Sensitivity of airborne fluorosensor measurements to linear vertical gradients in chlorophyll concentration

NASA Technical Reports Server (NTRS)

Venable, D. D.; Punjabi, A. R.; Poole, L. R.

1984-01-01

A semianalytic Monte Carlo radiative transfer simulation model for airborne laser fluorosensors has been extended to investigate the effects of inhomogeneities in the vertical distribution of phytoplankton concentrations in clear seawater. Simulation results for linearly varying step concentrations of chlorophyll are presented. The results indicate that statistically significant differences can be seen under certain conditions in the water Raman-normalized fluorescence signals between nonhomogeneous and homogeneous cases. A statistical test has been used to establish ranges of surface concentrations and/or verticl gradients in which calibration by surface samples would by inappropriate, and the results are discussed.

Estimating cosmic velocity fields from density fields and tidal tensors

NASA Astrophysics Data System (ADS)

Kitaura, Francisco-Shu; Angulo, Raul E.; Hoffman, Yehuda; Gottlöber, Stefan

2012-10-01

In this work we investigate the non-linear and non-local relation between cosmological density and peculiar velocity fields. Our goal is to provide an algorithm for the reconstruction of the non-linear velocity field from the fully non-linear density. We find that including the gravitational tidal field tensor using second-order Lagrangian perturbation theory based upon an estimate of the linear component of the non-linear density field significantly improves the estimate of the cosmic flow in comparison to linear theory not only in the low density, but also and more dramatically in the high-density regions. In particular we test two estimates of the linear component: the lognormal model and the iterative Lagrangian linearization. The present approach relies on a rigorous higher order Lagrangian perturbation theory analysis which incorporates a non-local relation. It does not require additional fitting from simulations being in this sense parameter free, it is independent of statistical-geometrical optimization and it is straightforward and efficient to compute. The method is demonstrated to yield an unbiased estimator of the velocity field on scales ≳5 h-1 Mpc with closely Gaussian distributed errors. Moreover, the statistics of the divergence of the peculiar velocity field is extremely well recovered showing a good agreement with the true one from N-body simulations. The typical errors of about 10 km s-1 (1σ confidence intervals) are reduced by more than 80 per cent with respect to linear theory in the scale range between 5 and 10 h-1 Mpc in high-density regions (δ > 2). We also find that iterative Lagrangian linearization is significantly superior in the low-density regime with respect to the lognormal model.

Selected Oral Health Indicators in the United States, 2005-2008

MedlinePlus

... errors of the percentages were estimated using Taylor series linearization, to take into account the complex sampling design. The statistical significance of differences between estimates were ...

2D versus 3D in the kinematic analysis of the horse at the trot.

PubMed

Miró, F; Santos, R; Garrido-Castro, J L; Galisteo, A M; Medina-Carnicer, R

2009-08-01

The handled trot of three Lusitano Purebred stallions was analyzed by using 2D and 3D kinematical analysis methods. Using the same capture and analysis system, 2D and 3D data of some linear (stride length, maximal height of the hoof trajectories) and angular (angular range of motion, inclination of bone segments) variables were obtained. A paired Student T-test was performed in order to detect statistically significant differences between data resulting from the two methodologies With respect to the angular variables, there were significant differences in scapula inclination, shoulder angle, cannon inclination and protraction-retraction angle in the forelimb variables, but none of them were statistically different in the hind limb. Differences between the two methods were found in most of the linear variables analyzed.

Evaluation of airborne lidar data to predict vegetation Presence/Absence

USGS Publications Warehouse

Palaseanu-Lovejoy, M.; Nayegandhi, A.; Brock, J.; Woodman, R.; Wright, C.W.

2009-01-01

This study evaluates the capabilities of the Experimental Advanced Airborne Research Lidar (EAARL) in delineating vegetation assemblages in Jean Lafitte National Park, Louisiana. Five-meter-resolution grids of bare earth, canopy height, canopy-reflection ratio, and height of median energy were derived from EAARL data acquired in September 2006. Ground-truth data were collected along transects to assess species composition, canopy cover, and ground cover. To decide which model is more accurate, comparisons of general linear models and generalized additive models were conducted using conventional evaluation methods (i.e., sensitivity, specificity, Kappa statistics, and area under the curve) and two new indexes, net reclassification improvement and integrated discrimination improvement. Generalized additive models were superior to general linear models in modeling presence/absence in training vegetation categories, but no statistically significant differences between the two models were achieved in determining the classification accuracy at validation locations using conventional evaluation methods, although statistically significant improvements in net reclassifications were observed. ?? 2009 Coastal Education and Research Foundation.

Subjective audio quality evaluation of embedded-optimization-based distortion precompensation algorithms.

PubMed

Defraene, Bruno; van Waterschoot, Toon; Diehl, Moritz; Moonen, Marc

2016-07-01

Subjective audio quality evaluation experiments have been conducted to assess the performance of embedded-optimization-based precompensation algorithms for mitigating perceptible linear and nonlinear distortion in audio signals. It is concluded with statistical significance that the perceived audio quality is improved by applying an embedded-optimization-based precompensation algorithm, both in case (i) nonlinear distortion and (ii) a combination of linear and nonlinear distortion is present. Moreover, a significant positive correlation is reported between the collected subjective and objective PEAQ audio quality scores, supporting the validity of using PEAQ to predict the impact of linear and nonlinear distortion on the perceived audio quality.

Multiple linear regression analysis

NASA Technical Reports Server (NTRS)

Edwards, T. R.

1980-01-01

Program rapidly selects best-suited set of coefficients. User supplies only vectors of independent and dependent data and specifies confidence level required. Program uses stepwise statistical procedure for relating minimal set of variables to set of observations; final regression contains only most statistically significant coefficients. Program is written in FORTRAN IV for batch execution and has been implemented on NOVA 1200.

Does transport time help explain the high trauma mortality rates in rural areas? New and traditional predictors assessed by new and traditional statistical methods

PubMed Central

Røislien, Jo; Lossius, Hans Morten; Kristiansen, Thomas

2015-01-01

Background Trauma is a leading global cause of death. Trauma mortality rates are higher in rural areas, constituting a challenge for quality and equality in trauma care. The aim of the study was to explore population density and transport time to hospital care as possible predictors of geographical differences in mortality rates, and to what extent choice of statistical method might affect the analytical results and accompanying clinical conclusions. Methods Using data from the Norwegian Cause of Death registry, deaths from external causes 1998–2007 were analysed. Norway consists of 434 municipalities, and municipality population density and travel time to hospital care were entered as predictors of municipality mortality rates in univariate and multiple regression models of increasing model complexity. We fitted linear regression models with continuous and categorised predictors, as well as piecewise linear and generalised additive models (GAMs). Models were compared using Akaike's information criterion (AIC). Results Population density was an independent predictor of trauma mortality rates, while the contribution of transport time to hospital care was highly dependent on choice of statistical model. A multiple GAM or piecewise linear model was superior, and similar, in terms of AIC. However, while transport time was statistically significant in multiple models with piecewise linear or categorised predictors, it was not in GAM or standard linear regression. Conclusions Population density is an independent predictor of trauma mortality rates. The added explanatory value of transport time to hospital care is marginal and model-dependent, highlighting the importance of exploring several statistical models when studying complex associations in observational data. PMID:25972600

Tools for Basic Statistical Analysis

NASA Technical Reports Server (NTRS)

Luz, Paul L.

2005-01-01

Statistical Analysis Toolset is a collection of eight Microsoft Excel spreadsheet programs, each of which performs calculations pertaining to an aspect of statistical analysis. These programs present input and output data in user-friendly, menu-driven formats, with automatic execution. The following types of calculations are performed: Descriptive statistics are computed for a set of data x(i) (i = 1, 2, 3 . . . ) entered by the user. Normal Distribution Estimates will calculate the statistical value that corresponds to cumulative probability values, given a sample mean and standard deviation of the normal distribution. Normal Distribution from two Data Points will extend and generate a cumulative normal distribution for the user, given two data points and their associated probability values. Two programs perform two-way analysis of variance (ANOVA) with no replication or generalized ANOVA for two factors with four levels and three repetitions. Linear Regression-ANOVA will curvefit data to the linear equation y=f(x) and will do an ANOVA to check its significance.

An R2 statistic for fixed effects in the linear mixed model.

PubMed

Edwards, Lloyd J; Muller, Keith E; Wolfinger, Russell D; Qaqish, Bahjat F; Schabenberger, Oliver

2008-12-20

Statisticians most often use the linear mixed model to analyze Gaussian longitudinal data. The value and familiarity of the R(2) statistic in the linear univariate model naturally creates great interest in extending it to the linear mixed model. We define and describe how to compute a model R(2) statistic for the linear mixed model by using only a single model. The proposed R(2) statistic measures multivariate association between the repeated outcomes and the fixed effects in the linear mixed model. The R(2) statistic arises as a 1-1 function of an appropriate F statistic for testing all fixed effects (except typically the intercept) in a full model. The statistic compares the full model with a null model with all fixed effects deleted (except typically the intercept) while retaining exactly the same covariance structure. Furthermore, the R(2) statistic leads immediately to a natural definition of a partial R(2) statistic. A mixed model in which ethnicity gives a very small p-value as a longitudinal predictor of blood pressure (BP) compellingly illustrates the value of the statistic. In sharp contrast to the extreme p-value, a very small R(2) , a measure of statistical and scientific importance, indicates that ethnicity has an almost negligible association with the repeated BP outcomes for the study.

A SIGNIFICANCE TEST FOR THE LASSO1

PubMed Central

Lockhart, Richard; Taylor, Jonathan; Tibshirani, Ryan J.; Tibshirani, Robert

2014-01-01

In the sparse linear regression setting, we consider testing the significance of the predictor variable that enters the current lasso model, in the sequence of models visited along the lasso solution path. We propose a simple test statistic based on lasso fitted values, called the covariance test statistic, and show that when the true model is linear, this statistic has an Exp(1) asymptotic distribution under the null hypothesis (the null being that all truly active variables are contained in the current lasso model). Our proof of this result for the special case of the first predictor to enter the model (i.e., testing for a single significant predictor variable against the global null) requires only weak assumptions on the predictor matrix X. On the other hand, our proof for a general step in the lasso path places further technical assumptions on X and the generative model, but still allows for the important high-dimensional case p > n, and does not necessarily require that the current lasso model achieves perfect recovery of the truly active variables. Of course, for testing the significance of an additional variable between two nested linear models, one typically uses the chi-squared test, comparing the drop in residual sum of squares (RSS) to a χ12 distribution. But when this additional variable is not fixed, and has been chosen adaptively or greedily, this test is no longer appropriate: adaptivity makes the drop in RSS stochastically much larger than χ12 under the null hypothesis. Our analysis explicitly accounts for adaptivity, as it must, since the lasso builds an adaptive sequence of linear models as the tuning parameter λ decreases. In this analysis, shrinkage plays a key role: though additional variables are chosen adaptively, the coefficients of lasso active variables are shrunken due to the l1 penalty. Therefore, the test statistic (which is based on lasso fitted values) is in a sense balanced by these two opposing properties—adaptivity and shrinkage—and its null distribution is tractable and asymptotically Exp(1). PMID:25574062

Coronal Holes and Solar f -Mode Wave Scattering Off Linear Boundaries

NASA Astrophysics Data System (ADS)

Hess Webber, Shea A.

2016-11-01

Coronal holes (CHs) are solar atmospheric features that have reduced emission in the extreme ultraviolet (EUV) spectrum due to decreased plasma density along open magnetic field lines. CHs are the source of the fast solar wind, can influence other solar activity, and track the solar cycle. Our interest in them deals with boundary detection near the solar surface. Detecting CH boundaries is important for estimating their size and tracking their evolution through time, as well as for comparing the physical properties within and outside of the feature. In this thesis, we (1) investigate CHs using statistical properties and image processing techniques on EUV images to detect CH boundaries in the low corona and chromosphere. SOHO/EIT data is used to locate polar CH boundaries on the solar limb, which are then tracked through two solar cycles. Additionally, we develop an edge-detection algorithm that we use on SDO/AIA data of a polar hole extension with an approximately linear boundary. These locations are used later to inform part of the helioseismic investigation; (2) develop a local time-distance (TD) helioseismology technique that can be used to detect CH boundary signatures at the photospheric level. We employ a new averaging scheme that makes use of the quasi-linear topology of elongated scattering regions, and create simulated data to test the new technique and compare results of some associated assumptions. This method enhances the wave propagation signal in the direction perpendicular to the linear feature and reduces the computational time of the TD analysis. We also apply a new statistical analysis of the significance of differences between the TD results; and (3) apply the TD techniques to solar CH data from SDO/HMI. The data correspond to the AIA data used in the edge-detection algorithm on EUV images. We look for statistically significant differences between the TD results inside and outside the CH region. In investigation (1), we found that the polar CH areas did not change significantly between minima, even though the magnetic field strength weakened. The results of (2) indicate that TD helioseismology techniques can be extended to make use of feature symmetry in the domain. The linear technique used here produces results that differ between a linear scattering region and a circular scattering region, shown using the simulated data algorithm. This suggests that using usual TD methods on scattering regions that are radially asymmetric may produce results with signatures of the anisotropy. The results of (1) and (3) indicate that the TD signal within our CH is statistically significantly different compared to unrelated quiet sun results. Surprisingly, the TD results in the quiet sun near the CH boundary also show significant differences compared to the separate quiet sun.

