung cancer (25%). After a maximum of 142 weeks' follow-up, 74% of patients had died. The best predictive model included sex, primary tumor, visceral metastases, KPS, VAS-gh, and VRS-vl (C-statistic = 0.72, 95% CI = 0.70-0.74). A reduced model, with only KPS and primary tumor, showed comparable discriminative capacity (C-statistic = 0.71, 95% CI = 0.69-0.72). External validation showed a C-statistic of 0.72 (95% CI = 0.70-0.73). Calibration of the derivation and the validation dataset showed underestimation of survival. Conclusion: In predicting survival in patients with painful bone metastases, KPS combined with primary tumor was comparable to a more complex model. Considering the amount of variables in complex models and the additional burden on patients, the simple model is preferred for daily use. In addition, a risk table for survival is provided.« less

The impact of high progesterone levels on the day of HCG administration in assisted human reproduction treatments.

PubMed

Tanada, Michelli S; Yoshida, Ivan H; Santos, Monise; Berton, Caroline Z; Souto, Elen; Carvalho, Waldemar P de; Cordts, Emerson B; Barbosa, Caio P

2018-06-01

Progesterone is a steroid hormone that acts on the endometrium. It is known for producing physical and mood-related side effects. Few studies have looked into how progesterone levels affect embryo development and quality. This study aimed to find a cutoff level for serum progesterone on the day of HCG administration from which embryo quality is impaired. The study included 145 cycles, from which 885 oocytes and 613 embryos were obtained. All patients had their serum progesterone levels measured on the day of HCG administration. Data sets were collected from patient medical records. The chi-square test was used to assess qualitative variables and the Mann-Whitney test to evaluate quantitative variables. Statistical analysis revealed that serum progesterone levels and reproductive variables were not significantly associated. In regards to oocyte maturity, however, when progesterone levels were greater than 1.3 ng/mL the probability of oocytes being immature increased by 12.7%. The fragmentation rate of embryos categorized as "top quality" in D3 increased proportionately to increases in progesterone levels (12.23%). High progesterone levels appeared to be correlated with increased embryo fragmentation rates, but high serum levels of the hormone on the day of HCG administration had no impact on reproductive variables and were not associated with impaired embryo development.

Predicting Satisfaction for Unicompartmental Knee Arthroplasty Patients in an Asian Population.

PubMed

Lee, Merrill; Huang, Yilun; Chong, Hwei Chi; Ning, Yilin; Lo, Ngai Nung; Yeo, Seng Jin

2016-08-01

Despite renewed interest in unicompartmental knee arthroplasty (UKA), there is a paucity of published literature with regard to patient satisfaction after UKA within Asian populations. The purpose of this study is to identify characteristics and factors which may contribute to patient dissatisfaction after UKA in a multiracial Asian population. Seven hundred twenty-four UKAs were performed between January 2007 and April 2013. Preoperative and postoperative variables were prospectively captured, such as standardized knee scores, knee range of motion, and patient satisfaction scores. These variables were then analyzed with a multiple logistic regression model to determine statistically significant factors contributing to patients' satisfaction. Minimum duration of follow-up was 2 years, with an overall patient satisfaction rate of 92.2%. There was improvement in mean knee range of motion and across various standardized knee scores. Preoperative variables associated with patient dissatisfaction included a poorer preoperative Mental Component Summary, better preoperative knee extension, and better preoperative Oxford Knee Scores. Significant postoperative variables included better Oxford Knee Score at 6 months and Mental Component Summary at 2 years. Despite the impressive patient satisfaction rate of UKA in this Asian population, these findings suggest that there is a targeted group of patients with select preoperative factors who would benefit from preoperative counseling. Copyright © 2016 Elsevier Inc. All rights reserved.

Permutation modulation for quantization and information reconciliation in CV-QKD systems

NASA Astrophysics Data System (ADS)

Daneshgaran, Fred; Mondin, Marina; Olia, Khashayar

2017-08-01

This paper is focused on the problem of Information Reconciliation (IR) for continuous variable Quantum Key Distribution (QKD). The main problem is quantization and assignment of labels to the samples of the Gaussian variables observed at Alice and Bob. Trouble is that most of the samples, assuming that the Gaussian variable is zero mean which is de-facto the case, tend to have small magnitudes and are easily disturbed by noise. Transmission over longer and longer distances increases the losses corresponding to a lower effective Signal to Noise Ratio (SNR) exasperating the problem. Here we propose to use Permutation Modulation (PM) as a means of quantization of Gaussian vectors at Alice and Bob over a d-dimensional space with d ≫ 1. The goal is to achieve the necessary coding efficiency to extend the achievable range of continuous variable QKD by quantizing over larger and larger dimensions. Fractional bit rate per sample is easily achieved using PM at very reasonable computational cost. Ordered statistics is used extensively throughout the development from generation of the seed vector in PM to analysis of error rates associated with the signs of the Gaussian samples at Alice and Bob as a function of the magnitude of the observed samples at Bob.

Investigation of the Process Conditions for Hydrogen Production by Steam Reforming of Glycerol over Ni/Al₂O₃ Catalyst Using Response Surface Methodology (RSM).

PubMed

Ebshish, Ali; Yaakob, Zahira; Taufiq-Yap, Yun Hin; Bshish, Ahmed

2014-03-19

In this work; a response surface methodology (RSM) was implemented to investigate the process variables in a hydrogen production system. The effects of five independent variables; namely the temperature (X₁); the flow rate (X₂); the catalyst weight (X₃); the catalyst loading (X₄) and the glycerol-water molar ratio (X₅) on the H₂ yield (Y₁) and the conversion of glycerol to gaseous products (Y₂) were explored. Using multiple regression analysis; the experimental results of the H₂ yield and the glycerol conversion to gases were fit to quadratic polynomial models. The proposed mathematical models have correlated the dependent factors well within the limits that were being examined. The best values of the process variables were a temperature of approximately 600 °C; a feed flow rate of 0.05 mL/min; a catalyst weight of 0.2 g; a catalyst loading of 20% and a glycerol-water molar ratio of approximately 12; where the H₂ yield was predicted to be 57.6% and the conversion of glycerol was predicted to be 75%. To validate the proposed models; statistical analysis using a two-sample t -test was performed; and the results showed that the models could predict the responses satisfactorily within the limits of the variables that were studied.

Stochastic Individual-Based Modeling of Bacterial Growth and Division Using Flow Cytometry.

PubMed

García, Míriam R; Vázquez, José A; Teixeira, Isabel G; Alonso, Antonio A

2017-01-01

A realistic description of the variability in bacterial growth and division is critical to produce reliable predictions of safety risks along the food chain. Individual-based modeling of bacteria provides the theoretical framework to deal with this variability, but it requires information about the individual behavior of bacteria inside populations. In this work, we overcome this problem by estimating the individual behavior of bacteria from population statistics obtained with flow cytometry. For this objective, a stochastic individual-based modeling framework is defined based on standard assumptions during division and exponential growth. The unknown single-cell parameters required for running the individual-based modeling simulations, such as cell size growth rate, are estimated from the flow cytometry data. Instead of using directly the individual-based model, we make use of a modified Fokker-Plank equation. This only equation simulates the population statistics in function of the unknown single-cell parameters. We test the validity of the approach by modeling the growth and division of Pediococcus acidilactici within the exponential phase. Estimations reveal the statistics of cell growth and division using only data from flow cytometry at a given time. From the relationship between the mother and daughter volumes, we also predict that P. acidilactici divide into two successive parallel planes.

Probabilistic models for reactive behaviour in heterogeneous condensed phase media

NASA Astrophysics Data System (ADS)

Baer, M. R.; Gartling, D. K.; DesJardin, P. E.

2012-02-01

This work presents statistically-based models to describe reactive behaviour in heterogeneous energetic materials. Mesoscale effects are incorporated in continuum-level reactive flow descriptions using probability density functions (pdfs) that are associated with thermodynamic and mechanical states. A generalised approach is presented that includes multimaterial behaviour by treating the volume fraction as a random kinematic variable. Model simplifications are then sought to reduce the complexity of the description without compromising the statistical approach. Reactive behaviour is first considered for non-deformable media having a random temperature field as an initial state. A pdf transport relationship is derived and an approximate moment approach is incorporated in finite element analysis to model an example application whereby a heated fragment impacts a reactive heterogeneous material which leads to a delayed cook-off event. Modelling is then extended to include deformation effects associated with shock loading of a heterogeneous medium whereby random variables of strain, strain-rate and temperature are considered. A demonstrative mesoscale simulation of a non-ideal explosive is discussed that illustrates the joint statistical nature of the strain and temperature fields during shock loading to motivate the probabilistic approach. This modelling is derived in a Lagrangian framework that can be incorporated in continuum-level shock physics analysis. Future work will consider particle-based methods for a numerical implementation of this modelling approach.

Homicides by Police: Comparing Counts From the National Violent Death Reporting System, Vital Statistics, and Supplementary Homicide Reports

PubMed Central

Azrael, Deborah; Cohen, Amy; Miller, Matthew; Thymes, Deonza; Wang, David Enze; Hemenway, David

2016-01-01

Objective. To evaluate the National Violent Death Reporting System (NVDRS) as a surveillance system for homicides by law enforcement officers. Methods. We assessed sensitivity and positive predictive value of the NVDRS “type of death” variable against our study count of homicides by police, which we derived from NVDRS coded and narrative data for states participating in NVDRS 2005 to 2012. We compared state counts of police homicides from NVDRS, Vital Statistics, and Federal Bureau of Investigation Supplementary Homicide Reports. Results. We identified 1552 police homicides in the 16 states. Positive predictive value and sensitivity of the NVDRS “type of death” variable for police homicides were high (98% and 90%, respectively). Counts from Vital Statistics and Supplementary Homicide Reports were 58% and 48%, respectively, of our study total; gaps varied widely by state. The annual rate of police homicide (0.24/100 000) varied 5-fold by state and 8-fold by race/ethnicity. Conclusions. NVDRS provides more complete data on police homicides than do existing systems. Policy Implications. Expanding NVDRS to all 50 states and making 2 improvements we identify will be an efficient way to provide the nation with more accurate, detailed data on homicides by law enforcement. PMID:26985611

Adaptation to local ultraviolet radiation conditions among neighbouring Daphnia populations

PubMed Central

Miner, Brooks E.; Kerr, Benjamin

2011-01-01

Understanding the historical processes that generated current patterns of phenotypic diversity in nature is particularly challenging in subdivided populations. Populations often exhibit heritable genetic differences that correlate with environmental variables, but the non-independence among neighbouring populations complicates statistical inference of adaptation. To understand the relative influence of adaptive and non-adaptive processes in generating phenotypes requires joint evaluation of genetic and phenotypic divergence in an integrated and statistically appropriate analysis. We investigated phenotypic divergence, population-genetic structure and potential fitness trade-offs in populations of Daphnia melanica inhabiting neighbouring subalpine ponds of widely differing transparency to ultraviolet radiation (UVR). Using a combination of experimental, population-genetic and statistical techniques, we separated the effects of shared population ancestry and environmental variables in predicting phenotypic divergence among populations. We found that native water transparency significantly predicted divergence in phenotypes among populations even after accounting for significant population structure. This result demonstrates that environmental factors such as UVR can at least partially account for phenotypic divergence. However, a lack of evidence for a hypothesized trade-off between UVR tolerance and growth rates in the absence of UVR prevents us from ruling out the possibility that non-adaptive processes are partially responsible for phenotypic differentiation in this system. PMID:20943691

Statistically Characterizing Intra- and Inter-Individual Variability in Children with Developmental Coordination Disorder

ERIC Educational Resources Information Center

King, Bradley R.; Harring, Jeffrey R.; Oliveira, Marcio A.; Clark, Jane E.

2011-01-01

Previous research investigating children with Developmental Coordination Disorder (DCD) has consistently reported increased intra- and inter-individual variability during motor skill performance. Statistically characterizing this variability is not only critical for the analysis and interpretation of behavioral data, but also may facilitate our…

Prediction of Patient-Controlled Analgesic Consumption: A Multimodel Regression Tree Approach.

PubMed

Hu, Yuh-Jyh; Ku, Tien-Hsiung; Yang, Yu-Hung; Shen, Jia-Ying

2018-01-01

Several factors contribute to individual variability in postoperative pain, therefore, individuals consume postoperative analgesics at different rates. Although many statistical studies have analyzed postoperative pain and analgesic consumption, most have identified only the correlation and have not subjected the statistical model to further tests in order to evaluate its predictive accuracy. In this study involving 3052 patients, a multistrategy computational approach was developed for analgesic consumption prediction. This approach uses data on patient-controlled analgesia demand behavior over time and combines clustering, classification, and regression to mitigate the limitations of current statistical models. Cross-validation results indicated that the proposed approach significantly outperforms various existing regression methods. Moreover, a comparison between the predictions by anesthesiologists and medical specialists and those of the computational approach for an independent test data set of 60 patients further evidenced the superiority of the computational approach in predicting analgesic consumption because it produced markedly lower root mean squared errors.

Multivariate evaluation of the cutting performance of rotary instruments with electric and air-turbine handpieces.

PubMed

Funkenbusch, Paul D; Rotella, Mario; Chochlidakis, Konstantinos; Ercoli, Carlo

2016-10-01

Laboratory studies of tooth preparation often involve single values for all variables other than the one being tested. In contrast, in clinical settings, not all variables can be adequately controlled. For example, a new dental rotary cutting instrument may be tested in the laboratory by making a specific cut with a fixed force, but, in clinical practice, the instrument must make different cuts with individual dentists applying different forces. Therefore, the broad applicability of laboratory results to diverse clinical conditions is uncertain and the comparison of effects across studies difficult. The purpose of this in vitro study was to examine the effects of 9 process variables on the dental cutting of rotary cutting instruments used with an electric handpiece and compare them with those of a previous study that used an air-turbine handpiece. The effects of 9 key process variables on the efficiency of a simulated dental cutting operation were measured. A fractional factorial experiment was conducted by using an electric handpiece in a computer-controlled, dedicated testing apparatus to simulate dental cutting procedures with Macor blocks as the cutting substrate. Analysis of variance (ANOVA) was used to assess the statistical significance (α=.05). Four variables (targeted applied load, cut length, diamond grit size, and cut type) consistently produced large, statistically significant effects, whereas 5 variables (rotation per minute, number of cooling ports, rotary cutting instrument diameter, disposability, and water flow rate) produced relatively small, statistically insignificant effects. These results are generally similar to those previously found for an air-turbine handpiece. Regardless of whether an electric or air-turbine handpiece was used, the control exerted by the dentist, simulated in this study by targeting a specific level of applied force, was the single most important factor affecting cutting efficiency. Cutting efficiency was also significantly affected by factors simulating patient/clinical circumstances and hardware choices. These results highlight the greater importance of local clinical conditions (procedure, dentist) in understanding dental cutting as opposed to other hardware-related factors. Copyright © 2016 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

Predictors of outcome after elective endovascular abdominal aortic aneurysm repair and external validation of a risk prediction model.