Biomarker selection for medical diagnosis using the partial area under the ROC curve

PubMed Central

2014-01-01

Background A biomarker is usually used as a diagnostic or assessment tool in medical research. Finding an ideal biomarker is not easy and combining multiple biomarkers provides a promising alternative. Moreover, some biomarkers based on the optimal linear combination do not have enough discriminatory power. As a result, the aim of this study was to find the significant biomarkers based on the optimal linear combination maximizing the pAUC for assessment of the biomarkers. Methods Under the binormality assumption we obtain the optimal linear combination of biomarkers maximizing the partial area under the receiver operating characteristic curve (pAUC). Related statistical tests are developed for assessment of a biomarker set and of an individual biomarker. Stepwise biomarker selections are introduced to identify those biomarkers of statistical significance. Results The results of simulation study and three real examples, Duchenne Muscular Dystrophy disease, heart disease, and breast tissue example are used to show that our methods are most suitable biomarker selection for the data sets of a moderate number of biomarkers. Conclusions Our proposed biomarker selection approaches can be used to find the significant biomarkers based on hypothesis testing. PMID:24410929

New Statistics for Testing Differential Expression of Pathways from Microarray Data

NASA Astrophysics Data System (ADS)

Siu, Hoicheong; Dong, Hua; Jin, Li; Xiong, Momiao

Exploring biological meaning from microarray data is very important but remains a great challenge. Here, we developed three new statistics: linear combination test, quadratic test and de-correlation test to identify differentially expressed pathways from gene expression profile. We apply our statistics to two rheumatoid arthritis datasets. Notably, our results reveal three significant pathways and 275 genes in common in two datasets. The pathways we found are meaningful to uncover the disease mechanisms of rheumatoid arthritis, which implies that our statistics are a powerful tool in functional analysis of gene expression data.

SOCR Analyses - an Instructional Java Web-based Statistical Analysis Toolkit.

PubMed

Chu, Annie; Cui, Jenny; Dinov, Ivo D

2009-03-01

The Statistical Online Computational Resource (SOCR) designs web-based tools for educational use in a variety of undergraduate courses (Dinov 2006). Several studies have demonstrated that these resources significantly improve students' motivation and learning experiences (Dinov et al. 2008). SOCR Analyses is a new component that concentrates on data modeling and analysis using parametric and non-parametric techniques supported with graphical model diagnostics. Currently implemented analyses include commonly used models in undergraduate statistics courses like linear models (Simple Linear Regression, Multiple Linear Regression, One-Way and Two-Way ANOVA). In addition, we implemented tests for sample comparisons, such as t-test in the parametric category; and Wilcoxon rank sum test, Kruskal-Wallis test, Friedman's test, in the non-parametric category. SOCR Analyses also include several hypothesis test models, such as Contingency tables, Friedman's test and Fisher's exact test.The code itself is open source (http://socr.googlecode.com/), hoping to contribute to the efforts of the statistical computing community. The code includes functionality for each specific analysis model and it has general utilities that can be applied in various statistical computing tasks. For example, concrete methods with API (Application Programming Interface) have been implemented in statistical summary, least square solutions of general linear models, rank calculations, etc. HTML interfaces, tutorials, source code, activities, and data are freely available via the web (www.SOCR.ucla.edu). Code examples for developers and demos for educators are provided on the SOCR Wiki website.In this article, the pedagogical utilization of the SOCR Analyses is discussed, as well as the underlying design framework. As the SOCR project is on-going and more functions and tools are being added to it, these resources are constantly improved. The reader is strongly encouraged to check the SOCR site for most updated information and newly added models.

A Systematic Review and Meta-Regression Analysis of Lung Cancer Risk and Inorganic Arsenic in Drinking Water.

PubMed

Lamm, Steven H; Ferdosi, Hamid; Dissen, Elisabeth K; Li, Ji; Ahn, Jaeil

2015-12-07

High levels (> 200 µg/L) of inorganic arsenic in drinking water are known to be a cause of human lung cancer, but the evidence at lower levels is uncertain. We have sought the epidemiological studies that have examined the dose-response relationship between arsenic levels in drinking water and the risk of lung cancer over a range that includes both high and low levels of arsenic. Regression analysis, based on six studies identified from an electronic search, examined the relationship between the log of the relative risk and the log of the arsenic exposure over a range of 1-1000 µg/L. The best-fitting continuous meta-regression model was sought and found to be a no-constant linear-quadratic analysis where both the risk and the exposure had been logarithmically transformed. This yielded both a statistically significant positive coefficient for the quadratic term and a statistically significant negative coefficient for the linear term. Sub-analyses by study design yielded results that were similar for both ecological studies and non-ecological studies. Statistically significant X-intercepts consistently found no increased level of risk at approximately 100-150 µg/L arsenic.

A Systematic Review and Meta-Regression Analysis of Lung Cancer Risk and Inorganic Arsenic in Drinking Water

PubMed Central

Lamm, Steven H.; Ferdosi, Hamid; Dissen, Elisabeth K.; Li, Ji; Ahn, Jaeil

2015-01-01

High levels (> 200 µg/L) of inorganic arsenic in drinking water are known to be a cause of human lung cancer, but the evidence at lower levels is uncertain. We have sought the epidemiological studies that have examined the dose-response relationship between arsenic levels in drinking water and the risk of lung cancer over a range that includes both high and low levels of arsenic. Regression analysis, based on six studies identified from an electronic search, examined the relationship between the log of the relative risk and the log of the arsenic exposure over a range of 1–1000 µg/L. The best-fitting continuous meta-regression model was sought and found to be a no-constant linear-quadratic analysis where both the risk and the exposure had been logarithmically transformed. This yielded both a statistically significant positive coefficient for the quadratic term and a statistically significant negative coefficient for the linear term. Sub-analyses by study design yielded results that were similar for both ecological studies and non-ecological studies. Statistically significant X-intercepts consistently found no increased level of risk at approximately 100–150 µg/L arsenic. PMID:26690190

miRNA Temporal Analyzer (mirnaTA): a bioinformatics tool for identifying differentially expressed microRNAs in temporal studies using normal quantile transformation.

PubMed

Cer, Regina Z; Herrera-Galeano, J Enrique; Anderson, Joseph J; Bishop-Lilly, Kimberly A; Mokashi, Vishwesh P

2014-01-01

Understanding the biological roles of microRNAs (miRNAs) is a an active area of research that has produced a surge of publications in PubMed, particularly in cancer research. Along with this increasing interest, many open-source bioinformatics tools to identify existing and/or discover novel miRNAs in next-generation sequencing (NGS) reads become available. While miRNA identification and discovery tools are significantly improved, the development of miRNA differential expression analysis tools, especially in temporal studies, remains substantially challenging. Further, the installation of currently available software is non-trivial and steps of testing with example datasets, trying with one's own dataset, and interpreting the results require notable expertise and time. Subsequently, there is a strong need for a tool that allows scientists to normalize raw data, perform statistical analyses, and provide intuitive results without having to invest significant efforts. We have developed miRNA Temporal Analyzer (mirnaTA), a bioinformatics package to identify differentially expressed miRNAs in temporal studies. mirnaTA is written in Perl and R (Version 2.13.0 or later) and can be run across multiple platforms, such as Linux, Mac and Windows. In the current version, mirnaTA requires users to provide a simple, tab-delimited, matrix file containing miRNA name and count data from a minimum of two to a maximum of 20 time points and three replicates. To recalibrate data and remove technical variability, raw data is normalized using Normal Quantile Transformation (NQT), and linear regression model is used to locate any miRNAs which are differentially expressed in a linear pattern. Subsequently, remaining miRNAs which do not fit a linear model are further analyzed in two different non-linear methods 1) cumulative distribution function (CDF) or 2) analysis of variances (ANOVA). After both linear and non-linear analyses are completed, statistically significant miRNAs (P < 0.05) are plotted as heat maps using hierarchical cluster analysis and Euclidean distance matrix computation methods. mirnaTA is an open-source, bioinformatics tool to aid scientists in identifying differentially expressed miRNAs which could be further mined for biological significance. It is expected to provide researchers with a means of interpreting raw data to statistical summaries in a fast and intuitive manner.

Visual field progression with frequency-doubling matrix perimetry and standard automated perimetry in patients with glaucoma and in healthy controls.

PubMed

Redmond, Tony; O'Leary, Neil; Hutchison, Donna M; Nicolela, Marcelo T; Artes, Paul H; Chauhan, Balwantray C

2013-12-01

A new analysis method called permutation of pointwise linear regression measures the significance of deterioration over time at each visual field location, combines the significance values into an overall statistic, and then determines the likelihood of change in the visual field. Because the outcome is a single P value, individualized to that specific visual field and independent of the scale of the original measurement, the method is well suited for comparing techniques with different stimuli and scales. To test the hypothesis that frequency-doubling matrix perimetry (FDT2) is more sensitive than standard automated perimetry (SAP) in identifying visual field progression in glaucoma. Patients with open-angle glaucoma and healthy controls were examined by FDT2 and SAP, both with the 24-2 test pattern, on the same day at 6-month intervals in a longitudinal prospective study conducted in a hospital-based setting. Only participants with at least 5 examinations were included. Data were analyzed with permutation of pointwise linear regression. Permutation of pointwise linear regression is individualized to each participant, in contrast to current analyses in which the statistical significance is inferred from population-based approaches. Analyses were performed with both total deviation and pattern deviation. Sixty-four patients and 36 controls were included in the study. The median age, SAP mean deviation, and follow-up period were 65 years, -2.6 dB, and 5.4 years, respectively, in patients and 62 years, +0.4 dB, and 5.2 years, respectively, in controls. Using total deviation analyses, statistically significant deterioration was identified in 17% of patients with FDT2, in 34% of patients with SAP, and in 14% of patients with both techniques; in controls these percentages were 8% with FDT2, 31% with SAP, and 8% with both. Using pattern deviation analyses, statistically significant deterioration was identified in 16% of patients with FDT2, in 17% of patients with SAP, and in 3% of patients with both techniques; in controls these values were 3% with FDT2 and none with SAP. No evidence was found that FDT2 is more sensitive than SAP in identifying visual field deterioration. In about one-third of healthy controls, age-related deterioration with SAP reached statistical significance.

Error Analysis for RADAR Neighbor Matching Localization in Linear Logarithmic Strength Varying Wi-Fi Environment

PubMed Central

Tian, Zengshan; Xu, Kunjie; Yu, Xiang

2014-01-01

This paper studies the statistical errors for the fingerprint-based RADAR neighbor matching localization with the linearly calibrated reference points (RPs) in logarithmic received signal strength (RSS) varying Wi-Fi environment. To the best of our knowledge, little comprehensive analysis work has appeared on the error performance of neighbor matching localization with respect to the deployment of RPs. However, in order to achieve the efficient and reliable location-based services (LBSs) as well as the ubiquitous context-awareness in Wi-Fi environment, much attention has to be paid to the highly accurate and cost-efficient localization systems. To this end, the statistical errors by the widely used neighbor matching localization are significantly discussed in this paper to examine the inherent mathematical relations between the localization errors and the locations of RPs by using a basic linear logarithmic strength varying model. Furthermore, based on the mathematical demonstrations and some testing results, the closed-form solutions to the statistical errors by RADAR neighbor matching localization can be an effective tool to explore alternative deployment of fingerprint-based neighbor matching localization systems in the future. PMID:24683349

Error analysis for RADAR neighbor matching localization in linear logarithmic strength varying Wi-Fi environment.

PubMed

Zhou, Mu; Tian, Zengshan; Xu, Kunjie; Yu, Xiang; Wu, Haibo

2014-01-01

This paper studies the statistical errors for the fingerprint-based RADAR neighbor matching localization with the linearly calibrated reference points (RPs) in logarithmic received signal strength (RSS) varying Wi-Fi environment. To the best of our knowledge, little comprehensive analysis work has appeared on the error performance of neighbor matching localization with respect to the deployment of RPs. However, in order to achieve the efficient and reliable location-based services (LBSs) as well as the ubiquitous context-awareness in Wi-Fi environment, much attention has to be paid to the highly accurate and cost-efficient localization systems. To this end, the statistical errors by the widely used neighbor matching localization are significantly discussed in this paper to examine the inherent mathematical relations between the localization errors and the locations of RPs by using a basic linear logarithmic strength varying model. Furthermore, based on the mathematical demonstrations and some testing results, the closed-form solutions to the statistical errors by RADAR neighbor matching localization can be an effective tool to explore alternative deployment of fingerprint-based neighbor matching localization systems in the future.

Comparative evaluation of the accuracy of linear measurements between cone beam computed tomography and 3D microtomography.

PubMed

Mangione, Francesca; Meleo, Deborah; Talocco, Marco; Pecci, Raffaella; Pacifici, Luciano; Bedini, Rossella

2013-01-01

The aim of this study was to evaluate the influence of artifacts on the accuracy of linear measurements estimated with a common cone beam computed tomography (CBCT) system used in dental clinical practice, by comparing it with microCT system as standard reference. Ten bovine bone cylindrical samples containing one implant each, able to provide both points of reference and image quality degradation, have been scanned by CBCT and microCT systems. Thanks to the software of the two systems, for each cylindrical sample, two diameters taken at different levels, by using implants different points as references, have been measured. Results have been analyzed by ANOVA and a significant statistically difference has been found. Due to the obtained results, in this work it is possible to say that the measurements made with the two different instruments are still not statistically comparable, although in some samples were obtained similar performances and therefore not statistically significant. With the improvement of the hardware and software of CBCT systems, in the near future the two instruments will be able to provide similar performances.

Predicting Success in Psychological Statistics Courses.

PubMed

Lester, David

2016-06-01

Many students perform poorly in courses on psychological statistics, and it is useful to be able to predict which students will have difficulties. In a study of 93 undergraduates enrolled in Statistical Methods (18 men, 75 women; M age = 22.0 years, SD = 5.1), performance was significantly associated with sex (female students performed better) and proficiency in algebra in a linear regression analysis. Anxiety about statistics was not associated with course performance, indicating that basic mathematical skills are the best correlate for performance in statistics courses and can usefully be used to stream students into classes by ability. © The Author(s) 2016.

Linearised and non-linearised isotherm models optimization analysis by error functions and statistical means

PubMed Central

2014-01-01

In adsorption study, to describe sorption process and evaluation of best-fitting isotherm model is a key analysis to investigate the theoretical hypothesis. Hence, numerous statistically analysis have been extensively used to estimate validity of the experimental equilibrium adsorption values with the predicted equilibrium values. Several statistical error analysis were carried out. In the present study, the following statistical analysis were carried out to evaluate the adsorption isotherm model fitness, like the Pearson correlation, the coefficient of determination and the Chi-square test, have been used. The ANOVA test was carried out for evaluating significance of various error functions and also coefficient of dispersion were evaluated for linearised and non-linearised models. The adsorption of phenol onto natural soil (Local name Kalathur soil) was carried out, in batch mode at 30 ± 20 C. For estimating the isotherm parameters, to get a holistic view of the analysis the models were compared between linear and non-linear isotherm models. The result reveled that, among above mentioned error functions and statistical functions were designed to determine the best fitting isotherm. PMID:25018878

Massive parallelization of serial inference algorithms for a complex generalized linear model

PubMed Central

Suchard, Marc A.; Simpson, Shawn E.; Zorych, Ivan; Ryan, Patrick; Madigan, David

2014-01-01

Following a series of high-profile drug safety disasters in recent years, many countries are redoubling their efforts to ensure the safety of licensed medical products. Large-scale observational databases such as claims databases or electronic health record systems are attracting particular attention in this regard, but present significant methodological and computational concerns. In this paper we show how high-performance statistical computation, including graphics processing units, relatively inexpensive highly parallel computing devices, can enable complex methods in large databases. We focus on optimization and massive parallelization of cyclic coordinate descent approaches to fit a conditioned generalized linear model involving tens of millions of observations and thousands of predictors in a Bayesian context. We find orders-of-magnitude improvement in overall run-time. Coordinate descent approaches are ubiquitous in high-dimensional statistics and the algorithms we propose open up exciting new methodological possibilities with the potential to significantly improve drug safety. PMID:25328363

Ergonomics study on mobile phones for thumb physiology discomfort

NASA Astrophysics Data System (ADS)

Bendero, J. M. S.; Doon, M. E. R.; Quiogue, K. C. A.; Soneja, L. C.; Ong, N. R.; Sauli, Z.; Vairavan, R.

2017-09-01

The study was conducted on Filipino undergraduate college students and aimed to find out about the significant factors associated with mobile phone usage and its effect on thumb pain.A correlation-prediction analysisand Multiple Linear Regression was adopted and used as the main tool in determining the significant factors and coming up with predictive models on thumb related pain. With the use of the software Statistical Package for the Social Sciences or SPSS in conducting linear regression, 2 significant factors on thumb-related pain (percentage of time using portrait as screen orientation when text messaging, amount of time playing games using one hand in a day) were found.

Correlation of spleen metabolism assessed by 18F-FDG PET with serum interleukin-2 receptor levels and other biomarkers in patients with untreated sarcoidosis.

PubMed

Kalkanis, Alexandros; Kalkanis, Dimitrios; Drougas, Dimitrios; Vavougios, George D; Datseris, Ioannis; Judson, Marc A; Georgiou, Evangelos

2016-03-01

The objective of our study was to assess the possible relationship between splenic F-18-fluorodeoxyglucose (18F-FDG) uptake and other established biochemical markers of sarcoidosis activity. Thirty treatment-naive sarcoidosis patients were prospectively enrolled in this study. They underwent biochemical laboratory tests, including serum interleukin-2 receptor (sIL-2R), serum C-reactive protein, serum angiotensin-I converting enzyme, and 24-h urine calcium levels, and a whole-body combined 18F-FDG PET/computed tomography (PET/CT) scan as a part of an ongoing study at our institute. These biomarkers were statistically compared in these patients. A statistically significant linear dependence was detected between sIL-2R and log-transformed spleen-average standard uptake value (SUV avg) (R2=0.488, P<0.0001) and log-transformed spleen-maximum standard uptake value (SUV max) (R2=0.490, P<0.0001). sIL-2R levels and splenic size correlated linearly (Pearson's r=0.373, P=0.042). Multivariate linear regression analysis revealed that this correlation remained significant after age and sex adjustment (β=0.001, SE=0.001, P=0.024). No statistically significant associations were detected between (a) any two serum biomarkers or (b) between spleen-SUV measurements and any serum biomarker other than sIL-2R. Our analysis revealed an association between sIL-2R levels and spleen 18F-FDG uptake and size, whereas all other serum biomarkers were not significantly associated with each other or with PET 18F-FDG uptake. Our results suggest that splenic inflammation may be related to the systemic inflammatory response in sarcoidosis that may be associated with elevated sIL-2R levels.

Review and statistical analysis of the use of ultrasonic velocity for estimating the porosity fraction in polycrystalline materials

NASA Technical Reports Server (NTRS)

Roth, D. J.; Swickard, S. M.; Stang, D. B.; Deguire, M. R.

1991-01-01

A review and statistical analysis of the ultrasonic velocity method for estimating the porosity fraction in polycrystalline materials is presented. Initially, a semiempirical model is developed showing the origin of the linear relationship between ultrasonic velocity and porosity fraction. Then, from a compilation of data produced by many researchers, scatter plots of velocity versus percent porosity data are shown for Al2O3, MgO, porcelain-based ceramics, PZT, SiC, Si3N4, steel, tungsten, UO2,(U0.30Pu0.70)C, and YBa2Cu3O(7-x). Linear regression analysis produces predicted slope, intercept, correlation coefficient, level of significance, and confidence interval statistics for the data. Velocity values predicted from regression analysis of fully-dense materials are in good agreement with those calculated from elastic properties.

A note about high blood pressure in childhood

NASA Astrophysics Data System (ADS)

Teodoro, M. Filomena; Simão, Carla

2017-06-01

In medical, behavioral and social sciences it is usual to get a binary outcome. In the present work is collected information where some of the outcomes are binary variables (1='yes'/ 0='no'). In [14] a preliminary study about the caregivers perception of pediatric hypertension was introduced. An experimental questionnaire was designed to be answered by the caregivers of routine pediatric consultation attendees in the Santa Maria's hospital (HSM). The collected data was statistically analyzed, where a descriptive analysis and a predictive model were performed. Significant relations between some socio-demographic variables and the assessed knowledge were obtained. In [14] can be found a statistical data analysis using partial questionnaire's information. The present article completes the statistical approach estimating a model for relevant remaining questions of questionnaire by Generalized Linear Models (GLM). Exploring the binary outcome issue, we intend to extend this approach using Generalized Linear Mixed Models (GLMM), but the process is still ongoing.

Review and statistical analysis of the ultrasonic velocity method for estimating the porosity fraction in polycrystalline materials

NASA Technical Reports Server (NTRS)

Roth, D. J.; Swickard, S. M.; Stang, D. B.; Deguire, M. R.

1990-01-01

A review and statistical analysis of the ultrasonic velocity method for estimating the porosity fraction in polycrystalline materials is presented. Initially, a semi-empirical model is developed showing the origin of the linear relationship between ultrasonic velocity and porosity fraction. Then, from a compilation of data produced by many researchers, scatter plots of velocity versus percent porosity data are shown for Al2O3, MgO, porcelain-based ceramics, PZT, SiC, Si3N4, steel, tungsten, UO2,(U0.30Pu0.70)C, and YBa2Cu3O(7-x). Linear regression analysis produced predicted slope, intercept, correlation coefficient, level of significance, and confidence interval statistics for the data. Velocity values predicted from regression analysis for fully-dense materials are in good agreement with those calculated from elastic properties.

A study of the effects of an experimental spiral physics curriculum taught to sixth grade girls and boys

NASA Astrophysics Data System (ADS)

Davis, Edith G.

The pilot study compared the effectiveness of using an experimental spiral physics curriculum to a traditional linear physics curriculum for sixth through eighth grades. The study also surveyed students' parents and principals about students' academic history and background as well as identified resilient children's attributes for academic success. The pilot study was used to help validate the testing instrument as well as help refine the complete study. The purpose of the complete study was to compare the effectiveness of using an experimental spiral physics curriculum and a traditional linear curriculum with sixth graders only; seventh and eighth graders were dropped in the complete study. The study also surveyed students' parents, teachers, and principals about students' academic history and background as well as identified resilient children's attributes for academic success. Both the experimental spiral physics curriculum and the traditional linear physics curriculum increased physics achievement; however, there was no statistically significant difference in effectiveness of teaching experimental spiral physics curriculum in the aggregated sixth grade group compared to the traditional linear physics curriculum. It is important to note that the majority of the subgroups studied did show statistically significant differences in effectiveness for the experimental spiral physics curriculum compared to the traditional linear physics curriculum. The Grounded Theory analysis of resilient student characteristics resulted in categories for future studies including the empathy factor ("E" factor), the tenacity factor ("T" factor), the relational factor ("R" factor), and the spiritual factor ("S" factor).

Evaluation of Two Statistical Methods Provides Insights into the Complex Patterns of Alternative Polyadenylation Site Switching

PubMed Central

Li, Jie; Li, Rui; You, Leiming; Xu, Anlong; Fu, Yonggui; Huang, Shengfeng

2015-01-01

Switching between different alternative polyadenylation (APA) sites plays an important role in the fine tuning of gene expression. New technologies for the execution of 3’-end enriched RNA-seq allow genome-wide detection of the genes that exhibit significant APA site switching between different samples. Here, we show that the independence test gives better results than the linear trend test in detecting APA site-switching events. Further examination suggests that the discrepancy between these two statistical methods arises from complex APA site-switching events that cannot be represented by a simple change of average 3’-UTR length. In theory, the linear trend test is only effective in detecting these simple changes. We classify the switching events into four switching patterns: two simple patterns (3’-UTR shortening and lengthening) and two complex patterns. By comparing the results of the two statistical methods, we show that complex patterns account for 1/4 of all observed switching events that happen between normal and cancerous human breast cell lines. Because simple and complex switching patterns may convey different biological meanings, they merit separate study. We therefore propose to combine both the independence test and the linear trend test in practice. First, the independence test should be used to detect APA site switching; second, the linear trend test should be invoked to identify simple switching events; and third, those complex switching events that pass independence testing but fail linear trend testing can be identified. PMID:25875641

Evaluating the statistical performance of less applied algorithms in classification of worldview-3 imagery data in an urbanized landscape

NASA Astrophysics Data System (ADS)

Ranaie, Mehrdad; Soffianian, Alireza; Pourmanafi, Saeid; Mirghaffari, Noorollah; Tarkesh, Mostafa

2018-03-01

In recent decade, analyzing the remotely sensed imagery is considered as one of the most common and widely used procedures in the environmental studies. In this case, supervised image classification techniques play a central role. Hence, taking a high resolution Worldview-3 over a mixed urbanized landscape in Iran, three less applied image classification methods including Bagged CART, Stochastic gradient boosting model and Neural network with feature extraction were tested and compared with two prevalent methods: random forest and support vector machine with linear kernel. To do so, each method was run ten time and three validation techniques was used to estimate the accuracy statistics consist of cross validation, independent validation and validation with total of train data. Moreover, using ANOVA and Tukey test, statistical difference significance between the classification methods was significantly surveyed. In general, the results showed that random forest with marginal difference compared to Bagged CART and stochastic gradient boosting model is the best performing method whilst based on independent validation there was no significant difference between the performances of classification methods. It should be finally noted that neural network with feature extraction and linear support vector machine had better processing speed than other.