PubMed

Wisniowski, Brendan; Barnes, Mary; Jenkins, Jason; Boyne, Nicholas; Kruger, Allan; Walker, Philip J

2011-09-01

Endovascular abdominal aortic aneurysm (AAA) repair (EVAR) has been associated with lower operative mortality and morbidity than open surgery but comparable long-term mortality and higher delayed complication and reintervention rates. Attention has therefore been directed to identifying preoperative and operative variables that influence outcomes after EVAR. Risk-prediction models, such as the EVAR Risk Assessment (ERA) model, have also been developed to help surgeons plan EVAR procedures. The aims of this study were (1) to describe outcomes of elective EVAR at the Royal Brisbane and Women's Hospital (RBWH), (2) to identify preoperative and operative variables predictive of outcomes after EVAR, and (3) to externally validate the ERA model. All elective EVAR procedures at the RBWH before July 1, 2009, were reviewed. Descriptive analyses were performed to determine the outcomes. Univariate and multivariate analyses were performed to identify preoperative and operative variables predictive of outcomes after EVAR. Binomial logistic regression analyses were used to externally validate the ERA model. Before July 1, 2009, 197 patients (172 men), who were a mean age of 72.8 years, underwent elective EVAR at the RBWH. Operative mortality was 1.0%. Survival was 81.1% at 3 years and 63.2% at 5 years. Multivariate analysis showed predictors of survival were age (P = .0126), American Society of Anesthesiologists (ASA) score (P = .0180), and chronic obstructive pulmonary disease (P = .0348) at 3 years and age (P = .0103), ASA score (P = .0006), renal failure (P = .0048), and serum creatinine (P = .0022) at 5 years. Aortic branch vessel score was predictive of initial (30-day) type II endoleak (P = .0015). AAA tortuosity was predictive of midterm type I endoleak (P = .0251). Female sex was associated with lower rates of initial clinical success (P = .0406). The ERA model fitted RBWH data well for early death (C statistic = .906), 3-year survival (C statistic = .735), 5-year survival (C statistic = .800), and initial type I endoleak (C statistic = .850). The outcomes of elective EVAR at the RBWH are broadly consistent with those of a nationwide Australian audit and recent randomized trials. Age and ASA score are independent predictors of midterm survival after elective EVAR. The ERA model predicts mortality-related outcomes and initial type I endoleak well for RBWH elective EVAR patients. Copyright © 2011 Society for Vascular Surgery. All rights reserved.

The rate of country-level improvements of the infant mortality rate is mainly determined by previous history.

PubMed

Bremberg, Sven G

2016-08-01

Studies of country-level determinants of health have produced conflicting results even when the analyses have been restricted to high-income counties. Yet, most of these studies have not taken historical, country-specific developments into account. Thus, it is appropriate to separate the influence of current exposures from historical aspects. Determinants of the infant mortality rate (IMR) were studied in 28 OECD countries over the period 1990-2012. Twelve determinants were selected. They refer to the level of general resources, resources that specifically address child health and characteristics that affect knowledge dissemination, including level of trust, and a health related behaviour: the rate of female smoking. Bivariate analyses with the IMR in year 2000 as outcome and the 12 determinants produced six statistically significant models. In multivariate analyses, the rate of decrease in the IMR was investigated as outcome and a history variable (IMR in 1990) was included in the models. The history variable alone explained 95% of the variation. None of the multivariate models, with the 12 determinants included, explained significantly more variation. Taking into account the historical development of the IMR will critically affect correlations between country-level determinants and the IMR. © The Author 2016. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

Comparison between medial rectus pulley fixation and augmented recession in children with convergence excess and variable-angle infantile esotropia.

PubMed

Fouad, Heba M; Abdelhakim, Mohamad A; Awadein, Ahmed; Elhilali, Hala

2016-10-01

To compare the outcomes of medial rectus (MR) muscle pulley fixation and augmented recession in children with convergence excess esotropia and variable-angle infantile esotropia. This was a prospective randomized interventional study in which children with convergence excess esotropia or variable-angle infantile esotropia were randomly allocated to either augmented MR muscle recession (augmented group) or MR muscle pulley posterior fixation (pulley group). In convergence excess, the MR recession was based on the average of distance and near angles of deviation with distance correction in the augmented group, and on the distance angle of deviation in the pulley group. In variable-angle infantile esotropia, the MR recession was based on the average of the largest and smallest angles in the augmented group and on the smallest angle in the pulley group. Pre- and postoperative ductions, versions, pattern strabismus, smallest and largest angles of deviation, and angle disparity were analyzed. Surgery was performed on 60 patients: 30 underwent bilateral augmented MR recession, and 30 underwent bilateral MR recession with pulley fixation. The success rate was statistically significantly higher (P = 0.037) in the pulley group (70%) than in the augmented group (40%). The postoperative smallest and largest angles and the angle disparity were statistically significantly lower in the pulley group than the augmented group (P < 0.01). Medial rectus muscle pulley fixation is a useful surgical step for addressing marked variability of the angle in variable angle esotropia and convergence excess esotropia. Copyright © 2016 American Association for Pediatric Ophthalmology and Strabismus. Published by Elsevier Inc. All rights reserved.

Assessment of left ventricular function in healthy Great Danes and in Great Danes with dilated cardiomyopathy using speckle tracking echocardiography.

PubMed

Pedro, B; Stephenson, H; Linney, C; Cripps, P; Dukes-McEwan, J

2017-08-01

Assess global circumferential and radial systolic and diastolic myocardial function with speckle tracking echocardiography (STE) in healthy Great Danes (GD) and in GD diagnosed with dilated cardiomyopathy (DCM). Eighty-nine GD were included in the study: 39 healthy (normal group [NORMg]) and 50 diagnosed with DCM (DCMg). This was a retrospective study. Signalment and echocardiographic diagnosis were obtained from the medical records of GD assessed between 2008 and 2012. Speckle tracking echocardiography analysis of circumferential (C) and radial (R) strain (St) and strain rate (SR) in systole (S), early (E) and late (A) diastole was performed at the levels of the mitral valve (MV), papillary muscles (PM) and apex (Ap) of the left ventricle. Univariable and multivariable analysis was performed to identify differences between groups. Speckle tracking echocardiography variables increase from the MV towards the Ap of the left ventricle in both NORMg and DCMg dogs, some reaching statistical significance. Most of the variables (28/31) were lower in DCMg than in NORMg dogs: statistically significant variables included radial SR at the Ap in systole (p=0.029), radial strain at the PM (p=0.012), circumferential SR at the PM in systole (p=0.031), circumferential and radial SR at the MV in early diastole (p=0.019 and p=0.049, respectively). There are significant differences in STE variables between NORMg and DCMg Great Danes, although the overlap between the two groups may indicate that these variables are not sufficiently discriminatory. STE variables are not sufficiently sensitive to use in isolation as a screening method. Copyright © 2017 Elsevier B.V. All rights reserved.

Variability-aware compact modeling and statistical circuit validation on SRAM test array

NASA Astrophysics Data System (ADS)

Qiao, Ying; Spanos, Costas J.

2016-03-01

Variability modeling at the compact transistor model level can enable statistically optimized designs in view of limitations imposed by the fabrication technology. In this work we propose a variability-aware compact model characterization methodology based on stepwise parameter selection. Transistor I-V measurements are obtained from bit transistor accessible SRAM test array fabricated using a collaborating foundry's 28nm FDSOI technology. Our in-house customized Monte Carlo simulation bench can incorporate these statistical compact models; and simulation results on SRAM writability performance are very close to measurements in distribution estimation. Our proposed statistical compact model parameter extraction methodology also has the potential of predicting non-Gaussian behavior in statistical circuit performances through mixtures of Gaussian distributions.

Bactibilia and surgical site infection after open cholecystectomy.

PubMed

Velázquez-Mendoza, José Dolores; Alvarez-Mora, Moisés; Velázquez-Morales, César Augusto; Anaya-Prado, Roberto

2010-01-01

Bactibilia is the presence of bacteria in gall bladder bile and may play a role in the appearance of septic complications. It has been related to increased rates of surgical site infection after cholecystectomy. In this study we investigated whether bactibilia correlates with the presence of surgical site infection after cholecystectomy. In this observational and descriptive study we investigated those patients operated by open cholecystectomy because of chronic cholecystitis. Patients had bile culture during surgery (January-December 2006). There were two study groups: patients with negative biliary culture (group 1) and patients with positive biliary culture (group 2). Variables were age, gender, biliary culture reports, abscess, cellulitis, seroma, and hematoma. Statistical analysis included Pearson chi(2) or Fisher's exact test. For independent variables, Student t-test was used. Eighty patients were included (n = 40 per group). There were 24 males (30%) and 56 females (70%) who had open cholecystectomy and had biliary culture. General morbidity was 42.50% and surgical site infection rate in general was 11.25%. There were two patients with abscesses and two patients with cellulitis in group 1. There were four patients with abscesses and one patient with cellulitis in group 2. There was no statistically significant difference when comparing surgical site infection in both groups. The presence of bacteria in gall bladder cultures does not correlate with the development of surgical site infection after open cholecystectomy.

RESPONSES OF MALE TROPICAL MOCKINGBIRDS TO VARIATION IN WITHIN-SONG AND BETWEEN-SONG VERSATILITY

PubMed Central

Botero, Carlos A.; Vehrencamp, Sandra L.

2007-01-01

Despite their large vocal repertoires and otherwise highly versatile singing style, male mockingbirds sometimes sing in a highly repetitive fashion. We conducted a playback experiment to determine the possible signal value of different syllable presentation patterns during simulated male intrusions in the Tropical Mockingbird (Mimus gilvus) testing the hypothesis that more repetitive singing represents a stronger threat and generates a stronger aggressive response. Responses were measured in terms of approach and singing behavior and were analyzed using McGregor’s (1992) multivariate method. We also introduce the use of survival analysis for analyzing response variables for which subjects do not perform the behavior in question in at least one of the replicates (known as ‘right-censored variables’ in the statistical literature). As predicted by theory, experimental subjects responded more aggressively to songs composed of a single note than to variable ones. However, versatility at the between-song level had an opposite effect as high song switching rates generated stronger responses than low ones. Given the lack of a statistical interaction between within-song versatility and switching rate, we conclude that these two parameters may serve independent purposes and possibly transmit different information. We discuss the possibility that the signal value of variation in vocal versatility lies in the mediation of territorial conflicts, the attraction of female partners and/or the mediation of conflicts over access to reproductive females. PMID:18509510

[The influence of physical exercise on heart rate variability].

PubMed

Gajek, Jacek; Zyśko, Dorota; Negrusz-Kawecka, Marta; Halawa, Bogumił

2003-03-01

Heart rate variability is controlled by the influence of autonomic nervous system, whereas one part of the system modulates the activity of the other. There is evidence of increased sympathetic activity in patients (pts) with essential hypertension. The aim of the study was to assess the persisting influence of increased sympathetic activity 30 min after moderate physical exercise on heart rate variability in patients with arterial hypertension. The study was performed in 19 patients (10 women, mean age 52.7 +/- 9.5 years and 9 men, mean age 37.7 +/- 8.8 years) with stage I (6 pts) and stage II (13 pts) arterial hypertension. All studied pts had sinus rhythm, were free of diabetes, coronary heart disease and congestive heart failure. 24-hour Holter monitoring was performed and for 30 min before the exercise test the pts stayed in supine rest. The exercise tests were performed between 10 and 11 a.m. Immediately after the exercise all pts stayed in supine position for 30 min. The heart rate variability parameters were studied using Holter monitoring system Medilog Optima Jet and were then analysed statistically. The mean energy expenditure during the exercise was 5.8 +/- 1.1 METs and the maximal heart rate was 148.1 +/- 20.3 bpm. All studied HRV parameters were significantly different in the assessed time period compared to the baseline values (p < 0.001). Significant correlation was found between the age of the studied patients and the mean RR interval, what can be considered as a hyperkinetic (hyperadrenergic) circulatory status and shorter RR interval in younger pts. Significant negative correlation between the age and SDNN parameter (r = -0.65, p < 0.001), 30 min after the exercise mirrors the prolonged adrenergic influence in older pts. The present study shows that the influence of moderate physical exercise on heart rate variability in pts with essential hypertension is extended over 30 min period after exercise and is more pronounced in older pts. The studies on HRV should be performed at longer time intervals after exercise.

Optimal allocation of testing resources for statistical simulations

NASA Astrophysics Data System (ADS)

Quintana, Carolina; Millwater, Harry R.; Singh, Gulshan; Golden, Patrick

2015-07-01

Statistical estimates from simulation involve uncertainty caused by the variability in the input random variables due to limited data. Allocating resources to obtain more experimental data of the input variables to better characterize their probability distributions can reduce the variance of statistical estimates. The methodology proposed determines the optimal number of additional experiments required to minimize the variance of the output moments given single or multiple constraints. The method uses multivariate t-distribution and Wishart distribution to generate realizations of the population mean and covariance of the input variables, respectively, given an amount of available data. This method handles independent and correlated random variables. A particle swarm method is used for the optimization. The optimal number of additional experiments per variable depends on the number and variance of the initial data, the influence of the variable in the output function and the cost of each additional experiment. The methodology is demonstrated using a fretting fatigue example.

Teasing apart the effects of natural and constructed green ...

EPA Pesticide Factsheets

Summer low flows and stream temperature maxima are key drivers affecting the sustainability of fish populations. Thus, it is critical to understand both the natural templates of spatiotemporal variability, how these are shifting due to anthropogenic influences of development and climate change, and how these impacts can be moderated by natural and constructed green infrastructure. Low flow statistics of New England streams have been characterized using a combination of regression equations to describe long-term averages as a function of indicators of hydrologic regime (rain- versus snow-dominated), precipitation, evapotranspiration or temperature, surface water storage, baseflow recession rates, and impervious cover. Difference equations have been constructed to describe interannual variation in low flow as a function of changing air temperature, precipitation, and ocean-atmospheric teleconnection indices. Spatial statistical network models have been applied to explore fine-scale variability of thermal regimes along stream networks in New England as a function of variables describing natural and altered energy inputs, groundwater contributions, and retention time. Low flows exacerbate temperature impacts by reducing thermal inertia of streams to energy inputs. Based on these models, we can construct scenarios of fish habitat suitability using current and projected future climate and the potential for preservation and restoration of historic habitat regimes th

Mediator effect of statistical process control between Total Quality Management (TQM) and business performance in Malaysian Automotive Industry

NASA Astrophysics Data System (ADS)

Ahmad, M. F.; Rasi, R. Z.; Zakuan, N.; Hisyamudin, M. N. N.