On Fitting Generalized Linear Mixed-effects Models for Binary Responses using Different Statistical Packages

PubMed Central

Zhang, Hui; Lu, Naiji; Feng, Changyong; Thurston, Sally W.; Xia, Yinglin; Tu, Xin M.

2011-01-01

Summary The generalized linear mixed-effects model (GLMM) is a popular paradigm to extend models for cross-sectional data to a longitudinal setting. When applied to modeling binary responses, different software packages and even different procedures within a package may give quite different results. In this report, we describe the statistical approaches that underlie these different procedures and discuss their strengths and weaknesses when applied to fit correlated binary responses. We then illustrate these considerations by applying these procedures implemented in some popular software packages to simulated and real study data. Our simulation results indicate a lack of reliability for most of the procedures considered, which carries significant implications for applying such popular software packages in practice. PMID:21671252

[Relationship between finger dermatoglyphics and body size indicators in adulthood among Chinese twin population from Qingdao and Lishui cities].

PubMed

Sun, Luanluan; Yu, Canqing; Lyu, Jun; Cao, Weihua; Pang, Zengchang; Chen, Weijian; Wang, Shaojie; Chen, Rongfu; Gao, Wenjing; Li, Liming

2014-01-01

To study the correlation between fingerprints and body size indicators in adulthood. Samples were composed of twins from two sub-registries of Chinese National Twin Registry (CNTR), including 405 twin pairs in Lishui and 427 twin pairs in Qingdao. All participants were asked to complete the field survey, consisting of questionnaire, physical examination and blood collection. From the 832 twin pairs, those with complete and clear demographic prints were selected as the target population. Information of Fingerprints pixel on the demographic characteristics of these 100 twin pairs and their related adulthood body type indicators were finally chosen to form this research. Descriptive statistics and mixed linear model were used for data analyses. In the mixed linear models adjusted for age and sex, data showed that the body fat percentage of those who had arches was higher than those who did not have the arches (P = 0.002), and those who had radial loops would have higher body fat percentage when compared with ones who did not (P = 0.041). After adjusted for age, there appeared no statistically significant correlation between radial loops and systolic pressure, but the correlations of arches (P = 0.031)and radial loops (P = 0.022) to diastolic pressure still remained statistically significant. Statistically significant correlations were found between fingerprint types and body size indicators, and the fingerprint types showed a useful tool to explore the effects of uterine environment on health status in one's adulthood.

Characterizations of linear sufficient statistics

NASA Technical Reports Server (NTRS)

Peters, B. C., Jr.; Reoner, R.; Decell, H. P., Jr.

1977-01-01

A surjective bounded linear operator T from a Banach space X to a Banach space Y must be a sufficient statistic for a dominated family of probability measures defined on the Borel sets of X. These results were applied, so that they characterize linear sufficient statistics for families of the exponential type, including as special cases the Wishart and multivariate normal distributions. The latter result was used to establish precisely which procedures for sampling from a normal population had the property that the sample mean was a sufficient statistic.

Gene Level Meta-Analysis of Quantitative Traits by Functional Linear Models.

PubMed

Fan, Ruzong; Wang, Yifan; Boehnke, Michael; Chen, Wei; Li, Yun; Ren, Haobo; Lobach, Iryna; Xiong, Momiao

2015-08-01

Meta-analysis of genetic data must account for differences among studies including study designs, markers genotyped, and covariates. The effects of genetic variants may differ from population to population, i.e., heterogeneity. Thus, meta-analysis of combining data of multiple studies is difficult. Novel statistical methods for meta-analysis are needed. In this article, functional linear models are developed for meta-analyses that connect genetic data to quantitative traits, adjusting for covariates. The models can be used to analyze rare variants, common variants, or a combination of the two. Both likelihood-ratio test (LRT) and F-distributed statistics are introduced to test association between quantitative traits and multiple variants in one genetic region. Extensive simulations are performed to evaluate empirical type I error rates and power performance of the proposed tests. The proposed LRT and F-distributed statistics control the type I error very well and have higher power than the existing methods of the meta-analysis sequence kernel association test (MetaSKAT). We analyze four blood lipid levels in data from a meta-analysis of eight European studies. The proposed methods detect more significant associations than MetaSKAT and the P-values of the proposed LRT and F-distributed statistics are usually much smaller than those of MetaSKAT. The functional linear models and related test statistics can be useful in whole-genome and whole-exome association studies. Copyright © 2015 by the Genetics Society of America.

SOCR Analyses – an Instructional Java Web-based Statistical Analysis Toolkit

PubMed Central

Chu, Annie; Cui, Jenny; Dinov, Ivo D.

2011-01-01

The Statistical Online Computational Resource (SOCR) designs web-based tools for educational use in a variety of undergraduate courses (Dinov 2006). Several studies have demonstrated that these resources significantly improve students' motivation and learning experiences (Dinov et al. 2008). SOCR Analyses is a new component that concentrates on data modeling and analysis using parametric and non-parametric techniques supported with graphical model diagnostics. Currently implemented analyses include commonly used models in undergraduate statistics courses like linear models (Simple Linear Regression, Multiple Linear Regression, One-Way and Two-Way ANOVA). In addition, we implemented tests for sample comparisons, such as t-test in the parametric category; and Wilcoxon rank sum test, Kruskal-Wallis test, Friedman's test, in the non-parametric category. SOCR Analyses also include several hypothesis test models, such as Contingency tables, Friedman's test and Fisher's exact test. The code itself is open source (http://socr.googlecode.com/), hoping to contribute to the efforts of the statistical computing community. The code includes functionality for each specific analysis model and it has general utilities that can be applied in various statistical computing tasks. For example, concrete methods with API (Application Programming Interface) have been implemented in statistical summary, least square solutions of general linear models, rank calculations, etc. HTML interfaces, tutorials, source code, activities, and data are freely available via the web (www.SOCR.ucla.edu). Code examples for developers and demos for educators are provided on the SOCR Wiki website. In this article, the pedagogical utilization of the SOCR Analyses is discussed, as well as the underlying design framework. As the SOCR project is on-going and more functions and tools are being added to it, these resources are constantly improved. The reader is strongly encouraged to check the SOCR site for most updated information and newly added models. PMID:21546994

Statistical analysis of effective singular values in matrix rank determination

NASA Technical Reports Server (NTRS)

Konstantinides, Konstantinos; Yao, Kung

1988-01-01

A major problem in using SVD (singular-value decomposition) as a tool in determining the effective rank of a perturbed matrix is that of distinguishing between significantly small and significantly large singular values to the end, conference regions are derived for the perturbed singular values of matrices with noisy observation data. The analysis is based on the theories of perturbations of singular values and statistical significance test. Threshold bounds for perturbation due to finite-precision and i.i.d. random models are evaluated. In random models, the threshold bounds depend on the dimension of the matrix, the noisy variance, and predefined statistical level of significance. Results applied to the problem of determining the effective order of a linear autoregressive system from the approximate rank of a sample autocorrelation matrix are considered. Various numerical examples illustrating the usefulness of these bounds and comparisons to other previously known approaches are given.

Tooth-size discrepancy: A comparison between manual and digital methods

PubMed Central

Correia, Gabriele Dória Cabral; Habib, Fernando Antonio Lima; Vogel, Carlos Jorge

2014-01-01

Introduction Technological advances in Dentistry have emerged primarily in the area of diagnostic tools. One example is the 3D scanner, which can transform plaster models into three-dimensional digital models. Objective This study aimed to assess the reliability of tooth size-arch length discrepancy analysis measurements performed on three-dimensional digital models, and compare these measurements with those obtained from plaster models. Material and Methods To this end, plaster models of lower dental arches and their corresponding three-dimensional digital models acquired with a 3Shape R700T scanner were used. All of them had lower permanent dentition. Four different tooth size-arch length discrepancy calculations were performed on each model, two of which by manual methods using calipers and brass wire, and two by digital methods using linear measurements and parabolas. Results Data were statistically assessed using Friedman test and no statistically significant differences were found between the two methods (P > 0.05), except for values found by the linear digital method which revealed a slight, non-significant statistical difference. Conclusions Based on the results, it is reasonable to assert that any of these resources used by orthodontists to clinically assess tooth size-arch length discrepancy can be considered reliable. PMID:25279529

Gender disparities in prosthodontics: authorship and leadership, 13 years of observation.

PubMed

Kongkiatkamon, Suchada; Yuan, Judy Chia-Chun; Lee, Damian J; Knoernschild, Kent L; Campbell, Stephen D; Sukotjo, Cortino

2010-10-01

The purpose of this study was to examine gender disparities in prosthodontics by reviewing the trend of female authorship in prosthodontic journals and exploring the role of female leadership in prosthodontic organizations and Advanced Education in Prosthodontic (AEP) programs. Three journals representing the prosthodontic specialty were selected to analyze the percentage of female dentist first and last (senior) authors for the years 1995, 2000, 2005, and 2008. Article inclusion criteria were restricted to the first or last authors who held at least a DMD/DDS/BDS degree and were from U.S. institutions. Data on female leadership in prosthodontic organizations and advanced education programs were collected, and the trends were studied. Descriptive statistics were used to analyze the data. A linear regression analysis was performed to investigate the proportion of female authorship compared to male in the dental literature. A Fisher's Exact Test was performed to contrast differences of female first and last authorship in the selected journals between years 1995 and 2008. Overall, there was no statistically significant linear increase in the proportion of either first or last female authorship compared to male authorship over time. With respect to each journal, the linear regression analysis showed that the increase of first female authorship was statistically significant (p= 0.016) compared to male authorship only in the Journal of Prosthetic Dentistry. The percentage of female presidents of prosthodontic organizations has been very limited. A similar trend was also observed in AEP program director positions. Over the past 13 years, female dentists' participation in prosthodontics literature authorship has not increased significantly in the United States. Furthermore, female involvement in prosthodontics leadership has been limited over the past decades. © 2010 by The American College of Prosthodontists.

[Comparison of application of Cochran-Armitage trend test and linear regression analysis for rate trend analysis in epidemiology study].

PubMed

Wang, D Z; Wang, C; Shen, C F; Zhang, Y; Zhang, H; Song, G D; Xue, X D; Xu, Z L; Zhang, S; Jiang, G H

2017-05-10

We described the time trend of acute myocardial infarction (AMI) from 1999 to 2013 in Tianjin incidence rate with Cochran-Armitage trend (CAT) test and linear regression analysis, and the results were compared. Based on actual population, CAT test had much stronger statistical power than linear regression analysis for both overall incidence trend and age specific incidence trend (Cochran-Armitage trend P value

Introduction to statistical modelling 2: categorical variables and interactions in linear regression.

PubMed

Lunt, Mark

2015-07-01

In the first article in this series we explored the use of linear regression to predict an outcome variable from a number of predictive factors. It assumed that the predictive factors were measured on an interval scale. However, this article shows how categorical variables can also be included in a linear regression model, enabling predictions to be made separately for different groups and allowing for testing the hypothesis that the outcome differs between groups. The use of interaction terms to measure whether the effect of a particular predictor variable differs between groups is also explained. An alternative approach to testing the difference between groups of the effect of a given predictor, which consists of measuring the effect in each group separately and seeing whether the statistical significance differs between the groups, is shown to be misleading. © The Author 2013. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

In-vivo nonlinear optical microscopy (NLOM) of epithelial-connective tissue interface (ECTI) reveals quantitative measures of neoplasia in hamster oral mucosa.

PubMed

Pal, Rahul; Yang, Jinping; Ortiz, Daniel; Qiu, Suimin; Resto, Vicente; McCammon, Susan; Vargas, Gracie

2015-01-01

The epithelial-connective tissue interface (ECTI) plays an integral role in epithelial neoplasia, including oral squamous cell carcinoma (OSCC). This interface undergoes significant alterations due to hyperproliferating epithelium that supports the transformation of normal epithelium to precancers and cancer. We present a method based on nonlinear optical microscopy to directly assess the ECTI and quantify dysplastic alterations using a hamster model for oral carcinogenesis. Neoplastic and non-neoplastic normal mucosa were imaged in-vivo by both multiphoton autofluorescence microscopy (MPAM) and second harmonic generation microscopy (SHGM) to obtain cross-sectional reconstructions of the oral epithelium and lamina propria. Imaged sites were biopsied and processed for histopathological grading and measurement of ECTI parameters. An ECTI shape parameter was calculated based on deviation from the linear geometry (ΔLinearity) seen in normal mucosa was measured using MPAM-SHGM and histology. The ECTI was readily visible in MPAM-SHGM and quantitative shape analysis showed ECTI deformation in dysplasia but not in normal mucosa. ΔLinearity was significantly (p < 0.01) higher in dysplasia (0.41±0.24) than normal (0.11±0.04) as measured in MPAM-SHGM and results were confirmed in histology which showed similar trends in ΔLinearity. Increase in ΔLinearity was also statistically significant for different grades of dysplasia. In-vivo ΔLinearity measurement alone from microscopy discriminated dysplasia from normal tissue with 87.9% sensitivity and 97.6% specificity, while calculations from histology provided 96.4% sensitivity and 85.7% specificity. Among other quantifiable architectural changes, a progressive statistically significant increase in epithelial thickness was seen with increasing grade of dysplasia. MPAM-SHGM provides new noninvasive ways for direct characterization of ECTI which may be used in preclinical studies to investigate the role of this interface in early transformation. Further development of the method may also lead to new diagnostic approaches to differentiate non-neoplastic tissue from precancers and neoplasia, possibly with other cellular and layer based indicators of abnormality.

Technical characteristics can make the difference in a surgical linear stapler. Or not?

PubMed

Giaccaglia, Valentina; Antonelli, Maria Serena; Addario Chieco, Paola; Cocorullo, Gianfranco; Cavallini, Marco; Gulotta, Gaspare

2015-07-01

Anastomotic leak (AL) after gastrointestinal surgery is a severe complication associated with relevant short- and long-term sequelae. Most of the anastomosis are currently performed with a surgical stapler that is required to have appropriate characteristics to guarantee good performances. The aim of our study was to evaluate, in the laboratory, pressure resistance and tensile strength of anastomosis performed with different surgical linear staplers, available in the market. We have been studying three linear staplers, with diverse cartridges and staple heights, of three different companies, used for gastrointestinal anastomosis and gastric or intestinal closure. We performed 50 anastomosis for each device, with the pertinent different cartridges, on fresh pig intestine, for a total of 350 anastomosis, then injected saline solution and recorded the pressure that provokes a leak on the staple line. There were no statistically significant differences between the mean pressure necessary to induce an AL in the various instruments (P > 0.05). For studying the tensile strength, we performed a total of 350 anastomosis with the different linear staplers on a special strong paper (Tyvek), then recorded the maximal tensile force that could open the anastomosis. There were no statistically significant differences between the different staplers about the strength necessary to open the staple line (P > 0.05). we demonstrated that different linear staplers of three companies available in the market give comparable anastomotic pressure resistance and tensile strength. This might suggest that small dissimilarities between different devices are not involved, at least as major parameters, in AL etiology. Copyright © 2015 Elsevier Inc. All rights reserved.

How Universal Is the Relationship Between Remotely Sensed Vegetation Indices (VI) and Crop Leaf Area Index (LAI)?

NASA Technical Reports Server (NTRS)

Kang, Yanghui; Ozdogan, Mutlu; Zipper, Samuel C.; Roman, Miguel

2016-01-01

Global LAI-VI relationships are statistically significant, crop-specific, and mostly non-linear. This research enables the operationalization of large-area crop modeling and, by extension, has relevance to both fundamental and applied agroecosystem research.

Leaf reflectance-nitrogen-chlorophyll relations among three south Texas woody rangeland plant species

NASA Technical Reports Server (NTRS)

Gausman, H. W.; Everitt, J. H.; Escobar, D. E. (Principal Investigator)

1982-01-01

Annual variations in the nitrogen-chlorophyll leaf reflectance of hackberry, honey mesquite and live oak in south Texas, were compared. In spring, leaf reflectance at the 0.55 m wavelength and nitrogen (N) concentration was high but leaf chlorophyll (chl) concentrations were low. In summer, leaf reflectance and N-concentration were low but lead chl concentrations were high. Linear correlations for both spring and summer of leaf reflectance with N and chl concentration or deviations from linear regression were not statistically significant.

A solar cycle dependence of nonlinearity in magnetospheric activity

NASA Astrophysics Data System (ADS)

Johnson, Jay R.; Wing, Simon

2005-04-01

The nonlinear dependencies inherent to the historical Kp data stream (1932-2003) are examined using mutual information and cumulant-based cost as discriminating statistics. The discriminating statistics are compared with surrogate data streams that are constructed using the corrected amplitude adjustment Fourier transform (CAAFT) method and capture the linear properties of the original Kp data. Differences are regularly seen in the discriminating statistics a few years prior to solar minima, while no differences are apparent at the time of solar maxima. These results suggest that the dynamics of the magnetosphere tend to be more linear at solar maximum than at solar minimum. The strong nonlinear dependencies tend to peak on a timescale around 40-50 hours and are statistically significant up to 1 week. Because the solar wind driver variables, VBs, and dynamical pressure exhibit a much shorter decorrelation time for nonlinearities, the results seem to indicate that the nonlinearity is related to internal magnetospheric dynamics. Moreover, the timescales for the nonlinearity seem to be on the same order as that for storm/ring current relaxation. We suggest that the strong solar wind driving that occurs around solar maximum dominates the magnetospheric dynamics, suppressing the internal magnetospheric nonlinearity. On the other hand, in the descending phase of the solar cycle just prior to solar minimum, when magnetospheric activity is weaker, the dynamics exhibit a significant nonlinear internal magnetospheric response that may be related to increased solar wind speed.

Do clinical and translational science graduate students understand linear regression? Development and early validation of the REGRESS quiz.

PubMed

Enders, Felicity

2013-12-01

Although regression is widely used for reading and publishing in the medical literature, no instruments were previously available to assess students' understanding. The goal of this study was to design and assess such an instrument for graduate students in Clinical and Translational Science and Public Health. A 27-item REsearch on Global Regression Expectations in StatisticS (REGRESS) quiz was developed through an iterative process. Consenting students taking a course on linear regression in a Clinical and Translational Science program completed the quiz pre- and postcourse. Student results were compared to practicing statisticians with a master's or doctoral degree in statistics or a closely related field. Fifty-two students responded precourse, 59 postcourse , and 22 practicing statisticians completed the quiz. The mean (SD) score was 9.3 (4.3) for students precourse and 19.0 (3.5) postcourse (P < 0.001). Postcourse students had similar results to practicing statisticians (mean (SD) of 20.1(3.5); P = 0.21). Students also showed significant improvement pre/postcourse in each of six domain areas (P < 0.001). The REGRESS quiz was internally reliable (Cronbach's alpha 0.89). The initial validation is quite promising with statistically significant and meaningful differences across time and study populations. Further work is needed to validate the quiz across multiple institutions. © 2013 Wiley Periodicals, Inc.

Dose and dose rate extrapolation factors for malignant and non-malignant health endpoints after exposure to gamma and neutron radiation.

PubMed

Tran, Van; Little, Mark P

2017-11-01

Murine experiments were conducted at the JANUS reactor in Argonne National Laboratory from 1970 to 1992 to study the effect of acute and protracted radiation dose from gamma rays and fission neutron whole body exposure. The present study reports the reanalysis of the JANUS data on 36,718 mice, of which 16,973 mice were irradiated with neutrons, 13,638 were irradiated with gamma rays, and 6107 were controls. Mice were mostly Mus musculus, but one experiment used Peromyscus leucopus. For both types of radiation exposure, a Cox proportional hazards model was used, using age as timescale, and stratifying on sex and experiment. The optimal model was one with linear and quadratic terms in cumulative lagged dose, with adjustments to both linear and quadratic dose terms for low-dose rate irradiation (<5 mGy/h) and with adjustments to the dose for age at exposure and sex. After gamma ray exposure there is significant non-linearity (generally with upward curvature) for all tumours, lymphoreticular, respiratory, connective tissue and gastrointestinal tumours, also for all non-tumour, other non-tumour, non-malignant pulmonary and non-malignant renal diseases (p < 0.001). Associated with this the low-dose extrapolation factor, measuring the overestimation in low-dose risk resulting from linear extrapolation is significantly elevated for lymphoreticular tumours 1.16 (95% CI 1.06, 1.31), elevated also for a number of non-malignant endpoints, specifically all non-tumour diseases, 1.63 (95% CI 1.43, 2.00), non-malignant pulmonary disease, 1.70 (95% CI 1.17, 2.76) and other non-tumour diseases, 1.47 (95% CI 1.29, 1.82). However, for a rather larger group of malignant endpoints the low-dose extrapolation factor is significantly less than 1 (implying downward curvature), with central estimates generally ranging from 0.2 to 0.8, in particular for tumours of the respiratory system, vasculature, ovary, kidney/urinary bladder and testis. For neutron exposure most endpoints, malignant and non-malignant, show downward curvature in the dose response, and for most endpoints this is statistically significant (p < 0.05). Associated with this, the low-dose extrapolation factor associated with neutron exposure is generally statistically significantly less than 1 for most malignant and non-malignant endpoints, with central estimates mostly in the range 0.1-0.9. In contrast to the situation at higher dose rates, there are statistically non-significant decreases of risk per unit dose at gamma dose rates of less than or equal to 5 mGy/h for most malignant endpoints, and generally non-significant increases in risk per unit dose at gamma dose rates ≤5 mGy/h for most non-malignant endpoints. Associated with this, the dose-rate extrapolation factor, the ratio of high dose-rate to low dose-rate (≤5 mGy/h) gamma dose response slopes, for many tumour sites is in the range 1.2-2.3, albeit not statistically significantly elevated from 1, while for most non-malignant endpoints the gamma dose-rate extrapolation factor is less than 1, with most estimates in the range 0.2-0.8. After neutron exposure there are non-significant indications of lower risk per unit dose at dose rates ≤5 mGy/h compared to higher dose rates for most malignant endpoints, and for all tumours (p = 0.001), and respiratory tumours (p = 0.007) this reduction is conventionally statistically significant; for most non-malignant outcomes risks per unit dose non-significantly increase at lower dose rates. Associated with this, the neutron dose-rate extrapolation factor is less than 1 for most malignant and non-malignant endpoints, in many cases statistically significantly so, with central estimates mostly in the range 0.0-0.2.

On fitting generalized linear mixed-effects models for binary responses using different statistical packages.

PubMed

Zhang, Hui; Lu, Naiji; Feng, Changyong; Thurston, Sally W; Xia, Yinglin; Zhu, Liang; Tu, Xin M

2011-09-10

The generalized linear mixed-effects model (GLMM) is a popular paradigm to extend models for cross-sectional data to a longitudinal setting. When applied to modeling binary responses, different software packages and even different procedures within a package may give quite different results. In this report, we describe the statistical approaches that underlie these different procedures and discuss their strengths and weaknesses when applied to fit correlated binary responses. We then illustrate these considerations by applying these procedures implemented in some popular software packages to simulated and real study data. Our simulation results indicate a lack of reliability for most of the procedures considered, which carries significant implications for applying such popular software packages in practice. Copyright © 2011 John Wiley & Sons, Ltd.

Subconcussive Head Impact Exposure and White Matter Tract Changes over a Single Season of Youth Football

PubMed Central

Bahrami, Naeim; Sharma, Dev; Rosenthal, Scott; Davenport, Elizabeth M.; Urban, Jillian E.; Wagner, Benjamin; Jung, Youngkyoo; Vaughan, Christopher G.; Gioia, Gerard A.; Stitzel, Joel D.; Maldjian, Joseph A.