2015-12-01

In today's highly competitive market, Total Quality Management (TQM) is vital management tool in ensuring a company can success in their business. In order to survive in the global market with intense competition amongst regions and enterprises, the adoption of tools and techniques are essential in improving business performance. There are consistent results between TQM and business performance. However, only few previous studies have examined the mediator effect namely statistical process control (SPC) between TQM and business performance. A mediator is a third variable that changes the association between an independent variable and an outcome variable. This study present research proposed a TQM performance model with mediator effect of SPC with structural equation modelling, which is a more comprehensive model for developing countries, specifically for Malaysia. A questionnaire was prepared and sent to 1500 companies from automotive industry and the related vendors in Malaysia, giving a 21.8 per cent rate. Attempts were made at findings significant impact of mediator between TQM practices and business performance showed that SPC is important tools and techniques in TQM implementation. The result concludes that SPC is partial correlation between and TQM and BP with indirect effect (IE) is 0.25 which can be categorised as high moderator effect.

[Evaluation of the capacity of the APR-DRG classification system to predict hospital mortality].

PubMed

De Marco, Maria Francesca; Lorenzoni, Luca; Addari, Piero; Nante, Nicola

2002-01-01

Inpatient mortality has increasingly been used as an hospital outcome measure. Comparing mortality rates across hospitals requires adjustment for patient risks before making inferences about quality of care based on patient outcomes. Therefore it is essential to dispose of well performing severity measures. The aim of this study is to evaluate the ability of the All Patient Refined DRG system to predict inpatient mortality for congestive heart failure, myocardial infarction, pneumonia and ischemic stroke. Administrative records were used in this analysis. We used two statistics methods to assess the ability of the APR-DRG to predict mortality: the area under the receiver operating characteristics curve (referred to as the c-statistic) and the Hosmer-Lemeshow test. The database for the study included 19,212 discharges for stroke, pneumonia, myocardial infarction and congestive heart failure from fifteen hospital participating in the Italian APR-DRG Project. A multivariate analysis was performed to predict mortality for each condition in study using age, sex and APR-DRG risk mortality subclass as independent variables. Inpatient mortality rate ranges from 9.7% (pneumonia) to 16.7% (stroke). Model discrimination, calculated using the c-statistic, was 0.91 for myocardial infarction, 0.68 for stroke, 0.78 for pneumonia and 0.71 for congestive heart failure. The model calibration assessed using the Hosmer-Leme-show test was quite good. The performance of the APR-DRG scheme when used on Italian hospital activity records is similar to that reported in literature and it seems to improve by adding age and sex to the model. The APR-DRG system does not completely capture the effects of these variables. In some cases, the better performance might be due to the inclusion of specific complications in the risk-of-mortality subclass assignment.

Testing competing forms of the Milankovitch hypothesis: A multivariate approach

NASA Astrophysics Data System (ADS)

Kaufmann, Robert K.; Juselius, Katarina

2016-02-01

We test competing forms of the Milankovitch hypothesis by estimating the coefficients and diagnostic statistics for a cointegrated vector autoregressive model that includes 10 climate variables and four exogenous variables for solar insolation. The estimates are consistent with the physical mechanisms postulated to drive glacial cycles. They show that the climate variables are driven partly by solar insolation, determining the timing and magnitude of glaciations and terminations, and partly by internal feedback dynamics, pushing the climate variables away from equilibrium. We argue that the latter is consistent with a weak form of the Milankovitch hypothesis and that it should be restated as follows: internal climate dynamics impose perturbations on glacial cycles that are driven by solar insolation. Our results show that these perturbations are likely caused by slow adjustment between land ice volume and solar insolation. The estimated adjustment dynamics show that solar insolation affects an array of climate variables other than ice volume, each at a unique rate. This implies that previous efforts to test the strong form of the Milankovitch hypothesis by examining the relationship between solar insolation and a single climate variable are likely to suffer from omitted variable bias.

Biomechanical analysis of two fixation methods for proximal chevron osteotomy of the first metatarsal.

PubMed

Schuh, Reinhard; Hofstaetter, Jochen Gerhard; Benca, Emir; Willegger, Madeleine; von Skrbensky, Gobert; Zandieh, Shahin; Wanivenhaus, Axel; Holinka, Johannes; Windhager, Reinhard

2014-05-01

The proximal chevron osteotomy provides high correctional power. However, relatively high rates of dorsiflexion malunion of up to 17 % are reported for this procedure. This leads to insufficient weight bearing of the first ray and therefore to metatarsalgia. Recent biomechanical and clinical studies pointed out the importance of rigid fixation of proximal metatarsal osteotomies. Therefore, the aim of the present study was to compare biomechanical properties of fixation of proximal chevron osteotomies with variable locking plate and cancellous screw respectively. Ten matched pairs of human fresh frozen cadaveric first metatarsals underwent proximal chevron osteotomy with either variable locking plate or cancellous screw fixation after obtaining bone mineral density. Biomechanical testing included repetitive plantar to dorsal loading from 0 to 31 N with the 858 Mini Bionix(®) (MTS(®) Systems Corporation, Eden Prairie, MN, USA). Dorsal angulation of the distal fragment was recorded. The variable locking plate construct reveals statistically superior results in terms of bending stiffness and dorsal angulation compared to the cancellous screw construct. There was a statistically significant correlation between bone mineral density and maximum tolerated load until construct failure occurred for the screw construct (r = 0.640, p = 0.406). The results of the present study indicate that variable locking plate fixation shows superior biomechanical results to cancellous screw fixation for proximal chevron osteotomy. Additionally, screw construct failure was related to levels of low bone mineral density. Based on the results of the present study we recommend variable locking plate fixation for proximal chevron osteotomy, especially in osteoporotic bone.

Curve fitting and modeling with splines using statistical variable selection techniques

NASA Technical Reports Server (NTRS)

Smith, P. L.

1982-01-01

The successful application of statistical variable selection techniques to fit splines is demonstrated. Major emphasis is given to knot selection, but order determination is also discussed. Two FORTRAN backward elimination programs, using the B-spline basis, were developed. The program for knot elimination is compared in detail with two other spline-fitting methods and several statistical software packages. An example is also given for the two-variable case using a tensor product basis, with a theoretical discussion of the difficulties of their use.

Fitting multidimensional splines using statistical variable selection techniques

NASA Technical Reports Server (NTRS)

Smith, P. L.

1982-01-01

This report demonstrates the successful application of statistical variable selection techniques to fit splines. Major emphasis is given to knot selection, but order determination is also discussed. Two FORTRAN backward elimination programs using the B-spline basis were developed, and the one for knot elimination is compared in detail with two other spline-fitting methods and several statistical software packages. An example is also given for the two-variable case using a tensor product basis, with a theoretical discussion of the difficulties of their use.

Statistical analysis and definition of blockages-prediction formulae for the wastewater network of Oslo by evolutionary computing.

PubMed

Ugarelli, Rita; Kristensen, Stig Morten; Røstum, Jon; Saegrov, Sveinung; Di Federico, Vittorio

2009-01-01

Oslo Vann og Avløpsetaten (Oslo VAV)-the water/wastewater utility in the Norwegian capital city of Oslo-is assessing future strategies for selection of most reliable materials for wastewater networks, taking into account not only material technical performance but also material performance, regarding operational condition of the system.The research project undertaken by SINTEF Group, the largest research organisation in Scandinavia, NTNU (Norges Teknisk-Naturvitenskapelige Universitet) and Oslo VAV adopts several approaches to understand reasons for failures that may impact flow capacity, by analysing historical data for blockages in Oslo.The aim of the study was to understand whether there is a relationship between the performance of the pipeline and a number of specific attributes such as age, material, diameter, to name a few. This paper presents the characteristics of the data set available and discusses the results obtained by performing two different approaches: a traditional statistical analysis by segregating the pipes into classes, each of which with the same explanatory variables, and a Evolutionary Polynomial Regression model (EPR), developed by Technical University of Bari and University of Exeter, to identify possible influence of pipe's attributes on the total amount of predicted blockages in a period of time.Starting from a detailed analysis of the available data for the blockage events, the most important variables are identified and a classification scheme is adopted.From the statistical analysis, it can be stated that age, size and function do seem to have a marked influence on the proneness of a pipeline to blockages, but, for the reduced sample available, it is difficult to say which variable it is more influencing. If we look at total number of blockages the oldest class seems to be the most prone to blockages, but looking at blockage rates (number of blockages per km per year), then it is the youngest class showing the highest blockage rate. EPR allowed identifying the relation between attitude to block and pipe's attributes in order to understand what affects the possibility to have a blockage in the pipe. EPR provides formulae to compute the accumulated number of blockages for a pipe class at the end of a given period of time. Those formulae do not represent simply regression models but highlight those variables which affect the physical phenomenon in question.

Is Bone Morphogenetic Protein-2 as Effective as Alveolar Distraction Osteogenesis for Vertical Bone Regeneration?

PubMed

Reuss, Jose M; Pi-Anfruns, Joan; Moy, Peter K

2018-04-01

The aim of this study was to assess the clinical effectiveness of alveolar distraction osteogenesis (ADO) versus recombinant human bone morphogenetic protein-2 (rh-BMP-2) for vertical ridge augmentation. Few data have been published on vertical bone regeneration using rh-BMP-2. The authors implemented a retrospective cohort study and enrolled a sample composed of patients with deficient alveolar vertical bone height. The primary predictor variable was vertical augmentation with BMP-2 and a titanium mesh or ADO. The primary outcome variable was gain in vertical bone height (millimeters) measured using computed tomography. The secondary outcome variable was postoperative complications, namely need for further grafting before or simultaneous with implant placement, soft tissue dehiscence, paresthesia, infection, implant failure, and pain. Other outcomes included implant stability at time of placement and follow-up (implant stability quotient by resonance frequency analysis), surgical time (minutes), and total treatment time until implant placement (weeks). Other study variables included location of reconstruction (maxilla or mandible). Appropriate bivariate statistics were computed and statistical significance was set a P value less than .05. The retrospective review yielded 21 patients in the BMP group and 19 in the ADO group. For the BMP-2 group, the average vertical bone gain was 2.96 ± 1.8 mm overall (maxilla, mean 3.6 ± 3.1 mm; mandible, mean 2.32 ± 1.8 mm). For the ADO group, this gain was 4 ± 1.69 mm overall (maxilla, mean 2.8 ± 1.94 mm; mandible, mean 5.2 ± 4.67 mm). For complications, group BMP showed a statistically minor tendency for more postoperative problems, such as wound dehiscence. For implant survival, group BMP showed a 92.2% survival rate versus 96.3% in group ADO at 3 to 45 months after delivery of the prosthesis (average, 22 months). The 2 techniques showed similar values in absolute vertical bone gain. Group ADO showed a slightly better outcome in outright vertical regenerative potential, albeit with a more frequent need for regrafting before and simultaneous with implant placement. Group BMP showed a lesser need for regrafting, despite having a higher postoperative complication rate. Copyright © 2017 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.

Model Parameter Variability for Enhanced Anaerobic Bioremediation of DNAPL Source Zones

NASA Astrophysics Data System (ADS)

Mao, X.; Gerhard, J. I.; Barry, D. A.

2005-12-01

The objective of the Source Area Bioremediation (SABRE) project, an international collaboration of twelve companies, two government agencies and three research institutions, is to evaluate the performance of enhanced anaerobic bioremediation for the treatment of chlorinated ethene source areas containing dense, non-aqueous phase liquids (DNAPL). This 4-year, 5.7 million dollars research effort focuses on a pilot-scale demonstration of enhanced bioremediation at a trichloroethene (TCE) DNAPL field site in the United Kingdom, and includes a significant program of laboratory and modelling studies. Prior to field implementation, a large-scale, multi-laboratory microcosm study was performed to determine the optimal system properties to support dehalogenation of TCE in site soil and groundwater. This statistically-based suite of experiments measured the influence of key variables (electron donor, nutrient addition, bioaugmentation, TCE concentration and sulphate concentration) in promoting the reductive dechlorination of TCE to ethene. As well, a comprehensive biogeochemical numerical model was developed for simulating the anaerobic dehalogenation of chlorinated ethenes. An appropriate (reduced) version of this model was combined with a parameter estimation method based on fitting of the experimental results. Each of over 150 individual microcosm calibrations involved matching predicted and observed time-varying concentrations of all chlorinated compounds. This study focuses on an analysis of this suite of fitted model parameter values. This includes determining the statistical correlation between parameters typically employed in standard Michaelis-Menten type rate descriptions (e.g., maximum dechlorination rates, half-saturation constants) and the key experimental variables. The analysis provides insight into the degree to which aqueous phase TCE and cis-DCE inhibit dechlorination of less-chlorinated compounds. Overall, this work provides a database of the numerical modelling parameters typically employed for simulating TCE dechlorination relevant for a range of system conditions (e.g, bioaugmented, high TCE concentrations, etc.). The significance of the obtained variability of parameters is illustrated with one-dimensional simulations of enhanced anaerobic bioremediation of residual TCE DNAPL.

Data-driven fuel consumption estimation: A multivariate adaptive regression spline approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Yuche; Zhu, Lei; Gonder, Jeffrey

Providing guidance and information to drivers to help them make fuel-efficient route choices remains an important and effective strategy in the near term to reduce fuel consumption from the transportation sector. One key component in implementing this strategy is a fuel-consumption estimation model. In this paper, we developed a mesoscopic fuel consumption estimation model that can be implemented into an eco-routing system. Our proposed model presents a framework that utilizes large-scale, real-world driving data, clusters road links by free-flow speed and fits one statistical model for each of cluster. This model includes predicting variables that were rarely or never consideredmore » before, such as free-flow speed and number of lanes. We applied the model to a real-world driving data set based on a global positioning system travel survey in the Philadelphia-Camden-Trenton metropolitan area. Results from the statistical analyses indicate that the independent variables we chose influence the fuel consumption rates of vehicles. But the magnitude and direction of the influences are dependent on the type of road links, specifically free-flow speeds of links. Here, a statistical diagnostic is conducted to ensure the validity of the models and results. Although the real-world driving data we used to develop statistical relationships are specific to one region, the framework we developed can be easily adjusted and used to explore the fuel consumption relationship in other regions.« less

Data-driven fuel consumption estimation: A multivariate adaptive regression spline approach

DOE PAGES

Chen, Yuche; Zhu, Lei; Gonder, Jeffrey; ...

2017-08-12

Providing guidance and information to drivers to help them make fuel-efficient route choices remains an important and effective strategy in the near term to reduce fuel consumption from the transportation sector. One key component in implementing this strategy is a fuel-consumption estimation model. In this paper, we developed a mesoscopic fuel consumption estimation model that can be implemented into an eco-routing system. Our proposed model presents a framework that utilizes large-scale, real-world driving data, clusters road links by free-flow speed and fits one statistical model for each of cluster. This model includes predicting variables that were rarely or never consideredmore » before, such as free-flow speed and number of lanes. We applied the model to a real-world driving data set based on a global positioning system travel survey in the Philadelphia-Camden-Trenton metropolitan area. Results from the statistical analyses indicate that the independent variables we chose influence the fuel consumption rates of vehicles. But the magnitude and direction of the influences are dependent on the type of road links, specifically free-flow speeds of links. Here, a statistical diagnostic is conducted to ensure the validity of the models and results. Although the real-world driving data we used to develop statistical relationships are specific to one region, the framework we developed can be easily adjusted and used to explore the fuel consumption relationship in other regions.« less

Simultaneous monitoring of maternal and fetal heart rate variability during labor in relation with fetal gender.

PubMed

Gonçalves, Hernâni; Fernandes, Diana; Pinto, Paula; Ayres-de-Campos, Diogo; Bernardes, João

2017-11-01

Male gender is considered a risk factor for several adverse perinatal outcomes. Fetal gender effect on fetal heart rate (FHR) has been subject of several studies with contradictory results. The importance of maternal heart rate (MHR) monitoring during labor has also been investigated, but less is known about the effect of fetal gender on MHR. The aim of this study is to simultaneously assess maternal and FHR variability during labor in relation with fetal gender. Simultaneous MHR and FHR recordings were obtained from 44 singleton term pregnancies during the last 2 hr of labor (H 1, H 2 ). Heart rate tracings were analyzed using linear (time- and frequency-domain) and nonlinear indices. Both linear and nonlinear components were considered in assessing FHR and MHR interaction, including cross-sample entropy (cross-SampEn). Mothers carrying male fetuses (n = 22) had significantly higher values for linear indices related with MHR average and variability and sympatho-vagal balance, while the opposite occurred in the high-frequency component and most nonlinear indices. Significant differences in FHR were only observed in H 1 with higher entropy values in female fetuses. Assessing the differences between FHR and MHR, statistically significant differences were obtained in most nonlinear indices between genders. A significantly higher cross-SampEn was observed in mothers carrying female fetuses (n = 22), denoting lower synchrony or similarity between MHR and FHR. The variability of MHR and the synchrony/similarity between MHR and FHR vary with respect to fetal gender during labor. These findings suggest that fetal gender needs to be taken into account when simultaneously monitoring MHR and FHR. © 2017 Wiley Periodicals, Inc.

The Paediatric Rheumatology International Trials Organisation provisional criteria for the evaluation of response to therapy in juvenile dermatomyositis.

PubMed

Ruperto, Nicolino; Pistorio, Angela; Ravelli, Angelo; Rider, Lisa G; Pilkington, Clarissa; Oliveira, Sheila; Wulffraat, Nico; Espada, Graciela; Garay, Stella; Cuttica, Ruben; Hofer, Michael; Quartier, Pierre; Melo-Gomes, Jose; Reed, Ann M; Wierzbowska, Malgorzata; Feldman, Brian M; Harjacek, Miroslav; Huppertz, Hans-Iko; Nielsen, Susan; Flato, Berit; Lahdenne, Pekka; Michels, Harmut; Murray, Kevin J; Punaro, Lynn; Rennebohm, Robert; Russo, Ricardo; Balogh, Zsolt; Rooney, Madeleine; Pachman, Lauren M; Wallace, Carol; Hashkes, Philip; Lovell, Daniel J; Giannini, Edward H; Gare, Boel Andersson; Martini, Alberto

2010-11-01

To develop a provisional definition for the evaluation of response to therapy in juvenile dermatomyositis (DM) based on the Paediatric Rheumatology International Trials Organisation juvenile DM core set of variables. Thirty-seven experienced pediatric rheumatologists from 27 countries achieved consensus on 128 difficult patient profiles as clinically improved or not improved using a stepwise approach (patient's rating, statistical analysis, definition selection). Using the physicians' consensus ratings as the "gold standard measure," chi-square, sensitivity, specificity, false-positive and-negative rates, area under the receiver operating characteristic curve, and kappa agreement for candidate definitions of improvement were calculated. Definitions with kappa values >0.8 were multiplied by the face validity score to select the top definitions. The top definition of improvement was at least 20% improvement from baseline in 3 of 6 core set variables with no more than 1 of the remaining worsening by more than 30%, which cannot be muscle strength. The second-highest scoring definition was at least 20% improvement from baseline in 3 of 6 core set variables with no more than 2 of the remaining worsening by more than 25%, which cannot be muscle strength (definition P1 selected by the International Myositis Assessment and Clinical Studies group). The third is similar to the second with the maximum amount of worsening set to 30%. This indicates convergent validity of the process. We propose a provisional data-driven definition of improvement that reflects well the consensus rating of experienced clinicians, which incorporates clinically meaningful change in core set variables in a composite end point for the evaluation of global response to therapy in juvenile DM. Copyright © 2010 by the American College of Rheumatology.

Descriptive statistics: the specification of statistical measures and their presentation in tables and graphs. Part 7 of a series on evaluation of scientific publications.

PubMed

Spriestersbach, Albert; Röhrig, Bernd; du Prel, Jean-Baptist; Gerhold-Ay, Aslihan; Blettner, Maria

2009-09-01

Descriptive statistics are an essential part of biometric analysis and a prerequisite for the understanding of further statistical evaluations, including the drawing of inferences. When data are well presented, it is usually obvious whether the author has collected and evaluated them correctly and in keeping with accepted practice in the field. Statistical variables in medicine may be of either the metric (continuous, quantitative) or categorical (nominal, ordinal) type. Easily understandable examples are given. Basic techniques for the statistical description of collected data are presented and illustrated with examples. The goal of a scientific study must always be clearly defined. The definition of the target value or clinical endpoint determines the level of measurement of the variables in question. Nearly all variables, whatever their level of measurement, can be usefully presented graphically and numerically. The level of measurement determines what types of diagrams and statistical values are appropriate. There are also different ways of presenting combinations of two independent variables graphically and numerically. The description of collected data is indispensable. If the data are of good quality, valid and important conclusions can already be drawn when they are properly described. Furthermore, data description provides a basis for inferential statistics.

Predicting Readmission at Early Hospitalization Using Electronic Clinical Data: An Early Readmission Risk Score.

PubMed

Tabak, Ying P; Sun, Xiaowu; Nunez, Carlos M; Gupta, Vikas; Johannes, Richard S

2017-03-01

Identifying patients at high risk for readmission early during hospitalization may aid efforts in reducing readmissions. We sought to develop an early readmission risk predictive model using automated clinical data available at hospital admission. We developed an early readmission risk model using a derivation cohort and validated the model with a validation cohort. We used a published Acute Laboratory Risk of Mortality Score as an aggregated measure of clinical severity at admission and the number of hospital discharges in the previous 90 days as a measure of disease progression. We then evaluated the administrative data-enhanced model by adding principal and secondary diagnoses and other variables. We examined the c-statistic change when additional variables were added to the model. There were 1,195,640 adult discharges from 70 hospitals with 39.8% male and the median age of 63 years (first and third quartile: 43, 78). The 30-day readmission rate was 11.9% (n=142,211). The early readmission model yielded a graded relationship of readmission and the Acute Laboratory Risk of Mortality Score and the number of previous discharges within 90 days. The model c-statistic was 0.697 with good calibration. When administrative variables were added to the model, the c-statistic increased to 0.722. Automated clinical data can generate a readmission risk score early at hospitalization with fair discrimination. It may have applied value to aid early care transition. Adding administrative data increases predictive accuracy. The administrative data-enhanced model may be used for hospital comparison and outcome research.

The relationship between venture capital investment and macro economic variables via statistical computation method

NASA Astrophysics Data System (ADS)

Aygunes, Gunes

2017-07-01

The objective of this paper is to survey and determine the macroeconomic factors affecting the level of venture capital (VC) investments in a country. The literary depends on venture capitalists' quality and countries' venture capital investments. The aim of this paper is to give relationship between venture capital investment and macro economic variables via statistical computation method. We investigate the countries and macro economic variables. By using statistical computation method, we derive correlation between venture capital investments and macro economic variables. According to method of logistic regression model (logit regression or logit model), macro economic variables are correlated with each other in three group. Venture capitalists regard correlations as a indicator. Finally, we give correlation matrix of our results.

Comparison of climate envelope models developed using expert-selected variables versus statistical selection

USGS Publications Warehouse

Brandt, Laura A.; Benscoter, Allison; Harvey, Rebecca G.; Speroterra, Carolina; Bucklin, David N.; Romañach, Stephanie; Watling, James I.; Mazzotti, Frank J.

2017-01-01

Climate envelope models are widely used to describe potential future distribution of species under different climate change scenarios. It is broadly recognized that there are both strengths and limitations to using climate envelope models and that outcomes are sensitive to initial assumptions, inputs, and modeling methods Selection of predictor variables, a central step in modeling, is one of the areas where different techniques can yield varying results. Selection of climate variables to use as predictors is often done using statistical approaches that develop correlations between occurrences and climate data. These approaches have received criticism in that they rely on the statistical properties of the data rather than directly incorporating biological information about species responses to temperature and precipitation. We evaluated and compared models and prediction maps for 15 threatened or endangered species in Florida based on two variable selection techniques: expert opinion and a statistical method. We compared model performance between these two approaches for contemporary predictions, and the spatial correlation, spatial overlap and area predicted for contemporary and future climate predictions. In general, experts identified more variables as being important than the statistical method and there was low overlap in the variable sets (<40%) between the two methods Despite these differences in variable sets (expert versus statistical), models had high performance metrics (>0.9 for area under the curve (AUC) and >0.7 for true skill statistic (TSS). Spatial overlap, which compares the spatial configuration between maps constructed using the different variable selection techniques, was only moderate overall (about 60%), with a great deal of variability across species. Difference in spatial overlap was even greater under future climate projections, indicating additional divergence of model outputs from different variable selection techniques. Our work is in agreement with other studies which have found that for broad-scale species distribution modeling, using statistical methods of variable selection is a useful first step, especially when there is a need to model a large number of species or expert knowledge of the species is limited. Expert input can then be used to refine models that seem unrealistic or for species that experts believe are particularly sensitive to change. It also emphasizes the importance of using multiple models to reduce uncertainty and improve map outputs for conservation planning. Where outputs overlap or show the same direction of change there is greater certainty in the predictions. Areas of disagreement can be used for learning by asking why the models do not agree, and may highlight areas where additional on-the-ground data collection could improve the models.

Engineering Students Designing a Statistical Procedure for Quantifying Variability

ERIC Educational Resources Information Center

Hjalmarson, Margret A.

2007-01-01

The study examined first-year engineering students' responses to a statistics task that asked them to generate a procedure for quantifying variability in a data set from an engineering context. Teams used technological tools to perform computations, and their final product was a ranking procedure. The students could use any statistical measures,…

A model for AGN variability on multiple time-scales

NASA Astrophysics Data System (ADS)

Sartori, Lia F.; Schawinski, Kevin; Trakhtenbrot, Benny; Caplar, Neven; Treister, Ezequiel; Koss, Michael J.; Urry, C. Megan; Zhang, C. E.

2018-05-01

We present a framework to link and describe active galactic nuclei (AGN) variability on a wide range of time-scales, from days to billions of years. In particular, we concentrate on the AGN variability features related to changes in black hole fuelling and accretion rate. In our framework, the variability features observed in different AGN at different time-scales may be explained as realisations of the same underlying statistical properties. In this context, we propose a model to simulate the evolution of AGN light curves with time based on the probability density function (PDF) and power spectral density (PSD) of the Eddington ratio (L/LEdd) distribution. Motivated by general galaxy population properties, we propose that the PDF may be inspired by the L/LEdd distribution function (ERDF), and that a single (or limited number of) ERDF+PSD set may explain all observed variability features. After outlining the framework and the model, we compile a set of variability measurements in terms of structure function (SF) and magnitude difference. We then combine the variability measurements on a SF plot ranging from days to Gyr. The proposed framework enables constraints on the underlying PSD and the ability to link AGN variability on different time-scales, therefore providing new insights into AGN variability and black hole growth phenomena.

Sub-Seasonal Variability of Tropical Rainfall Observed by TRMM and Ground-based Polarimetric Radar

NASA Astrophysics Data System (ADS)

Dolan, Brenda; Rutledge, Steven; Lang, Timothy; Cifelli, Robert; Nesbitt, Stephen

2010-05-01

Studies of tropical precipitation characteristics from the TRMM-LBA and NAME field campaigns using ground-based polarimetric S-band data have revealed significant differences in microphysical processes occurring in the various meteorological regimes sampled in those projects. In TRMM-LMA (January-February 1999 in Brazil; a TRMM ground validation experiment), variability is driven by prevailing low-level winds. During periods of low-level easterlies, deeper and more intense convection is observed, while during periods of low-level westerlies, weaker convection embedded in widespread stratiform precipitation is common. In the NAME region (North American Monsoon Experiment, summer 2004 along the west coast of Mexico), strong terrain variability drives differences in precipitation, with larger drops and larger ice mass aloft associated with convection occurring over the coastal plain compared to convection over the higher terrain of the Sierra Madre Occidental, or adjacent coastal waters. Comparisons with the TRMM precipitation radar (PR) indicate that such sub-seasonal variability in these two regions are not well characterized by the TRMM PR reflectivity and rainfall statistics. TRMM PR reflectivity profiles in the LBA region are somewhat lower than S-Pol values, particularly in the more intense easterly regime convection. In NAME, mean reflectivities are even more divergent, with TRMM profiles below those of S-Pol. In both regions, the TRMM PR does not capture rain rates above 80 mm hr-1 despite much higher rain rates estimated from the S-Pol polarimetric data, and rain rates are generally lower for a given reflectivity from TRMM PR compared to S-Pol. These differences between TRMM PR and S-Pol may arise from the inability of Z-R relationships to capture the full variability of microphysical conditions or may highlight problems with TRMM retrievals over land. In addition to the TRMM-LBA and NAME regions, analysis of sub-seasonal precipitation variability and comparison of TRMM PR statistics with ground-based radar has been extended to other regions of the globe. The Australian Bureau of Meteorology C-band polarimetric radar C-Pol has been collecting data in Darwin, Australia for over a decade. The Darwin region affords the opportunity to look at precipitation characteristics over land and ocean, as well as variability associated with monsoon and break periods over long periods of time. The polarimetric X-band radar XPort was stationed in West Africa at a field site in Benin during the 2006 and 2007 African monsoon periods, where differences in rainfall associated with African Easterly Wave (AEW) passages and non-AEW periods can be examined. Similar comparisons between TRMM PR and ground based polarimetric radars will also be reported for these regions.