2016-01-01

Purpose To examine the effects of subconcussive impacts resulting from a single season of youth (age range, 8–13 years) football on changes in specific white matter (WM) tracts as detected with diffusion-tensor imaging in the absence of clinically diagnosed concussions. Materials and Methods Head impact data were recorded by using the Head Impact Telemetry system and quantified as the combined-probability risk-weighted cumulative exposure (RWECP). Twenty-five male participants were evaluated for seasonal fractional anisotropy (FA) changes in specific WM tracts: the inferior fronto-occipital fasciculus (IFOF), inferior longitudinal fasciculus, and superior longitudinal fasciculus (SLF). Fiber tracts were segmented into a central core and two fiber terminals. The relationship between seasonal FA change in the whole fiber, central core, and the fiber terminals with RWECP was also investigated. Linear regression analysis was conducted to determine the association between RWECP and change in fiber tract FA during the season. Results There were statistically significant linear relationships between RWEcp and decreased FA in the whole (R2 = 0.433; P = .003), core (R2 = 0.3649; P = .007), and terminals (R2 = 0.5666; P < .001) of left IFOF. A trend toward statistical significance (P = .08) in right SLF was observed. A statistically significant correlation between decrease in FA of the right SLF terminal and RWECP was also observed (R2 = 0.2893; P = .028). Conclusion This study found a statistically significant relationship between head impact exposure and change of FAfractional anisotropy value of whole, core, and terminals of left IFOF and right SLF’s terminals where WM and gray matter intersect, in the absence of a clinically diagnosed concussion. © RSNA, 2016 PMID:27775478

Subconcussive Head Impact Exposure and White Matter Tract Changes over a Single Season of Youth Football.

PubMed

Bahrami, Naeim; Sharma, Dev; Rosenthal, Scott; Davenport, Elizabeth M; Urban, Jillian E; Wagner, Benjamin; Jung, Youngkyoo; Vaughan, Christopher G; Gioia, Gerard A; Stitzel, Joel D; Whitlow, Christopher T; Maldjian, Joseph A

2016-12-01

Purpose To examine the effects of subconcussive impacts resulting from a single season of youth (age range, 8-13 years) football on changes in specific white matter (WM) tracts as detected with diffusion-tensor imaging in the absence of clinically diagnosed concussions. Materials and Methods Head impact data were recorded by using the Head Impact Telemetry system and quantified as the combined-probability risk-weighted cumulative exposure (RWE CP ). Twenty-five male participants were evaluated for seasonal fractional anisotropy (FA) changes in specific WM tracts: the inferior fronto-occipital fasciculus (IFOF), inferior longitudinal fasciculus, and superior longitudinal fasciculus (SLF). Fiber tracts were segmented into a central core and two fiber terminals. The relationship between seasonal FA change in the whole fiber, central core, and the fiber terminals with RWE CP was also investigated. Linear regression analysis was conducted to determine the association between RWE CP and change in fiber tract FA during the season. Results There were statistically significant linear relationships between RWE cp and decreased FA in the whole (R 2 = 0.433; P = .003), core (R 2 = 0.3649; P = .007), and terminals (R 2 = 0.5666; P < .001) of left IFOF. A trend toward statistical significance (P = .08) in right SLF was observed. A statistically significant correlation between decrease in FA of the right SLF terminal and RWE CP was also observed (R 2 = 0.2893; P = .028). Conclusion This study found a statistically significant relationship between head impact exposure and change of FA fractional anisotropy value of whole, core, and terminals of left IFOF and right SLF's terminals where WM and gray matter intersect, in the absence of a clinically diagnosed concussion. © RSNA, 2016.

Comparison of Neural Network and Linear Regression Models in Statistically Predicting Mental and Physical Health Status of Breast Cancer Survivors

DTIC Science & Technology

2015-07-15

Long-term effects on cancer survivors’ quality of life of physical training versus physical training combined with cognitive-behavioral therapy ...COMPARISON OF NEURAL NETWORK AND LINEAR REGRESSION MODELS IN STATISTICALLY PREDICTING MENTAL AND PHYSICAL HEALTH STATUS OF BREAST...34Comparison of Neural Network and Linear Regression Models in Statistically Predicting Mental and Physical Health Status of Breast Cancer Survivors

Note: Nonpolar solute partial molar volume response to attractive interactions with water.

PubMed

Williams, Steven M; Ashbaugh, Henry S

2014-01-07

The impact of attractive interactions on the partial molar volumes of methane-like solutes in water is characterized using molecular simulations. Attractions account for a significant 20% volume drop between a repulsive Weeks-Chandler-Andersen and full Lennard-Jones description of methane interactions. The response of the volume to interaction perturbations is characterized by linear fits to our simulations and a rigorous statistical thermodynamic expression for the derivative of the volume to increasing attractions. While a weak non-linear response is observed, an average effective slope accurately captures the volume decrease. This response, however, is anticipated to become more non-linear with increasing solute size.

Note: Nonpolar solute partial molar volume response to attractive interactions with water

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

Williams, Steven M.; Ashbaugh, Henry S., E-mail: hanka@tulane.edu

2014-01-07

The impact of attractive interactions on the partial molar volumes of methane-like solutes in water is characterized using molecular simulations. Attractions account for a significant 20% volume drop between a repulsive Weeks-Chandler-Andersen and full Lennard-Jones description of methane interactions. The response of the volume to interaction perturbations is characterized by linear fits to our simulations and a rigorous statistical thermodynamic expression for the derivative of the volume to increasing attractions. While a weak non-linear response is observed, an average effective slope accurately captures the volume decrease. This response, however, is anticipated to become more non-linear with increasing solute size.

[Clinical application of biofragmentable anastomosis ring for intestinal anastomosis].

PubMed

Ye, Feng; Lin, Jian-jiang

2006-11-01

To compare the efficacy of the biofragmentable anastomotic ring (BAR) with conventional hand-sutured and stapling techniques,and to evaluate the safety and applicability of the BAR in intestinal anastomosis. The totol of 498 patients performed intestinal anastomosis from January 2000 to November 2005 were allocated to BAR group (n=186), hand-sutured group (n=177) and linear cutter group (n=135). The operative time, postoperative convalescence and corresponding complication were recorded. Postoperative anastomotic inflammation and anastomotic stenosis were observed during half or one year follow-up of 436 patients. The operative time was (102 +/- 16) min in the BAR group, (121 +/- 15) min in the hand-sutured group, and (105 +/- 18 ) min in the linear cutter group. The difference was significant statistically (P <0.05). The operative time in BAR group and linear cutter group was shorter than hand-sutured group. One case of anastomotic leakage was noted in the BAR group, one case in the hand-sutured group, and none in the linear cutter group. They were cured by conservative methods. One case of anastomotic obstruction happened in the BAR group, one case in the hand-sutured group. Two of them were cured by conservative methods. Two cases of anastomotic obstruction happened in the hand-sutured group. However, one of them required reoperation to remove the obstruction. In the BAR, hand-sutured and the linear cutter group, the postoperative first flatus time was (67.2+/- 4.6) h, (70.2 +/- 5.8) h and (69.2 +/- 6.2)h, respectively. No significant differences were observed among three groups(P > 0.05). The rate of postoperative anastomotic inflammation was 3.0 % (5/164) in the BAR group, 47.8 % (76/159) in hand-sutured group and 7.1 % (8/113) in the linear cutter group. The difference was significant statistically (P <0.05). The rate of postoperative anastomotic inflammation in the BAR group and in the linear cutter group was less than that in hand-sutured group. BAR is one of rapid,safe and effective methods in intestinal anastomosis. It has less anastomotic inflammatory reaction than hand-sutured technique. It should be considered equal to manual and stapler methods.

[Ultrasonic measurements of fetal thalamus, caudate nucleus and lenticular nucleus in prenatal diagnosis].

PubMed

Yang, Ruiqi; Wang, Fei; Zhang, Jialing; Zhu, Chonglei; Fan, Limei

2015-05-19

To establish the reference values of thalamus, caudate nucleus and lenticular nucleus diameters through fetal thalamic transverse section. A total of 265 fetuses at our hospital were randomly selected from November 2012 to August 2014. And the transverse and length diameters of thalamus, caudate nucleus and lenticular nucleus were measured. SPSS 19.0 statistical software was used to calculate the regression curve of fetal diameter changes and gestational weeks of pregnancy. P < 0.05 was considered as having statistical significance. The linear regression equation of fetal thalamic length diameter and gestational week was: Y = 0.051X+0.201, R = 0.876, linear regression equation of thalamic transverse diameter and fetal gestational week was: Y = 0.031X+0.229, R = 0.817, linear regression equation of fetal head of caudate nucleus length diameter and gestational age was: Y = 0.033X+0.101, R = 0.722, linear regression equation of fetal head of caudate nucleus transverse diameter and gestational week was: R = 0.025 - 0.046, R = 0.711, linear regression equation of fetal lentiform nucleus length diameter and gestational week was: Y = 0.046+0.229, R = 0.765, linear regression equation of fetal lentiform nucleus diameter and gestational week was: Y = 0.025 - 0.05, R = 0.772. Ultrasonic measurement of diameter of fetal thalamus caudate nucleus, and lenticular nucleus through thalamic transverse section is simple and convenient. And measurements increase with fetal gestational weeks and there is linear regression relationship between them.

[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.

Inhaled corticosteroids in children with persistent asthma: effects on growth.

PubMed

Zhang, Linjie; Prietsch, Sílvio O M; Ducharme, Francine M

2014-07-17

Treatment guidelines for asthma recommend inhaled corticosteroids (ICS) as first-line therapy for children with persistent asthma. Although ICS treatment is generally considered safe in children, the potential systemic adverse effects related to regular use of these drugs have been and continue to be a matter of concern, especially the effects on linear growth. To assess the impact of ICS on the linear growth of children with persistent asthma and to explore potential effect modifiers such as characteristics of available treatments (molecule, dose, length of exposure, inhalation device) and of treated children (age, disease severity, compliance with treatment). We searched the Cochrane Airways Group Specialised Register of trials (CAGR), which is derived from systematic searches of bibliographic databases including CENTRAL, MEDLINE, EMBASE, CINAHL, AMED and PsycINFO; we handsearched respiratory journals and meeting abstracts. We also conducted a search of ClinicalTrials.gov and manufacturers' clinical trial databases to look for potential relevant unpublished studies. The literature search was conducted in January 2014. Parallel-group randomised controlled trials comparing daily use of ICS, delivered by any type of inhalation device for at least three months, versus placebo or non-steroidal drugs in children up to 18 years of age with persistent asthma. Two review authors independently performed study selection, data extraction and assessment of risk of bias in included studies. We conducted meta-analyses using the Cochrane statistical package RevMan 5.2 and Stata version 11.0. We used the random-effects model for meta-analyses. We used mean differences (MDs) and 95% CIs as the metrics for treatment effects. A negative value for MD indicates that ICS have suppressive effects on linear growth compared with controls. We performed a priori planned subgroup analyses to explore potential effect modifiers, such as ICS molecule, daily dose, inhalation device and age of the treated child. We included 25 trials involving 8471 (5128 ICS-treated and 3343 control) children with mild to moderate persistent asthma. Six molecules (beclomethasone dipropionate, budesonide, ciclesonide, flunisolide, fluticasone propionate and mometasone furoate) [corrected] given at low or medium daily doses were used during a period of three months to four to six years. Most trials were blinded and over half of the trials had drop out rates of over 20%.Compared with placebo or non-steroidal drugs, ICS produced a statistically significant reduction in linear growth velocity (14 trials with 5717 participants, MD -0.48 cm/y, 95% CI -0.65 to -0.30, moderate quality evidence) and in the change from baseline in height (15 trials with 3275 participants; MD -0.61 cm/y, 95% CI -0.83 to -0.38, moderate quality evidence) during a one-year treatment period.Subgroup analysis showed a statistically significant group difference between six molecules in the mean reduction of linear growth velocity during one-year treatment (Chi² = 26.1, degrees of freedom (df) = 5, P value < 0.0001). The group difference persisted even when analysis was restricted to the trials using doses equivalent to 200 μg/d hydrofluoroalkane (HFA)-beclomethasone. Subgroup analyses did not show a statistically significant impact of daily dose (low vs medium), inhalation device or participant age on the magnitude of ICS-induced suppression of linear growth velocity during a one-year treatment period. However, head-to-head comparisons are needed to assess the effects of different drug molecules, dose, inhalation device or patient age. No statistically significant difference in linear growth velocity was found between participants treated with ICS and controls during the second year of treatment (five trials with 3174 participants; MD -0.19 cm/y, 95% CI -0.48 to 0.11, P value 0.22). Of two trials that reported linear growth velocity in the third year of treatment, one trial involving 667 participants showed similar growth velocity between the budesonide and placebo groups (5.34 cm/y vs 5.34 cm/y), and another trial involving 1974 participants showed lower growth velocity in the budesonide group compared with the placebo group (MD -0.33 cm/y, 95% CI -0.52 to -0.14, P value 0.0005). Among four trials reporting data on linear growth after treatment cessation, three did not describe statistically significant catch-up growth in the ICS group two to four months after treatment cessation. One trial showed accelerated linear growth velocity in the fluticasone group at 12 months after treatment cessation, but there remained a statistically significant difference of 0.7 cm in height between the fluticasone and placebo groups at the end of the three-year trial.One trial with follow-up into adulthood showed that participants of prepubertal age treated with budesonide 400 μg/d for a mean duration of 4.3 years had a mean reduction of 1.20 cm (95% CI -1.90 to -0.50) in adult height compared with those treated with placebo. Regular use of ICS at low or medium daily doses is associated with a mean reduction of 0.48 cm/y in linear growth velocity and a 0.61-cm change from baseline in height during a one-year treatment period in children with mild to moderate persistent asthma. The effect size of ICS on linear growth velocity appears to be associated more strongly with the ICS molecule than with the device or dose (low to medium dose range). ICS-induced growth suppression seems to be maximal during the first year of therapy and less pronounced in subsequent years of treatment. However, additional studies are needed to better characterise the molecule dependency of growth suppression, particularly with newer molecules (mometasone, ciclesonide), to specify the respective role of molecule, daily dose, inhalation device and patient age on the effect size of ICS, and to define the growth suppression effect of ICS treatment over a period of several years in children with persistent asthma.