Testing for Granger Causality in the Frequency Domain: A Phase Resampling Method.

PubMed

Liu, Siwei; Molenaar, Peter

2016-01-01

This article introduces phase resampling, an existing but rarely used surrogate data method for making statistical inferences of Granger causality in frequency domain time series analysis. Granger causality testing is essential for establishing causal relations among variables in multivariate dynamic processes. However, testing for Granger causality in the frequency domain is challenging due to the nonlinear relation between frequency domain measures (e.g., partial directed coherence, generalized partial directed coherence) and time domain data. Through a simulation study, we demonstrate that phase resampling is a general and robust method for making statistical inferences even with short time series. With Gaussian data, phase resampling yields satisfactory type I and type II error rates in all but one condition we examine: when a small effect size is combined with an insufficient number of data points. Violations of normality lead to slightly higher error rates but are mostly within acceptable ranges. We illustrate the utility of phase resampling with two empirical examples involving multivariate electroencephalography (EEG) and skin conductance data.

Larger differences in utilization of rarely requested tests in primary care in Spain.

PubMed

Salinas, Maria; López-Garrigós, Maite; Flores, Emilio; Uris, Joaquín; Leiva-Salinas, Carlos

2015-01-01

The study was performed to compare and analyze the inter-departmental variability in the request of rarely requested laboratory tests in primary care, as opposed to other more common and highly requested tests. Data from production statistics for the year 2012 from 76 Spanish laboratories was used. The number of antinuclear antibodies, antistreptolysin O, creatinine, cyclic citrullinated peptide antibodies, deaminated peptide gliadine IgA antibodies, glucose, protein electrophoresis, rheumatoid factor, transglutaminase IgA antibodies, urinalysis and uric acid tests requested was collected. The number of test requests per 1000 inhabitants was calculated. In order to explore the variability the coefficient of quartile dispersion was calculated. The smallest variation was seen for creatinine, glucose, uric acid and urinalysis; the most requested tests. The tests that were least requested showed the greatest variability. Our study shows through a very simplified approach, in a population close to twenty million inhabitants, how in primary care, the variability in the request of laboratory tests is inversely proportional to the request rate.

Global sequence variation in the histidine-rich proteins 2 and 3 of Plasmodium falciparum: implications for the performance of malaria rapid diagnostic tests

PubMed Central

2010-01-01

Background Accurate diagnosis is essential for prompt and appropriate treatment of malaria. While rapid diagnostic tests (RDTs) offer great potential to improve malaria diagnosis, the sensitivity of RDTs has been reported to be highly variable. One possible factor contributing to variable test performance is the diversity of parasite antigens. This is of particular concern for Plasmodium falciparum histidine-rich protein 2 (PfHRP2)-detecting RDTs since PfHRP2 has been reported to be highly variable in isolates of the Asia-Pacific region. Methods The pfhrp2 exon 2 fragment from 458 isolates of P. falciparum collected from 38 countries was amplified and sequenced. For a subset of 80 isolates, the exon 2 fragment of histidine-rich protein 3 (pfhrp3) was also amplified and sequenced. DNA sequence and statistical analysis of the variation observed in these genes was conducted. The potential impact of the pfhrp2 variation on RDT detection rates was examined by analysing the relationship between sequence characteristics of this gene and the results of the WHO product testing of malaria RDTs: Round 1 (2008), for 34 PfHRP2-detecting RDTs. Results Sequence analysis revealed extensive variations in the number and arrangement of various repeats encoded by the genes in parasite populations world-wide. However, no statistically robust correlation between gene structure and RDT detection rate for P. falciparum parasites at 200 parasites per microlitre was identified. Conclusions The results suggest that despite extreme sequence variation, diversity of PfHRP2 does not appear to be a major cause of RDT sensitivity variation. PMID:20470441

Timing at peak force may be the hidden target controlled in continuation and synchronization tapping.

PubMed

Du, Yue; Clark, Jane E; Whitall, Jill

2017-05-01

Timing control, such as producing movements at a given rate or synchronizing movements to an external event, has been studied through a finger-tapping task where timing is measured at the initial contact between finger and tapping surface or the point when a key is pressed. However, the point of peak force is after the time registered at the tapping surface and thus is a less obvious but still an important event during finger tapping. Here, we compared the time at initial contact with the time at peak force as participants tapped their finger on a force sensor at a given rate after the metronome was turned off (continuation task) or in synchrony with the metronome (sensorimotor synchronization task). We found that, in the continuation task, timing was comparably accurate between initial contact and peak force. These two timing events also exhibited similar trial-by-trial statistical dependence (i.e., lag-one autocorrelation). However, the central clock variability was lower at the peak force than the initial contact. In the synchronization task, timing control at peak force appeared to be less variable and more accurate than that at initial contact. In addition to lower central clock variability, the mean SE magnitude at peak force (SEP) was around zero while SE at initial contact (SEC) was negative. Although SEC and SEP demonstrated the same trial-by-trial statistical dependence, we found that participants adjusted the time of tapping to correct SEP, but not SEC, toward zero. These results suggest that timing at peak force is a meaningful target of timing control, particularly in synchronization tapping. This result may explain the fact that SE at initial contact is typically negative as widely observed in the preexisting literature.

LES/PDF studies of joint statistics of mixture fraction and progress variable in piloted methane jet flames with inhomogeneous inlet flows

NASA Astrophysics Data System (ADS)

Zhang, Pei; Barlow, Robert; Masri, Assaad; Wang, Haifeng

2016-11-01

The mixture fraction and progress variable are often used as independent variables for describing turbulent premixed and non-premixed flames. There is a growing interest in using these two variables for describing partially premixed flames. The joint statistical distribution of the mixture fraction and progress variable is of great interest in developing models for partially premixed flames. In this work, we conduct predictive studies of the joint statistics of mixture fraction and progress variable in a series of piloted methane jet flames with inhomogeneous inlet flows. The employed models combine large eddy simulations with the Monte Carlo probability density function (PDF) method. The joint PDFs and marginal PDFs are examined in detail by comparing the model predictions and the measurements. Different presumed shapes of the joint PDFs are also evaluated.

Quantum-like microeconomics: Statistical model of distribution of investments and production

NASA Astrophysics Data System (ADS)

Khrennikov, Andrei

2008-10-01

In this paper we demonstrate that the probabilistic quantum-like (QL) behavior-the Born’s rule, interference of probabilities, violation of Bell’s inequality, representation of variables by in general noncommutative self-adjoint operators, Schrödinger’s dynamics-can be exhibited not only by processes in the micro world, but also in economics. In our approach the QL-behavior is induced not by properties of systems. Here systems (commodities) are macroscopic. They could not be superpositions of two different states. In our approach the QL-behavior of economical statistics is a consequence of the organization of the process of production as well as investments. In particular, Hamiltonian (“financial energy”) is determined by rate of return.

Bayesian methods in reliability

NASA Astrophysics Data System (ADS)

Sander, P.; Badoux, R.

1991-11-01

The present proceedings from a course on Bayesian methods in reliability encompasses Bayesian statistical methods and their computational implementation, models for analyzing censored data from nonrepairable systems, the traits of repairable systems and growth models, the use of expert judgment, and a review of the problem of forecasting software reliability. Specific issues addressed include the use of Bayesian methods to estimate the leak rate of a gas pipeline, approximate analyses under great prior uncertainty, reliability estimation techniques, and a nonhomogeneous Poisson process. Also addressed are the calibration sets and seed variables of expert judgment systems for risk assessment, experimental illustrations of the use of expert judgment for reliability testing, and analyses of the predictive quality of software-reliability growth models such as the Weibull order statistics.

Comparison of statistical models to estimate parasite growth rate in the induced blood stage malaria model.

PubMed

Wockner, Leesa F; Hoffmann, Isabell; O'Rourke, Peter; McCarthy, James S; Marquart, Louise

2017-08-25

The efficacy of vaccines aimed at inhibiting the growth of malaria parasites in the blood can be assessed by comparing the growth rate of parasitaemia in the blood of subjects treated with a test vaccine compared to controls. In studies using induced blood stage malaria (IBSM), a type of controlled human malaria infection, parasite growth rate has been measured using models with the intercept on the y-axis fixed to the inoculum size. A set of statistical models was evaluated to determine an optimal methodology to estimate parasite growth rate in IBSM studies. Parasite growth rates were estimated using data from 40 subjects published in three IBSM studies. Data was fitted using 12 statistical models: log-linear, sine-wave with the period either fixed to 48 h or not fixed; these models were fitted with the intercept either fixed to the inoculum size or not fixed. All models were fitted by individual, and overall by study using a mixed effects model with a random effect for the individual. Log-linear models and sine-wave models, with the period fixed or not fixed, resulted in similar parasite growth rate estimates (within 0.05 log 10 parasites per mL/day). Average parasite growth rate estimates for models fitted by individual with the intercept fixed to the inoculum size were substantially lower by an average of 0.17 log 10 parasites per mL/day (range 0.06-0.24) compared with non-fixed intercept models. Variability of parasite growth rate estimates across the three studies analysed was substantially higher (3.5 times) for fixed-intercept models compared with non-fixed intercept models. The same tendency was observed in models fitted overall by study. Modelling data by individual or overall by study had minimal effect on parasite growth estimates. The analyses presented in this report confirm that fixing the intercept to the inoculum size influences parasite growth estimates. The most appropriate statistical model to estimate the growth rate of blood-stage parasites in IBSM studies appears to be a log-linear model fitted by individual and with the intercept estimated in the log-linear regression. Future studies should use this model to estimate parasite growth rates.

The Effects of Data and Graph Type on Concepts and Visualizations of Variability

ERIC Educational Resources Information Center

Cooper, Linda L.; Shore, Felice S.

2010-01-01

Recognizing and interpreting variability in data lies at the heart of statistical reasoning. Since graphical displays should facilitate communication about data, statistical literacy should include an understanding of how variability in data can be gleaned from a graph. This paper identifies several types of graphs that students typically…

Manipulating measurement scales in medical statistical analysis and data mining: A review of methodologies

PubMed Central

Marateb, Hamid Reza; Mansourian, Marjan; Adibi, Peyman; Farina, Dario

2014-01-01

Background: selecting the correct statistical test and data mining method depends highly on the measurement scale of data, type of variables, and purpose of the analysis. Different measurement scales are studied in details and statistical comparison, modeling, and data mining methods are studied based upon using several medical examples. We have presented two ordinal–variables clustering examples, as more challenging variable in analysis, using Wisconsin Breast Cancer Data (WBCD). Ordinal-to-Interval scale conversion example: a breast cancer database of nine 10-level ordinal variables for 683 patients was analyzed by two ordinal-scale clustering methods. The performance of the clustering methods was assessed by comparison with the gold standard groups of malignant and benign cases that had been identified by clinical tests. Results: the sensitivity and accuracy of the two clustering methods were 98% and 96%, respectively. Their specificity was comparable. Conclusion: by using appropriate clustering algorithm based on the measurement scale of the variables in the study, high performance is granted. Moreover, descriptive and inferential statistics in addition to modeling approach must be selected based on the scale of the variables. PMID:24672565

Evaluating measurement models in clinical research: covariance structure analysis of latent variable models of self-conception.

PubMed

Hoyle, R H

1991-02-01

Indirect measures of psychological constructs are vital to clinical research. On occasion, however, the meaning of indirect measures of psychological constructs is obfuscated by statistical procedures that do not account for the complex relations between items and latent variables and among latent variables. Covariance structure analysis (CSA) is a statistical procedure for testing hypotheses about the relations among items that indirectly measure a psychological construct and relations among psychological constructs. This article introduces clinical researchers to the strengths and limitations of CSA as a statistical procedure for conceiving and testing structural hypotheses that are not tested adequately with other statistical procedures. The article is organized around two empirical examples that illustrate the use of CSA for evaluating measurement models with correlated error terms, higher-order factors, and measured and latent variables.

[Hydrologic variability and sensitivity based on Hurst coefficient and Bartels statistic].

PubMed

Lei, Xu; Xie, Ping; Wu, Zi Yi; Sang, Yan Fang; Zhao, Jiang Yan; Li, Bin Bin

2018-04-01

Due to the global climate change and frequent human activities in recent years, the pure stochastic components of hydrological sequence is mixed with one or several of the variation ingredients, including jump, trend, period and dependency. It is urgently needed to clarify which indices should be used to quantify the degree of their variability. In this study, we defined the hydrological variability based on Hurst coefficient and Bartels statistic, and used Monte Carlo statistical tests to test and analyze their sensitivity to different variants. When the hydrological sequence had jump or trend variation, both Hurst coefficient and Bartels statistic could reflect the variation, with the Hurst coefficient being more sensitive to weak jump or trend variation. When the sequence had period, only the Bartels statistic could detect the mutation of the sequence. When the sequence had a dependency, both the Hurst coefficient and the Bartels statistics could reflect the variation, with the latter could detect weaker dependent variations. For the four variations, both the Hurst variability and Bartels variability increased with the increases of variation range. Thus, they could be used to measure the variation intensity of the hydrological sequence. We analyzed the temperature series of different weather stations in the Lancang River basin. Results showed that the temperature of all stations showed the upward trend or jump, indicating that the entire basin had experienced warming in recent years and the temperature variability in the upper and lower reaches was much higher. This case study showed the practicability of the proposed method.

Predicting Fog in the Nocturnal Boundary Layer

NASA Astrophysics Data System (ADS)

Izett, Jonathan; van de Wiel, Bas; Baas, Peter; van der Linden, Steven; van Hooft, Antoon; Bosveld, Fred

2017-04-01

Fog is a global phenomenon that presents a hazard to navigation and human safety, resulting in significant economic impacts for air and shipping industries as well as causing numerous road traffic accidents. Accurate prediction of fog events, however, remains elusive both in terms of timing and occurrence itself. Statistical methods based on set threshold criteria for key variables such as wind speed have been developed, but high rates of correct prediction of fog events still lead to similarly high "false alarms" when the conditions appear favourable, but no fog forms. Using data from the CESAR meteorological observatory in the Netherlands, we analyze specific cases and perform statistical analyses of event climatology, in order to identify the necessary conditions for correct prediction of fog. We also identify potential "missing ingredients" in current analysis that could help to reduce the number of false alarms. New variables considered include the indicators of boundary layer stability, as well as the presence of aerosols conducive to droplet formation. The poster presents initial findings of new research as well as plans for continued research.

Project update: evaluating the community health legacy of WWI chemical weapons testing.

PubMed

Fox, Mary A

2014-10-01

The Spring Valley community of Washington, District of Columbia, was built on the site of a World War I chemical weapons lab where testing activities had distributed arsenic to surface soil and waste disposal had resulted in localized subsurface contamination. In previous work, findings were suggestive of potential site-related health issues, although no evidence of cancer clustering was found. In follow-up, we updated the community health assessment and explored time trends for several arsenic-related cancers. Health indicators continue to be very good in Spring Valley. For all major causes of mortality, Spring Valley rates were lower than United States (US) rates with most substantially lower (20-80 %); rates for heart diseases, Alzheimer's, and essential hypertension and related kidney disease were only slightly lower than US rates (3-8 %). Incidence and mortality rates for the selected cancers in the Spring Valley area were lower than US rates. Small non-statistically significant increasing time trends were observed in Spring Valley for incidence of two arsenic-related cancers: bladder and lung and bronchus. A moderate statistically significant increasing rate trend was observed for lung and bronchus cancer mortality in Spring Valley (p < 0.01). Lung and bronchus cancer mortality rates were also increasing in the Chevy Chase community, the local comparison area closely matched to Spring Valley on important demographic variables, suggesting that the observed increases may not be site-related. A full profile of common cancer site rates and trends for both study areas was suggested to better understand the rate trend findings but no epidemiological study was recommended.

Estimating sensitivity and specificity for technology assessment based on observer studies.

PubMed

Nishikawa, Robert M; Pesce, Lorenzo L

2013-07-01

The goal of this study was to determine the accuracy and precision of using scores from a receiver operating characteristic rating scale to estimate sensitivity and specificity. We used data collected in a previous study that measured the improvements in radiologists' ability to classify mammographic microcalcification clusters as benign or malignant with and without the use of a computer-aided diagnosis scheme. Sensitivity and specificity were estimated from the rating data from a question that directly asked the radiologists their biopsy recommendations, which was used as the "truth," because it is the actual recall decision, thus it is their subjective truth. By thresholding the rating data, sensitivity and specificity were estimated for different threshold values. Because of interreader and intrareader variability, estimated sensitivity and specificity values for individual readers could be as much as 100% in error when using rating data compared to using the biopsy recommendation data. When pooled together, the estimates using thresholding the rating data were in good agreement with sensitivity and specificity estimated from the recommendation data. However, the statistical power of the rating data estimates was lower. By simply asking the observer his or her explicit recommendation (eg, biopsy or no biopsy), sensitivity and specificity can be measured directly, giving a more accurate description of empirical variability and the power of the study can be maximized. Copyright © 2013 AUR. Published by Elsevier Inc. All rights reserved.

Estimating Latent Variable Interactions With Non-Normal Observed Data: A Comparison of Four Approaches

PubMed Central

Cham, Heining; West, Stephen G.; Ma, Yue; Aiken, Leona S.

2012-01-01

A Monte Carlo simulation was conducted to investigate the robustness of four latent variable interaction modeling approaches (Constrained Product Indicator [CPI], Generalized Appended Product Indicator [GAPI], Unconstrained Product Indicator [UPI], and Latent Moderated Structural Equations [LMS]) under high degrees of non-normality of the observed exogenous variables. Results showed that the CPI and LMS approaches yielded biased estimates of the interaction effect when the exogenous variables were highly non-normal. When the violation of non-normality was not severe (normal; symmetric with excess kurtosis < 1), the LMS approach yielded the most efficient estimates of the latent interaction effect with the highest statistical power. In highly non-normal conditions, the GAPI and UPI approaches with ML estimation yielded unbiased latent interaction effect estimates, with acceptable actual Type-I error rates for both the Wald and likelihood ratio tests of interaction effect at N ≥ 500. An empirical example illustrated the use of the four approaches in testing a latent variable interaction between academic self-efficacy and positive family role models in the prediction of academic performance. PMID:23457417

Education, sense of mastery and mental health: results from a nation wide health monitoring study in Norway

PubMed Central

Dalgard, Odd Steffen; Mykletun, Arnstein; Rognerud, Marit; Johansen, Rune; Zahl, Per Henrik

2007-01-01

Background Earlier studies have shown that people with low level of education have increased rates of mental health problems. The aim of the present study is to investigate the association between level of education and psychological distress, and to explore to which extent the association is mediated by sense of mastery, and social variables like social support, negative life events, household income, employment and marital status. Methods The data for the study were obtained from the Level of Living Survey conducted by Statistics Norway in 2002. Data on psychological distress and psychosocial variables were gathered by a self-administered questionnaire, whereas socio-demographic data were based on register statistics. Psychological distress was measured by Hopkins Symptom Checklist 25 items. Results There was a significant association between low level of education and psychological distress in both genders, the association being strongest in women aged 55–67 years. Low level of education was also significantly associated with low sense of mastery, low social support, many negative life events (only in men), low household income and unemployment,. Sense of mastery emerged as a strong mediating variable between level of education and psychological distress, whereas the other variables played a minor role when adjusting for sense of mastery. Conclusion Low sense of mastery seems to account for much of the association between low educational level and psychological distress, and should be an important target in mental health promotion for groups with low level of education. PMID:17519014

[Relationship between family variables and conjugal adjustment].

PubMed

Jiménez-Picón, Nerea; Lima-Rodríguez, Joaquín-Salvador; Lima-Serrano, Marta

2018-04-01

To determine whether family variables, such as type of relationship, years of marriage, existence of offspring, number of members of family, stage of family life cycle, transition between stages, perceived social support, and/or stressful life events are related to conjugal adjustment. A cross-sectional and correlational study using questionnaires. Primary care and hospital units of selected centres in the province of Seville, Spain. Consecutive stratified sampling by quotas of 369 heterosexual couples over 18years of age, who maintained a relationship, with or without children, living in Seville. A self-report questionnaire for the sociodemographic variables, and the abbreviated version of the Dyadic Adjustment Scale, Questionnaire MOS Perceived Social Support, and Social Readjustment Rating Scale, were used. Descriptive and inferential statistics were performed with correlation analysis and multivariate regression. Statistically significant associations were found between conjugal adjustment and marriage years (r=-10: P<.05), stage of family life cycle (F=2.65; P<.05), the transition between stages (RPB=.11; P<.05) and perceived social support (r=.44; P<.001). The regression model showed the predictive power of perceived social support and the family life cycle stage (mature-aged stage) on conjugal adjustment (R2=.21; F=9.9; df=356; P<.001). Couples may be assessed from Primary Care and be provide with resources and support. In addition, it can identify variables that may help improve the conjugal relationship. Copyright © 2017 Elsevier España, S.L.U. All rights reserved.

Information flow to assess cardiorespiratory interactions in patients on weaning trials.

PubMed

Vallverdú, M; Tibaduisa, O; Clariá, F; Hoyer, D; Giraldo, B; Benito, S; Caminal, P

2006-01-01

Nonlinear processes of the autonomic nervous system (ANS) can produce breath-to-breath variability in the pattern of breathing. In order to provide assess to these nonlinear processes, nonlinear statistical dependencies between heart rate variability and respiratory pattern variability are analyzed. In this way, auto-mutual information and cross-mutual information concepts are applied. This information flow analysis is presented as a short-term non linear analysis method to investigate the information flow interactions in patients on weaning trials. 78 patients from mechanical ventilation were studied: Group A of 28 patients that failed to maintain spontaneous breathing and were reconnected; Group B of 50 patients with successful trials. The results show lower complexity with an increase of information flow in group A than in group B. Furthermore, a more (weakly) coupled nonlinear oscillator behavior is observed in the series of group A than in B.

Introduction to the use of regression models in epidemiology.

PubMed

Bender, Ralf

2009-01-01

Regression modeling is one of the most important statistical techniques used in analytical epidemiology. By means of regression models the effect of one or several explanatory variables (e.g., exposures, subject characteristics, risk factors) on a response variable such as mortality or cancer can be investigated. From multiple regression models, adjusted effect estimates can be obtained that take the effect of potential confounders into account. Regression methods can be applied in all epidemiologic study designs so that they represent a universal tool for data analysis in epidemiology. Different kinds of regression models have been developed in dependence on the measurement scale of the response variable and the study design. The most important methods are linear regression for continuous outcomes, logistic regression for binary outcomes, Cox regression for time-to-event data, and Poisson regression for frequencies and rates. This chapter provides a nontechnical introduction to these regression models with illustrating examples from cancer research.

Walk test and school performance in mouth-breathing children.

PubMed

Boas, Ana Paula Dias Vilas; Marson, Fernando Augusto de Lima; Ribeiro, Maria Angela Gonçalves de Oliveira; Sakano, Eulália; Conti, Patricia Blau Margosian; Toro, Adyléia Dalbo Contrera; Ribeiro, José Dirceu

2013-01-01

In recent decades, many studies on mouth breathing (MB) have been published; however, little is known about many aspects of this syndrome, including severity, impact on physical and academic performances. Compare the physical performance in a six minutes walk test (6MWT) and the academic performance of MB and nasal-breathing (NB) children and adolescents. This is a descriptive, cross-sectional, and prospective study with MB and NB children submitted to the 6MWT and scholar performance assessment. We included 156 children, 87 girls (60 NB and 27 MB) and 69 boys (44 NB and 25 MB). Variables were analyzed during the 6MWT: heart rate (HR), respiratory rate, oxygen saturation, distance walked in six minutes and modified Borg scale. All the variables studied were statistically different between groups NB and MB, with the exception of school performance and HR in 6MWT. MB affects physical performance and not the academic performance, we noticed a changed pattern in the 6MWT in the MB group. Since the MBs in our study were classified as non-severe, other studies comparing the academic performance variables and 6MWT are needed to better understand the process of physical and academic performances in MB children.

The Impact of Socioeconomic Conditions, Social Networks, and Health on Frail Older People's Life Satisfaction: A Cross-Sectional Study

PubMed Central

Berglund, Helene; Hasson, Henna; Wilhelmson, Katarina; Dunér, Anna; Dahlin-Ivanoff, Synneve

2016-01-01

It has been shown that frailty is associated with low levels of well-being and life satisfaction. Further exploration is needed, however, to better understand which components constitute life satisfaction for frail older people and how satisfaction is related to other life circumstances. The aim of this study was to examine relationships between frail older people’s life satisfaction and their socioeconomic conditions, social networks, and health-related conditions. A cross-sectional study was conducted (n=179). A logistic regression analysis was performed, including life satisfaction as the dependent variable and 12 items as independent variables. Four of the independent variables made statistically significant contributions: financial situation (OR 3.53), social contacts (OR 2.44), risk of depression (OR 2.26), and self-rated health (OR 2.79). This study demonstrates that financial situation, self-rated health conditions and social networks are important components for frail older people’s life satisfaction. Health and social care professionals and policy makers should consider this knowledge in the care and service for frail older people; and actions that benefit life satisfaction – such as social support – should be promoted. PMID:27403463

Ventilatory abnormalities in patients with cystic fibrosis undergoing the submaximal treadmill exercise test.

PubMed

Parazzi, Paloma Lopes Francisco; Marson, Fernando Augusto de Lima; Ribeiro, Maria Angela Gonçalves de Oliveira; de Almeida, Celize Cruz Bresciani; Martins, Luiz Cláudio; Paschoal, Ilma Aparecida; Toro, Adyleia Aparecida Dalbo Contrera; Schivinski, Camila Isabel Santos; Ribeiro, Jose Dirceu

2015-05-19

Exercise has been studied as a prognostic marker for patients with cystic fibrosis (CF), as well as a tool for improving their quality of life and analyzing lung disease. In this context, the aim of the present study was to evaluate and compare variables of lung functioning. Our data included: (i) volumetric capnography (VCAP) parameters: expiratory minute volume (VE), volume of exhaled carbon dioxide (VCO2), VE/VCO2, ratio of dead space to tidal volume (VD/VT), and end-tidal carbon dioxide (PetCO2); (ii) spirometry parameters: forced vital capacity (FVC), percent forced expiratory volume in the first second of the FVC (FEV1%), and FEV1/FVC%; and (iii) cardiorespiratory parameters: heart rate (HR), respiratory rate, oxygen saturation (SpO2), and Borg scale rating at rest and during exercise. The subjects comprised children, adolescents, and young adults aged 6-25 years with CF (CF group [CFG]) and without CF (control group [CG]). This was a clinical, prospective, controlled study involving 128 male and female patients (64 with CF) of a university hospital. All patients underwent treadmill exercise tests and provided informed consent after study approval by the institutional ethics committee. Linear regression, Kruskal-Wallis test, and Mann-Whitney test were performed to compare the CFG and CG. The α value was set at 0.05. Patients in the CFG showed significantly different VCAP values and spirometry variables throughout the exercise test. Before, during, and after exercise, several variables were different between the two groups; statistically significant differences were seen in the spirometry parameters, SpO2, HR, VCO2, VE/VCO2, PetCO2, and Borg scale rating. VCAP variables changed at each time point analyzed during the exercise test in both groups. VCAP can be used to analyze ventilatory parameters during exercise. All cardiorespiratory, spirometry, and VCAP variables differed between patients in the CFG and CG before, during, and after exercise.

Risk Factors for Sexual Violence in the Military: An Analysis of Sexual Assault and Sexual Harassment Incidents and Reporting

DTIC Science & Technology

2017-03-01

53 ix LIST OF TABLES Table 1. Descriptive Statistics for Control Variables by... Statistics for Control Variables by Gender (Random Subsample with Complete Survey) ............................................................30 Table...empirical analysis. Chapter IV describes the summary statistics and results. Finally, Chapter V offers concluding thoughts, study limitations, and

Statistics Anxiety and Worry: The Roles of Worry Beliefs, Negative Problem Orientation, and Cognitive Avoidance

ERIC Educational Resources Information Center

Williams, Amanda S.

2015-01-01

Statistics anxiety is a common problem for graduate students. This study explores the multivariate relationship between a set of worry-related variables and six types of statistics anxiety. Canonical correlation analysis indicates a significant relationship between the two sets of variables. Findings suggest that students who are more intolerant…

Symbolic dynamics marker of heart rate variability combined with clinical variables enhance obstructive sleep apnea screening

NASA Astrophysics Data System (ADS)

Ravelo-García, A. G.; Saavedra-Santana, P.; Juliá-Serdá, G.; Navarro-Mesa, J. L.; Navarro-Esteva, J.; Álvarez-López, X.; Gapelyuk, A.; Penzel, T.; Wessel, N.