Can upstaging of ductal carcinoma in situ be predicted at biopsy by histologic and mammographic features?

NASA Astrophysics Data System (ADS)

Shi, Bibo; Grimm, Lars J.; Mazurowski, Maciej A.; Marks, Jeffrey R.; King, Lorraine M.; Maley, Carlo C.; Hwang, E. Shelley; Lo, Joseph Y.

2017-03-01

Reducing the overdiagnosis and overtreatment associated with ductal carcinoma in situ (DCIS) requires accurate prediction of the invasive potential at cancer screening. In this work, we investigated the utility of pre-operative histologic and mammographic features to predict upstaging of DCIS. The goal was to provide intentionally conservative baseline performance using readily available data from radiologists and pathologists and only linear models. We conducted a retrospective analysis on 99 patients with DCIS. Of those 25 were upstaged to invasive cancer at the time of definitive surgery. Pre-operative factors including both the histologic features extracted from stereotactic core needle biopsy (SCNB) reports and the mammographic features annotated by an expert breast radiologist were investigated with statistical analysis. Furthermore, we built classification models based on those features in an attempt to predict the presence of an occult invasive component in DCIS, with generalization performance assessed by receiver operating characteristic (ROC) curve analysis. Histologic features including nuclear grade and DCIS subtype did not show statistically significant differences between cases with pure DCIS and with DCIS plus invasive disease. However, three mammographic features, i.e., the major axis length of DCIS lesion, the BI-RADS level of suspicion, and radiologist's assessment did achieve the statistical significance. Using those three statistically significant features as input, a linear discriminant model was able to distinguish patients with DCIS plus invasive disease from those with pure DCIS, with AUC-ROC equal to 0.62. Overall, mammograms used for breast screening contain useful information that can be perceived by radiologists and help predict occult invasive components in DCIS.

Nonlinear Extraction of Independent Components of Natural Images Using Radial Gaussianization

PubMed Central

Lyu, Siwei; Simoncelli, Eero P.

2011-01-01

We consider the problem of efficiently encoding a signal by transforming it to a new representation whose components are statistically independent. A widely studied linear solution, known as independent component analysis (ICA), exists for the case when the signal is generated as a linear transformation of independent nongaussian sources. Here, we examine a complementary case, in which the source is nongaussian and elliptically symmetric. In this case, no invertible linear transform suffices to decompose the signal into independent components, but we show that a simple nonlinear transformation, which we call radial gaussianization (RG), is able to remove all dependencies. We then examine this methodology in the context of natural image statistics. We first show that distributions of spatially proximal bandpass filter responses are better described as elliptical than as linearly transformed independent sources. Consistent with this, we demonstrate that the reduction in dependency achieved by applying RG to either nearby pairs or blocks of bandpass filter responses is significantly greater than that achieved by ICA. Finally, we show that the RG transformation may be closely approximated by divisive normalization, which has been used to model the nonlinear response properties of visual neurons. PMID:19191599

Maxillary distraction osteogenesis in the adolescent cleft patient: three-dimensional computed tomography analysis of linear and volumetric changes over five years.

PubMed

Chen, Philip Kuo-Ting; Por, Yong-Chen; Liou, Eric Jein-Wein; Chang, Frank Chun-Shin

2011-07-01

To assess the results of maxillary distraction osteogenesis with the Rigid External Distraction System using three-dimensional computed tomography scan volume-rendered images with respect to stability and facial growth at three time frames: preoperative (T0), 1-year postoperative (T1), and 5-years postoperative (T2). Retrospective analysis. Tertiary. A total of 12 patients with severe cleft maxillary hypoplasia were treated between June 30, 1997, and July 15, 1998. The mean age at surgery was 11 years 1 month. Le Fort I maxillary distraction osteogenesis. Distraction was started 2 to 5 days postsurgery at a rate of 1 mm per day. The consolidation period was 3 months. No face mask was used. A paired t test was used for statistical analysis. Overjet, ANB, and SNA and maxillary, pterygoid, and mandibular volumes. From T0 to T1, there were statistically significant increments of overjet, ANB, and SNA and maxillary, pterygoid, and mandibular volumes. The T1 to T2 period demonstrated a reduction of overjet (30.07%) and ANB (54.42%). The maxilla showed a stable SNA and a small but statistically significant advancement of the ANS point. There was a significant increase in the mandibular volume. However, there was no significant change in the maxillary and pterygoid volumes. Maxillary distraction osteogenesis demonstrated linear and volumetric maxillary growth during the distraction phase without clinically significant continued growth thereafter. Overcorrection is required to take into account recurrence of midface retrusion over the long term.

Performance of an Axisymmetric Rocket Based Combined Cycle Engine During Rocket Only Operation Using Linear Regression Analysis

NASA Technical Reports Server (NTRS)

Smith, Timothy D.; Steffen, Christopher J., Jr.; Yungster, Shaye; Keller, Dennis J.

1998-01-01

The all rocket mode of operation is shown to be a critical factor in the overall performance of a rocket based combined cycle (RBCC) vehicle. An axisymmetric RBCC engine was used to determine specific impulse efficiency values based upon both full flow and gas generator configurations. Design of experiments methodology was used to construct a test matrix and multiple linear regression analysis was used to build parametric models. The main parameters investigated in this study were: rocket chamber pressure, rocket exit area ratio, injected secondary flow, mixer-ejector inlet area, mixer-ejector area ratio, and mixer-ejector length-to-inlet diameter ratio. A perfect gas computational fluid dynamics analysis, using both the Spalart-Allmaras and k-omega turbulence models, was performed with the NPARC code to obtain values of vacuum specific impulse. Results from the multiple linear regression analysis showed that for both the full flow and gas generator configurations increasing mixer-ejector area ratio and rocket area ratio increase performance, while increasing mixer-ejector inlet area ratio and mixer-ejector length-to-diameter ratio decrease performance. Increasing injected secondary flow increased performance for the gas generator analysis, but was not statistically significant for the full flow analysis. Chamber pressure was found to be not statistically significant.

Effects of measurement errors on psychometric measurements in ergonomics studies: Implications for correlations, ANOVA, linear regression, factor analysis, and linear discriminant analysis.

PubMed

Liu, Yan; Salvendy, Gavriel

2009-05-01

This paper aims to demonstrate the effects of measurement errors on psychometric measurements in ergonomics studies. A variety of sources can cause random measurement errors in ergonomics studies and these errors can distort virtually every statistic computed and lead investigators to erroneous conclusions. The effects of measurement errors on five most widely used statistical analysis tools have been discussed and illustrated: correlation; ANOVA; linear regression; factor analysis; linear discriminant analysis. It has been shown that measurement errors can greatly attenuate correlations between variables, reduce statistical power of ANOVA, distort (overestimate, underestimate or even change the sign of) regression coefficients, underrate the explanation contributions of the most important factors in factor analysis and depreciate the significance of discriminant function and discrimination abilities of individual variables in discrimination analysis. The discussions will be restricted to subjective scales and survey methods and their reliability estimates. Other methods applied in ergonomics research, such as physical and electrophysiological measurements and chemical and biomedical analysis methods, also have issues of measurement errors, but they are beyond the scope of this paper. As there has been increasing interest in the development and testing of theories in ergonomics research, it has become very important for ergonomics researchers to understand the effects of measurement errors on their experiment results, which the authors believe is very critical to research progress in theory development and cumulative knowledge in the ergonomics field.

Does competition improve financial stability of the banking sector in ASEAN countries? An empirical analysis.

PubMed

Noman, Abu Hanifa Md; Gee, Chan Sok; Isa, Che Ruhana

2017-01-01

This study examines the influence of competition on the financial stability of the commercial banks of Association of Southeast Asian Nation (ASEAN) over the 1990 to 2014 period. Panzar-Rosse H-statistic, Lerner index and Herfindahl-Hirschman Index (HHI) are used as measures of competition, while Z-score, non-performing loan (NPL) ratio and equity ratio are used as measures of financial stability. Two-step system Generalized Method of Moments (GMM) estimates demonstrate that competition measured by H-statistic is positively related to Z-score and equity ratio, and negatively related to non-performing loan ratio. Conversely, market power measured by Lerner index is negatively related to Z-score and equity ratio and positively related to NPL ratio. These results strongly support the competition-stability view for ASEAN banks. We also capture the non-linear relationship between competition and financial stability by incorporating a quadratic term of competition in our models. The results show that the coefficient of the quadratic term of H-statistic is negative for the Z-score model given a positive coefficient of the linear term in the same model. These results support the non-linear relationship between competition and financial stability of the banking sector. The study contains significant policy implications for improving the financial stability of the commercial banks.

Does competition improve financial stability of the banking sector in ASEAN countries? An empirical analysis

PubMed Central

Gee, Chan Sok; Isa, Che Ruhana

2017-01-01

This study examines the influence of competition on the financial stability of the commercial banks of Association of Southeast Asian Nation (ASEAN) over the 1990 to 2014 period. Panzar-Rosse H-statistic, Lerner index and Herfindahl-Hirschman Index (HHI) are used as measures of competition, while Z-score, non-performing loan (NPL) ratio and equity ratio are used as measures of financial stability. Two-step system Generalized Method of Moments (GMM) estimates demonstrate that competition measured by H-statistic is positively related to Z-score and equity ratio, and negatively related to non-performing loan ratio. Conversely, market power measured by Lerner index is negatively related to Z-score and equity ratio and positively related to NPL ratio. These results strongly support the competition-stability view for ASEAN banks. We also capture the non-linear relationship between competition and financial stability by incorporating a quadratic term of competition in our models. The results show that the coefficient of the quadratic term of H-statistic is negative for the Z-score model given a positive coefficient of the linear term in the same model. These results support the non-linear relationship between competition and financial stability of the banking sector. The study contains significant policy implications for improving the financial stability of the commercial banks. PMID:28486548

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.

The influence of linear elements on plant species diversity of Mediterranean rural landscapes: assessment of different indices and statistical approaches.

PubMed

García del Barrio, J M; Ortega, M; Vázquez De la Cueva, A; Elena-Rosselló, R

2006-08-01

This paper mainly aims to study the linear element influence on the estimation of vascular plant species diversity in five Mediterranean landscapes modeled as land cover patch mosaics. These landscapes have several core habitats and a different set of linear elements--habitat edges or ecotones, roads or railways, rivers, streams and hedgerows on farm land--whose plant composition were examined. Secondly, it aims to check plant diversity estimation in Mediterranean landscapes using parametric and non-parametric procedures, with two indices: Species richness and Shannon index. Land cover types and landscape linear elements were identified from aerial photographs. Their spatial information was processed using GIS techniques. Field plots were selected using a stratified sampling design according to relieve and tree density of each habitat type. A 50x20 m2 multi-scale sampling plot was designed for the core habitats and across the main landscape linear elements. Richness and diversity of plant species were estimated by comparing the observed field data to ICE (Incidence-based Coverage Estimator) and ACE (Abundance-based Coverage Estimator) non-parametric estimators. The species density, percentage of unique species, and alpha diversity per plot were significantly higher (p < 0.05) in linear elements than in core habitats. ICE estimate of number of species was 32% higher than of ACE estimate, which did not differ significantly from the observed values. Accumulated species richness in core habitats together with linear elements, were significantly higher than those recorded only in the core habitats in all the landscapes. Conversely, Shannon diversity index did not show significant differences.

MIDAS: Regionally linear multivariate discriminative statistical mapping.