2014-06-01

Many sleep centres try to perform a reduced portable test in order to decrease the number of overnight polysomnographies that are expensive, time-consuming, and disturbing. With some limitations, heart rate variability (HRV) has been useful in this task. The aim of this investigation was to evaluate if inclusion of symbolic dynamics variables to a logistic regression model integrating clinical and physical variables, can improve the detection of subjects for further polysomnographies. To our knowledge, this is the first contribution that innovates in that strategy. A group of 133 patients has been referred to the sleep center for suspected sleep apnea. Clinical assessment of the patients consisted of a sleep related questionnaire and a physical examination. The clinical variables related to apnea and selected in the statistical model were age (p < 10-3), neck circumference (p < 10-3), score on a questionnaire scale intended to quantify daytime sleepiness (p < 10-3), and intensity of snoring (p < 10-3). The validation of this model demonstrated an increase in classification performance when a variable based on non-linear dynamics of HRV (p < 0.01) was used additionally to the other variables. For diagnostic rule based only on clinical and physical variables, the corresponding area under the receiver operating characteristic (ROC) curve was 0.907 (95% confidence interval (CI) = 0.848, 0.967), (sensitivity 87.10% and specificity 80%). For the model including the average of a symbolic dynamic variable, the area under the ROC curve was increased to 0.941 (95% = 0.897, 0.985), (sensitivity 88.71% and specificity 82.86%). In conclusion, symbolic dynamics, coupled with significant clinical and physical variables can help to prioritize polysomnographies in patients with a high probability of apnea. In addition, the processing of the HRV is a well established low cost and robust technique.

[Clinical research IV. Relevancy of the statistical test chosen].

PubMed

Talavera, Juan O; Rivas-Ruiz, Rodolfo

2011-01-01

When we look at the difference between two therapies or the association of a risk factor or prognostic indicator with its outcome, we need to evaluate the accuracy of the result. This assessment is based on a judgment that uses information about the study design and statistical management of the information. This paper specifically mentions the relevance of the statistical test selected. Statistical tests are chosen mainly from two characteristics: the objective of the study and type of variables. The objective can be divided into three test groups: a) those in which you want to show differences between groups or inside a group before and after a maneuver, b) those that seek to show the relationship (correlation) between variables, and c) those that aim to predict an outcome. The types of variables are divided in two: quantitative (continuous and discontinuous) and qualitative (ordinal and dichotomous). For example, if we seek to demonstrate differences in age (quantitative variable) among patients with systemic lupus erythematosus (SLE) with and without neurological disease (two groups), the appropriate test is the "Student t test for independent samples." But if the comparison is about the frequency of females (binomial variable), then the appropriate statistical test is the χ(2).

Stochastic Dual Algorithm for Voltage Regulation in Distribution Networks with Discrete Loads: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dall-Anese, Emiliano; Zhou, Xinyang; Liu, Zhiyuan

This paper considers distribution networks with distributed energy resources and discrete-rate loads, and designs an incentive-based algorithm that allows the network operator and the customers to pursue given operational and economic objectives, while concurrently ensuring that voltages are within prescribed limits. Four major challenges include: (1) the non-convexity from discrete decision variables, (2) the non-convexity due to a Stackelberg game structure, (3) unavailable private information from customers, and (4) different update frequency from two types of devices. In this paper, we first make convex relaxation for discrete variables, then reformulate the non-convex structure into a convex optimization problem together withmore » pricing/reward signal design, and propose a distributed stochastic dual algorithm for solving the reformulated problem while restoring feasible power rates for discrete devices. By doing so, we are able to statistically achieve the solution of the reformulated problem without exposure of any private information from customers. Stability of the proposed schemes is analytically established and numerically corroborated.« less

Sex differences in associations between insulin resistance, heart rate variability, and arterial stiffness in healthy women and men: a physiology study.

PubMed

Rannelli, Luke Anthony; MacRae, Jennifer M; Mann, Michelle C; Ramesh, Sharanya; Hemmelgarn, Brenda R; Rabi, Doreen; Sola, Darlene Y; Ahmed, Sofia B

2017-04-01

Diabetes confers greater cardiovascular risk to women than to men. Whether insulin-resistance-mediated risk extends to the healthy population is unknown. Measures of insulin resistance (fasting insulin, homeostatic model assessment, hemoglobin A1c, quantitative insulin sensitivity check index, glucose) were determined in 48 (56% female) healthy subjects. Heart rate variability (HRV) was calculated by spectral power analysis and arterial stiffness was determined using noninvasive applanation tonometry. Both were measured at baseline and in response to angiotensin II infusion. In women, there was a non-statistically significant trend towards increasing insulin resistance being associated with an overall unfavourable HRV response and increased arterial stiffness to the stressor, while men demonstrated the opposite response. Significant differences in the associations between insulin resistance and cardiovascular physiological profile exist between healthy women and men. Further studies investigating the sex differences in the pathophysiology of insulin resistance in cardiovascular disease are warranted.

Recurrence quantification analysis of heart rate variability and respiratory flow series in patients on weaning trials.

PubMed

Arcentales, Andrés; Giraldo, Beatriz F; Caminal, Pere; Benito, Salvador; Voss, Andreas

2011-01-01

Autonomic nervous system regulates the behavior of cardiac and respiratory systems. Its assessment during the ventilator weaning can provide information about physio-pathological imbalances. This work proposes a non linear analysis of the complexity of the heart rate variability (HRV) and breathing duration (T(Tot)) applying recurrence plot (RP) and their interaction joint recurrence plot (JRP). A total of 131 patients on weaning trials from mechanical ventilation were analyzed: 92 patients with successful weaning (group S) and 39 patients that failed to maintain spontaneous breathing (group F). The results show that parameters as determinism (DET), average diagonal line length (L), and entropy (ENTR), are statistically significant with RP for T(Tot) series, but not with HRV. When comparing the groups with JRP, all parameters have been relevant. In all cases, mean values of recurrence quantification analysis are higher in the group S than in the group F. The main differences between groups were found on the diagonal and vertical structures of the joint recurrence plot.

Effect of private versus emergency medical systems transportation in motor vehicle accident victims: Trauma Center Experience in Saudi Arabia.

PubMed

Alshahrani, Mohammed S

2017-01-01

To assess the effect of the mode of transportation of trauma patients (emergency medical service [EMS] vs. non-EMS) on their final clinical outcome in terms of mortality and length of hospital stay. A retrospective study included all patients who were involved in motor vehicle crashes, and who were transferred immediately to an emergency department of a trauma care center from December 2008 to December 2012. Patients were classified into two groups: those brought through EMS and those brought by non-EMS (private transport). Information on demographic characteristics including age and gender was recorded and medical data such as blood pressure, pulse, oxygen saturation, temperature, initial Glasgow Coma Score (GCS), saturation, temperature, initial Glasgow Coma Score (GCS), injury severity score (ISS), and final outcome (discharged or expired) were obtained. Descriptive statistics, mean and standard deviation (SD) were computed for continuous variables and statistical significance was tested by t -test or Mann-Whitney U-test. Categorical variables were described by frequency distribution and percentages; Chi-square or Fisher's exact test as appropriate were employed to test for statistical significance. Logistics regression was performed with mortality as dependent variable and mode of transport and all demographic and prehospital variables as independent variables. A general linear model analysis was performed to test whether the mode of transport was significant to length of hospital stay in EMS and non-EMS clients. Out of 308 patients identified during the study period, 232 were transported through EMS and 76 through non-EMS. The two groups were similar with regard to mortality and length of stay. The crude mortality rate was 30.6% (95% confidence interval [CI]: 24.64-36.53) in the EMS group and 28.9% (95% CI: 18.44-38.76) in the non-EMS group ( p = 0.785). The average length of hospital stay was 9 days (interquartile range [IQR] = 8, 95% CI: 7.3-10.1) for the EMS group and 8 days (IQR = 9.5, 95% CI: 6.7-10.9) for the non-EMS group ( p = 0.803). Multivariate analysis showed that of the study variables, only the injury severity score (ISS) and Glasgow coma score (GCS) were significant to mortality ( p < 0.01), and GCS was more significant to the length of hospital stay ( p < 0.01). There was no significant difference between the EMS and non-EMS groups as they relate to mortality and length of stay in hospital. However, the mortality and length of hospital stay was statistically significant to ISS and GCS.

Linear and nonlinear measures of fetal heart rate patterns evaluated on very short fetal magnetocardiograms.

PubMed

Moraes, Eder Rezende; Murta, Luiz Otavio; Baffa, Oswaldo; Wakai, Ronald T; Comani, Silvia

2012-10-01

We analyzed the effectiveness of linear short- and long-term variability time domain parameters, an index of sympatho-vagal balance (SDNN/RMSSD) and entropy in differentiating fetal heart rate patterns (fHRPs) on the fetal heart rate (fHR) series of 5, 3 and 2 min duration reconstructed from 46 fetal magnetocardiograms. Gestational age (GA) varied from 21 to 38 weeks. FHRPs were classified based on the fHR standard deviation. In sleep states, we observed that vagal influence increased with GA, and entropy significantly increased (decreased) with GA (SDNN/RMSSD), demonstrating that a prevalence of vagal activity with autonomous nervous system maturation may be associated with increased sleep state complexity. In active wakefulness, we observed a significant negative (positive) correlation of short-term (long-term) variability parameters with SDNN/RMSSD. ANOVA statistics demonstrated that long-term irregularity and standard deviation of normal-to-normal beat intervals (SDNN) best differentiated among fHRPs. Our results confirm that short- and long-term variability parameters are useful to differentiate between quiet and active states, and that entropy improves the characterization of sleep states. All measures differentiated fHRPs more effectively on very short HR series, as a result of the fMCG high temporal resolution and of the intrinsic timescales of the events that originate the different fHRPs.

Effects of Heart Rate Variability Biofeedback on EEG Alpha Asymmetry and Anxiety Symptoms in Male Athletes: A Pilot Study.

PubMed

Dziembowska, Inga; Izdebski, Paweł; Rasmus, Anna; Brudny, Janina; Grzelczak, Marta; Cysewski, Piotr

2016-06-01

Heart rate variability biofeedback (HRV-BFB) has been shown as useful tool to manage stress in various populations. The present study was designed to investigate whether the biofeedback-based stress management tool consisting of rhythmic breathing, actively self-generated positive emotions and a portable biofeedback device induce changes in athletes' HRV, EEG patterns, and self-reported anxiety and self-esteem. The study involved 41 healthy male athletes, aged 16-21 (mean 18.34 ± 1.36) years. Participants were randomly divided into two groups: biofeedback and control. Athletes in the biofeedback group received HRV biofeedback training, athletes in the control group didn't receive any intervention. During the randomized controlled trial (days 0-21), the mean anxiety score declined significantly for the intervention group (change-4 p < 0.001) but not for the control group (p = 0.817). In addition, as compared to the control, athletes in biofeedback group showed substantial and statistically significant improvement in heart rate variability indices and changes in power spectra of both theta and alpha brain waves, and alpha asymmetry. These changes suggest better self-control in the central nervous system and better flexibility of the autonomic nervous system in the group that received biofeedback training. A HRV biofeedback-based stress management tool may be beneficial for stress reduction for young male athletes.

The effects of competition on premiums: using United Healthcare's 2015 entry into Affordable Care Act's marketplaces as an instrumental variable.

PubMed

Agirdas, Cagdas; Krebs, Robert J; Yano, Masato

2018-01-08

One goal of the Affordable Care Act is to increase insurance coverage by improving competition and lowering premiums. To facilitate this goal, the federal government enacted online marketplaces in the 395 rating areas spanning 34 states that chose not to establish their own state-run marketplaces. Few multivariate regression studies analyzing the effects of competition on premiums suffer from endogeneity, due to simultaneity and omitted variable biases. However, United Healthcare's decision to enter these marketplaces in 2015 provides the researcher with an opportunity to address this endogeneity problem. Exploiting the variation caused by United Healthcare's entry decision as an instrument for competition, we study the impact of competition on premiums during the first 2 years of these marketplaces. Combining panel data from five different sources and controlling for 12 variables, we find that one more insurer in a rating area leads to a 6.97% reduction in the second-lowest-priced silver plan premium, which is larger than the estimated effects in existing literature. Furthermore, we run a threshold analysis and find that competition's effects on premiums become statistically insignificant if there are four or more insurers in a rating area. These findings are robust to alternative measures of premiums, inclusion of a non-linear term in the regression models and a county-level analysis.

Quantifying Precipitation Variability and Relative Erosion Rates on Titan Using a GCM and Implications for Observed Geomorphology

NASA Astrophysics Data System (ADS)

Faulk, S.; Moon, S.; Mitchell, J.; Lora, J. M.

2016-12-01

Titan's zonal-mean precipitation behavior has been widely investigated using general circulation models (GCMs), but the spatial and temporal variability of rainfall in Titan's active hydrologic cycle is less well understood. We conduct statistical analyses of rainfall, diagnosed from GCM simulations of Titan's atmosphere, to determine storm intensity and frequency. Intense storms of methane have been proposed to be critical for enabling mechanical erosion of Titan's surface, as indicated by extensive observations of dendritic valley networks. Using precipitation outputs from the Titan Atmospheric Model (TAM), a GCM shown to realistically simulate many features of Titan's atmosphere, we quantify the precipitation variability and resulting relative erosion rates within eight separate latitude bins for a variety of initial surface liquid distributions. We find that while the overall wettest regions are indeed the poles, the most intense rainfall generally occurs in the high mid-latitudes, between 45-67.5 degrees, consistent with recent geomorphological observations of alluvial fans concentrated at those latitudes. We also find that precipitation rates necessary for surface erosion, as estimated by Perron et al. (2006) J. Geophys. Res. 111, E11001, frequently occur at all latitudes, with recurrence intervals of less than one Titan year. Such analysis is crucial towards understanding the complex interaction between Titan's atmosphere and surface and defining the influence of precipitation on observed geomorphology.

Estimating and mapping ecological processes influencing microbial community assembly

PubMed Central

Stegen, James C.; Lin, Xueju; Fredrickson, Jim K.; Konopka, Allan E.

2015-01-01

Ecological community assembly is governed by a combination of (i) selection resulting from among-taxa differences in performance; (ii) dispersal resulting from organismal movement; and (iii) ecological drift resulting from stochastic changes in population sizes. The relative importance and nature of these processes can vary across environments. Selection can be homogeneous or variable, and while dispersal is a rate, we conceptualize extreme dispersal rates as two categories; dispersal limitation results from limited exchange of organisms among communities, and homogenizing dispersal results from high levels of organism exchange. To estimate the influence and spatial variation of each process we extend a recently developed statistical framework, use a simulation model to evaluate the accuracy of the extended framework, and use the framework to examine subsurface microbial communities over two geologic formations. For each subsurface community we estimate the degree to which it is influenced by homogeneous selection, variable selection, dispersal limitation, and homogenizing dispersal. Our analyses revealed that the relative influences of these ecological processes vary substantially across communities even within a geologic formation. We further identify environmental and spatial features associated with each ecological process, which allowed mapping of spatial variation in ecological-process-influences. The resulting maps provide a new lens through which ecological systems can be understood; in the subsurface system investigated here they revealed that the influence of variable selection was associated with the rate at which redox conditions change with subsurface depth. PMID:25983725

Statistical analysis of tire treadwear data

DOT National Transportation Integrated Search

1985-03-01

This report describes the results of a statistical analysis of the treadwear : variability of radial tires subjected to the Uniform Tire Quality Grading (UTQG) : standard. Because unexplained variability in the treadwear portion of the standard : cou...

Predictors of long-term compliance in attending a worksite hypertension programme.

PubMed

Landers, R; Riccobene, A; Beyreuther, M; Neusy, A J

1993-12-01

Variables such as patient's anxiety, knowledge, number of medication changes, medication-induced side-effects and programme-derived benefits and conveniences have been reported or theorised to be important determinants of patient's attendance at worksite hypertension programmes. This study investigates whether these variables have predictive value in differentiating compliers from noncompliers attending a union-sponsored worksite hypertension programme for at least five years. Scores were created from a questionnaire distributed to 243 patients with a response rate of 98%. Compliance was defined as missing < or = 25% of scheduled clinic appointments. By discriminant statistical analysis scores for patient's anxiety, knowledge, number of medication changes, medication side-effects, perceived benefits and conveniences failed to show any predictive value for patient's compliance with appointment keeping.

Learning (Not) to Talk about Race: Investigating What Doctoral Students Learn about Race Variables and Statistical Modeling

ERIC Educational Resources Information Center

Armijo, Michael; Lundy-Wagner, Valerie; Merrill, Elizabeth

2012-01-01

This paper asks how doctoral students understand the use of race variables in statistical modeling. More specifically, it examines how doctoral students at two universities are trained to define, operationalize, and analyze race variables. The authors interviewed students and instructors in addition to conducting a document analysis of their texts…

Which Variables Associated with Data-Driven Instruction Are Believed to Best Predict Urban Student Achievement?

ERIC Educational Resources Information Center

Greer, Wil

2013-01-01

This study identified the variables associated with data-driven instruction (DDI) that are perceived to best predict student achievement. Of the DDI variables discussed in the literature, 51 of them had a sufficient enough research base to warrant statistical analysis. Of them, 26 were statistically significant. Multiple regression and an…

Hydromechanical Earthquake Nucleation Model Forecasts Onset, Peak, and Falling Rates of Induced Seismicity in Oklahoma and Kansas

NASA Astrophysics Data System (ADS)

Norbeck, J. H.; Rubinstein, J. L.

2018-04-01

The earthquake activity in Oklahoma and Kansas that began in 2008 reflects the most widespread instance of induced seismicity observed to date. We develop a reservoir model to calculate the hydrologic conditions associated with the activity of 902 saltwater disposal wells injecting into the Arbuckle aquifer. Estimates of basement fault stressing conditions inform a rate-and-state friction earthquake nucleation model to forecast the seismic response to injection. Our model replicates many salient features of the induced earthquake sequence, including the onset of seismicity, the timing of the peak seismicity rate, and the reduction in seismicity following decreased disposal activity. We present evidence for variable time lags between changes in injection and seismicity rates, consistent with the prediction from rate-and-state theory that seismicity rate transients occur over timescales inversely proportional to stressing rate. Given the efficacy of the hydromechanical model, as confirmed through a likelihood statistical test, the results of this study support broader integration of earthquake physics within seismic hazard analysis.

Critically evaluating the theory and performance of Bayesian analysis of macroevolutionary mixtures

PubMed Central

Moore, Brian R.; Höhna, Sebastian; May, Michael R.; Rannala, Bruce; Huelsenbeck, John P.

2016-01-01

Bayesian analysis of macroevolutionary mixtures (BAMM) has recently taken the study of lineage diversification by storm. BAMM estimates the diversification-rate parameters (speciation and extinction) for every branch of a study phylogeny and infers the number and location of diversification-rate shifts across branches of a tree. Our evaluation of BAMM reveals two major theoretical errors: (i) the likelihood function (which estimates the model parameters from the data) is incorrect, and (ii) the compound Poisson process prior model (which describes the prior distribution of diversification-rate shifts across branches) is incoherent. Using simulation, we demonstrate that these theoretical issues cause statistical pathologies; posterior estimates of the number of diversification-rate shifts are strongly influenced by the assumed prior, and estimates of diversification-rate parameters are unreliable. Moreover, the inability to correctly compute the likelihood or to correctly specify the prior for rate-variable trees precludes the use of Bayesian approaches for testing hypotheses regarding the number and location of diversification-rate shifts using BAMM. PMID:27512038

Does unemployment affect child abuse rates? Evidence from New York State.

PubMed

Raissian, Kerri M

2015-10-01

This article used child maltreatment reports from New York State from 2000 to 2010 to investigate the relationship between county level unemployment and county level child maltreatment rates. Models showed that a 1 percentage point increase in unemployment rates reduced the child report rate by approximately 4.25%. Report rates for young children (children under the age of 6) and older children (children ages 6 and over) responded similarly to changes in local unemployment, but the relationship between unemployment rates and child maltreatment reports did vary by a county's metropolitan designation. The negative relationship between unemployment and child maltreatment reports was largely contained to metropolitan counties. The relationship between unemployment and child maltreatment reports in non-metropolitan counties was often positive but not statistically significant. These findings were robust to a number of specifications. In alternate models, the county's mandated reporter employment rate was added as a control; the inclusion of this variable did not alter the results. Copyright © 2015 Elsevier Ltd. All rights reserved.

Incorporating GIS and remote sensing for census population disaggregation

NASA Astrophysics Data System (ADS)

Wu, Shuo-Sheng'derek'

Census data are the primary source of demographic data for a variety of researches and applications. For confidentiality issues and administrative purposes, census data are usually released to the public by aggregated areal units. In the United States, the smallest census unit is census blocks. Due to data aggregation, users of census data may have problems in visualizing population distribution within census blocks and estimating population counts for areas not coinciding with census block boundaries. The main purpose of this study is to develop methodology for estimating sub-block areal populations and assessing the estimation errors. The City of Austin, Texas was used as a case study area. Based on tax parcel boundaries and parcel attributes derived from ancillary GIS and remote sensing data, detailed urban land use classes were first classified using a per-field approach. After that, statistical models by land use classes were built to infer population density from other predictor variables, including four census demographic statistics (the Hispanic percentage, the married percentage, the unemployment rate, and per capita income) and three physical variables derived from remote sensing images and building footprints vector data (a landscape heterogeneity statistics, a building pattern statistics, and a building volume statistics). In addition to statistical models, deterministic models were proposed to directly infer populations from building volumes and three housing statistics, including the average space per housing unit, the housing unit occupancy rate, and the average household size. After population models were derived or proposed, how well the models predict populations for another set of sample blocks was assessed. The results show that deterministic models were more accurate than statistical models. Further, by simulating the base unit for modeling from aggregating blocks, I assessed how well the deterministic models estimate sub-unit-level populations. I also assessed the aggregation effects and the resealing effects on sub-unit estimates. Lastly, from another set of mixed-land-use sample blocks, a mixed-land-use model was derived and compared with a residential-land-use model. The results of per-field land use classification are satisfactory with a Kappa accuracy statistics of 0.747. Model Assessments by land use show that population estimates for multi-family land use areas have higher errors than those for single-family land use areas, and population estimates for mixed land use areas have higher errors than those for residential land use areas. The assessments of sub-unit estimates using a simulation approach indicate that smaller areas show higher estimation errors, estimation errors do not relate to the base unit size, and resealing improves all levels of sub-unit estimates.

Mechanistic Considerations Used in the Development of the PROFIT PCI Failure Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pankaskie, P. J.

A fuel Pellet-Zircaloy Cladding (thermo-mechanical-chemical) Interactions (PC!) failure model for estimating the probability of failure in !ransient increases in power (PROFIT) was developed. PROFIT is based on 1) standard statistical methods applied to available PC! fuel failure data and 2) a mechanistic analysis of the environmental and strain-rate-dependent stress versus strain characteristics of Zircaloy cladding. The statistical analysis of fuel failures attributable to PCI suggested that parameters in addition to power, transient increase in power, and burnup are needed to define PCI fuel failures in terms of probability estimates with known confidence limits. The PROFIT model, therefore, introduces an environmentalmore » and strain-rate dependent strain energy absorption to failure (SEAF) concept to account for the stress versus strain anomalies attributable to interstitial-disloction interaction effects in the Zircaloy cladding. Assuming that the power ramping rate is the operating corollary of strain-rate in the Zircaloy cladding, then the variables of first order importance in the PCI fuel failure phenomenon are postulated to be: 1. pre-transient fuel rod power, P{sub I}, 2. transient increase in fuel rod power, {Delta}P, 3. fuel burnup, Bu, and 4. the constitutive material property of the Zircaloy cladding, SEAF.« less

Increased river alkalinization in the Eastern U.S.

PubMed

Kaushal, Sujay S; Likens, Gene E; Utz, Ryan M; Pace, Michael L; Grese, Melissa; Yepsen, Metthea

2013-09-17

The interaction between human activities and watershed geology is accelerating long-term changes in the carbon cycle of rivers. We evaluated changes in bicarbonate alkalinity, a product of chemical weathering, and tested for long-term trends at 97 sites in the eastern United States draining over 260,000 km(2). We observed statistically significant increasing trends in alkalinity at 62 of the 97 sites, while remaining sites exhibited no significant decreasing trends. Over 50% of study sites also had statistically significant increasing trends in concentrations of calcium (another product of chemical weathering) where data were available. River alkalinization rates were significantly related to watershed carbonate lithology, acid deposition, and topography. These three variables explained ~40% of variation in river alkalinization rates. The strongest predictor of river alkalinization rates was carbonate lithology. The most rapid rates of river alkalinization occurred at sites with highest inputs of acid deposition and highest elevation. The rise of alkalinity in many rivers throughout the Eastern U.S. suggests human-accelerated chemical weathering, in addition to previously documented impacts of mining and land use. Increased river alkalinization has major environmental implications including impacts on water hardness and salinization of drinking water, alterations of air-water exchange of CO2, coastal ocean acidification, and the influence of bicarbonate availability on primary production.

Systematic review and meta-analysis of dropout rates in individual psychotherapy for generalized anxiety disorder.

PubMed

Gersh, Elon; Hallford, David J; Rice, Simon M; Kazantzis, Nikolaos; Gersh, Hannah; Gersh, Benji; McCarty, Carolyn A

2017-12-01

Despite being a relatively prevalent and debilitating disorder, Generalized Anxiety Disorder (GAD) is the second least studied anxiety disorder and among the most difficult to treat. Dropout from psychotherapy is concerning as it is associated with poorer outcomes, leads to service inefficiencies and can disproportionately affect disadvantaged populations. No study to date has calculated a weighted mean dropout rate for GAD and explored associated correlates. A systematic review was conducted using PsycINFO, Medline and Embase databases, identifying studies investigating individual psychotherapies for adults with GAD. Forty-five studies, involving 2224 participants, were identified for meta-analysis. The weighted mean dropout rate was 16.99% (95% confidence interval 14.42%-19.91%). The Q-statistic indicated significant heterogeneity among studies. Moderator analysis and meta-regressions indicated no statistically significant effect of client age, sex, symptom severity, comorbidity, treatment type, study type (randomized trial or not), study quality, number of sessions or therapist experience. In research investigating psychotherapy for GAD, approximately one in six clients can be expected to drop out of treatment. Dropout rate was not significantly moderated by the client, therapist or treatment variables investigated. Future research should specify the definition of dropout, reasons for dropout and associated correlates to assist the field's progression. Copyright © 2017 Elsevier Ltd. All rights reserved.

Statistical Analysis of Time-Series from Monitoring of Active Volcanic Vents

NASA Astrophysics Data System (ADS)

Lachowycz, S.; Cosma, I.; Pyle, D. M.; Mather, T. A.; Rodgers, M.; Varley, N. R.

2016-12-01

Despite recent advances in the collection and analysis of time-series from volcano monitoring, and the resulting insights into volcanic processes, challenges remain in forecasting and interpreting activity from near real-time analysis of monitoring data. Statistical methods have potential to characterise the underlying structure and facilitate intercomparison of these time-series, and so inform interpretation of volcanic activity. We explore the utility of multiple statistical techniques that could be widely applicable to monitoring data, including Shannon entropy and detrended fluctuation analysis, by their application to various data streams from volcanic vents during periods of temporally variable activity. Each technique reveals changes through time in the structure of some of the data that were not apparent from conventional analysis. For example, we calculate the Shannon entropy (a measure of the randomness of a signal) of time-series from the recent dome-forming eruptions of Volcán de Colima (Mexico) and Soufrière Hills (Montserrat). The entropy of real-time seismic measurements and the count rate of certain volcano-seismic event types from both volcanoes is found to be temporally variable, with these data generally having higher entropy during periods of lava effusion and/or larger explosions. In some instances, the entropy shifts prior to or coincident with changes in seismic or eruptive activity, some of which were not clearly recognised by real-time monitoring. Comparison with other statistics demonstrates the sensitivity of the entropy to the data distribution, but that it is distinct from conventional statistical measures such as coefficient of variation. We conclude that each analysis technique examined could provide valuable insights for interpretation of diverse monitoring time-series.

Statistical Association Criteria in Forensic Psychiatry–A criminological evaluation of casuistry

PubMed Central

Gheorghiu, V; Buda, O; Popescu, I; Trandafir, MS

2011-01-01

Purpose. Identification of potential shared primary psychoprophylaxis and crime prevention is measured by analyzing the rate of commitments for patients–subjects to forensic examination. Material and method. The statistic trial is a retrospective, document–based study. The statistical lot consists of 770 initial examination reports performed and completed during the whole year 2007, primarily analyzed in order to summarize the data within the National Institute of Forensic Medicine, Bucharest, Romania (INML), with one of the group variables being ‘particularities of the psychiatric patient history’, containing the items ‘forensic onset’, ‘commitments within the last year prior to the examination’ and ‘absence of commitments within the last year prior to the examination’. The method used was the Kendall bivariate correlation. For this study, the authors separately analyze only the two items regarding commitments by other correlation alternatives and by modern, elaborate statistical analyses, i.e. recording of the standard case study variables, Kendall bivariate correlation, cross tabulation, factor analysis and hierarchical cluster analysis. Results. The results are varied, from theoretically presumed clinical nosography (such as schizophrenia or manic depression), to non–presumed (conduct disorders) or unexpected behavioral acts, and therefore difficult to interpret. Conclusions. One took into consideration the features of the batch as well as the results of the previous standard correlation of the whole statistical lot. The authors emphasize the role of medical security measures that are actually applied in the therapeutic management in general and in risk and second offence management in particular, as well as the role of forensic psychiatric examinations in the detection of certain aspects related to the monitoring of mental patients. PMID:21505571