PubMed

Varol, Erdem; Sotiras, Aristeidis; Davatzikos, Christos

2018-07-01

Statistical parametric maps formed via voxel-wise mass-univariate tests, such as the general linear model, are commonly used to test hypotheses about regionally specific effects in neuroimaging cross-sectional studies where each subject is represented by a single image. Despite being informative, these techniques remain limited as they ignore multivariate relationships in the data. Most importantly, the commonly employed local Gaussian smoothing, which is important for accounting for registration errors and making the data follow Gaussian distributions, is usually chosen in an ad hoc fashion. Thus, it is often suboptimal for the task of detecting group differences and correlations with non-imaging variables. Information mapping techniques, such as searchlight, which use pattern classifiers to exploit multivariate information and obtain more powerful statistical maps, have become increasingly popular in recent years. However, existing methods may lead to important interpretation errors in practice (i.e., misidentifying a cluster as informative, or failing to detect truly informative voxels), while often being computationally expensive. To address these issues, we introduce a novel efficient multivariate statistical framework for cross-sectional studies, termed MIDAS, seeking highly sensitive and specific voxel-wise brain maps, while leveraging the power of regional discriminant analysis. In MIDAS, locally linear discriminative learning is applied to estimate the pattern that best discriminates between two groups, or predicts a variable of interest. This pattern is equivalent to local filtering by an optimal kernel whose coefficients are the weights of the linear discriminant. By composing information from all neighborhoods that contain a given voxel, MIDAS produces a statistic that collectively reflects the contribution of the voxel to the regional classifiers as well as the discriminative power of the classifiers. Critically, MIDAS efficiently assesses the statistical significance of the derived statistic by analytically approximating its null distribution without the need for computationally expensive permutation tests. The proposed framework was extensively validated using simulated atrophy in structural magnetic resonance imaging (MRI) and further tested using data from a task-based functional MRI study as well as a structural MRI study of cognitive performance. The performance of the proposed framework was evaluated against standard voxel-wise general linear models and other information mapping methods. The experimental results showed that MIDAS achieves relatively higher sensitivity and specificity in detecting group differences. Together, our results demonstrate the potential of the proposed approach to efficiently map effects of interest in both structural and functional data. Copyright © 2018. Published by Elsevier Inc.

Fourier transform infrared reflectance spectra of latent fingerprints: a biometric gauge for the age of an individual.

PubMed

Hemmila, April; McGill, Jim; Ritter, David

2008-03-01

To determine if changes in fingerprint infrared spectra linear with age can be found, partial least squares (PLS1) regression of 155 fingerprint infrared spectra against the person's age was constructed. The regression produced a linear model of age as a function of spectrum with a root mean square error of calibration of less than 4 years, showing an inflection at about 25 years of age. The spectral ranges emphasized by the regression do not correspond to the highest concentration constituents of the fingerprints. Separate linear regression models for old and young people can be constructed with even more statistical rigor. The success of the regression demonstrates that a combination of constituents can be found that changes linearly with age, with a significant shift around puberty.

Three decades (1983-2010) of contaminant trends in East Greenland polar bears (Ursus maritimus). Part 2: brominated flame retardants.

PubMed

Dietz, Rune; Rigét, Frank F; Sonne, Christian; Born, Erik W; Bechshøft, Thea; McKinney, Melissa A; Drimmie, Robert J; Muir, Derek C G; Letcher, Robert J

2013-09-01

Brominated flame retardants were determined in adipose tissues from 294 polar bears (Ursus maritimus) sampled in East Greenland in 23 of the 28years between 1983 and 2010. Significant linear increases were found for sum polybrominated diphenyl ether (ΣPBDE), BDE100, BDE153, and hexabromocyclododecane (HBCD). Average increases of 5.0% per year (range: 2.9-7.6%/year) were found for the subadult polar bears. BDE47 and BDE99 concentrations did not show a significant linear trend over time, but rather a significant non-linear trend peaking between 2000 and 2004. The average ΣPBDE concentrations increased 2.3 fold from 25.0ng/g lw (95% C.I.: 15.3-34.7ng/g lw) in 1983-1986 to 58.5ng/g lw (95% C.I.: 43.6-73.4ng/g lw) in 2006-2010. Similar but fewer statistically significant trends were found for adult females and adult males likely due to smaller sample size and years. Analyses of δ(15)N and δ(13)C stable isotopes in hair revealed no clear linear temporal trends in trophic level or carbon source, respectively, and non-linear trends differed among sex and age groups. These increasing concentrations of organobromine contaminants contribute to complex organohalogen mixture, already causing health effects to the East Greenland polar bears. Copyright © 2012 Elsevier Ltd. All rights reserved.

Detector noise statistics in the non-linear regime

NASA Technical Reports Server (NTRS)

Shopbell, P. L.; Bland-Hawthorn, J.

1992-01-01

The statistical behavior of an idealized linear detector in the presence of threshold and saturation levels is examined. It is assumed that the noise is governed by the statistical fluctuations in the number of photons emitted by the source during an exposure. Since physical detectors cannot have infinite dynamic range, our model illustrates that all devices have non-linear regimes, particularly at high count rates. The primary effect is a decrease in the statistical variance about the mean signal due to a portion of the expected noise distribution being removed via clipping. Higher order statistical moments are also examined, in particular, skewness and kurtosis. In principle, the expected distortion in the detector noise characteristics can be calibrated using flatfield observations with count rates matched to the observations. For this purpose, some basic statistical methods that utilize Fourier analysis techniques are described.

Focal activation of primary visual cortex following supra-choroidal electrical stimulation of the retina: Intrinsic signal imaging and linear model analysis.

PubMed

Cloherty, Shaun L; Hietanen, Markus A; Suaning, Gregg J; Ibbotson, Michael R

2010-01-01

We performed optical intrinsic signal imaging of cat primary visual cortex (Area 17 and 18) while delivering bipolar electrical stimulation to the retina by way of a supra-choroidal electrode array. Using a general linear model (GLM) analysis we identified statistically significant (p < 0.01) activation in a localized region of cortex following supra-threshold electrical stimulation at a single retinal locus. (1) demonstrate that intrinsic signal imaging combined with linear model analysis provides a powerful tool for assessing cortical responses to prosthetic stimulation, and (2) confirm that supra-choroidal electrical stimulation can achieve localized activation of the cortex consistent with focal activation of the retina.

A Solar Cycle Dependence of Nonlinearity in Magnetospheric Activity

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

Johnson, Jay R; Wing, Simon

2005-03-08

The nonlinear dependencies inherent to the historical K(sub)p data stream (1932-2003) are examined using mutual information and cumulant based cost as discriminating statistics. The discriminating statistics are compared with surrogate data streams that are constructed using the corrected amplitude adjustment Fourier transform (CAAFT) method and capture the linear properties of the original K(sub)p data. Differences are regularly seen in the discriminating statistics a few years prior to solar minima, while no differences are apparent at the time of solar maximum. These results suggest that the dynamics of the magnetosphere tend to be more linear at solar maximum than at solarmore » minimum. The strong nonlinear dependencies tend to peak on a timescale around 40-50 hours and are statistically significant up to one week. Because the solar wind driver variables, VB(sub)s and dynamical pressure exhibit a much shorter decorrelation time for nonlinearities, the results seem to indicate that the nonlinearity is related to internal magnetospheric dynamics. Moreover, the timescales for the nonlinearity seem to be on the same order as that for storm/ring current relaxation. We suggest that the strong solar wind driving that occurs around solar maximum dominates the magnetospheric dynamics suppressing the internal magnetospheric nonlinearity. On the other hand, in the descending phase of the solar cycle just prior to solar minimum, when magnetospheric activity is weaker, the dynamics exhibit a significant nonlinear internal magnetospheric response that may be related to increased solar wind speed.« less

The role of climatic variables in winter cereal yields: a retrospective analysis.

PubMed

Luo, Qunying; Wen, Li

2015-02-01

This study examined the effects of observed climate including [CO2] on winter cereal [winter wheat (Triticum aestivum), barley (Hordeum vulgare) and oat (Avena sativa)] yields by adopting robust statistical analysis/modelling approaches (i.e. autoregressive fractionally integrated moving average, generalised addition model) based on long time series of historical climate data and cereal yield data at three locations (Moree, Dubbo and Wagga Wagga) in New South Wales, Australia. Research results show that (1) growing season rainfall was significantly, positively and non-linearly correlated with crop yield at all locations considered; (2) [CO2] was significantly, positively and non-linearly correlated with crop yields in all cases except wheat and barley yields at Wagga Wagga; (3) growing season maximum temperature was significantly, negatively and non-linearly correlated with crop yields at Dubbo and Moree (except for barley); and (4) radiation was only significantly correlated with oat yield at Wagga Wagga. This information will help to identify appropriate management adaptation options in dealing with the risk and in taking the opportunities of climate change.

The reliability and reproducibility of cephalometric measurements: a comparison of conventional and digital methods

PubMed Central

AlBarakati, SF; Kula, KS; Ghoneima, AA

2012-01-01

Objective The aim of this study was to assess the reliability and reproducibility of angular and linear measurements of conventional and digital cephalometric methods. Methods A total of 13 landmarks and 16 skeletal and dental parameters were defined and measured on pre-treatment cephalometric radiographs of 30 patients. The conventional and digital tracings and measurements were performed twice by the same examiner with a 6 week interval between measurements. The reliability within the method was determined using Pearson's correlation coefficient (r2). The reproducibility between methods was calculated by paired t-test. The level of statistical significance was set at p < 0.05. Results All measurements for each method were above 0.90 r2 (strong correlation) except maxillary length, which had a correlation of 0.82 for conventional tracing. Significant differences between the two methods were observed in most angular and linear measurements except for ANB angle (p = 0.5), angle of convexity (p = 0.09), anterior cranial base (p = 0.3) and the lower anterior facial height (p = 0.6). Conclusion In general, both methods of conventional and digital cephalometric analysis are highly reliable. Although the reproducibility of the two methods showed some statistically significant differences, most differences were not clinically significant. PMID:22184624

Testing the dose-response specification in epidemiology: public health and policy consequences for lead.

PubMed

Rothenberg, Stephen J; Rothenberg, Jesse C

2005-09-01

Statistical evaluation of the dose-response function in lead epidemiology is rarely attempted. Economic evaluation of health benefits of lead reduction usually assumes a linear dose-response function, regardless of the outcome measure used. We reanalyzed a previously published study, an international pooled data set combining data from seven prospective lead studies examining contemporaneous blood lead effect on IQ (intelligence quotient) of 7-year-old children (n = 1,333). We constructed alternative linear multiple regression models with linear blood lead terms (linear-linear dose response) and natural-log-transformed blood lead terms (log-linear dose response). We tested the two lead specifications for nonlinearity in the models, compared the two lead specifications for significantly better fit to the data, and examined the effects of possible residual confounding on the functional form of the dose-response relationship. We found that a log-linear lead-IQ relationship was a significantly better fit than was a linear-linear relationship for IQ (p = 0.009), with little evidence of residual confounding of included model variables. We substituted the log-linear lead-IQ effect in a previously published health benefits model and found that the economic savings due to U.S. population lead decrease between 1976 and 1999 (from 17.1 microg/dL to 2.0 microg/dL) was 2.2 times (319 billion dollars) that calculated using a linear-linear dose-response function (149 billion dollars). The Centers for Disease Control and Prevention action limit of 10 microg/dL for children fails to protect against most damage and economic cost attributable to lead exposure.

Demographic confounders in volumetric MRI analysis: is the posterior fossa really small in the adult Chiari 1 malformation?

PubMed

Roller, Lauren A; Bruce, Beau B; Saindane, Amit M

2015-04-01

Measurement of posterior fossa volume has been proposed to have diagnostic utility and physiologic significance in the Chiari malformation type 1. This study evaluated the effects of demographics on posterior fossa volume and total intracranial volume in adult control subjects, adult patients with Chiari malformation type 1, and adult patients with idiopathic intracranial hypertension, who may share some imaging features of patients with Chiari malformation type 1. Twenty-eight patients with Chiari malformation type 1, 21 patients with idiopathic intracranial hypertension, and 113 control subjects underwent brain MRI including contrast-enhanced 3D gradient-recalled echo (GRE) T1-weighted imaging. Linear measurements of the posterior fossa and intracranial space were obtained. Manual segmentation of the posterior fossa and intracranial space was performed to yield posterior fossa volume and total intracranial volume. Age, sex, race, and body mass index (weight in kilograms divided by the square of height in meters; BMI) were controlled for when comparing cohorts. Three of the 12 linear measurements significantly predicted total intracranial volume (accounting for 74% of variance), and four predicted posterior fossa volume (54% of variance). Age, race, sex, and BMI each statistically significantly influenced posterior fossa volume and total intracranial volume. No statistically significant differences in posterior fossa volume, total intracranial volume, or ratio of posterior fossa volume to total intracranial volume were seen between the Chiari malformation type 1 group and control group after controlling for demographics. Patients with idiopathic intracranial hypertension were more likely than control subjects to have smaller posterior fossa volumes (odds ratio [OR]=1.81; p=0.01) and larger total intracranial volumes (OR=1.24; p=0.06). Linear measurements of the posterior fossa are not strong predictors of posterior fossa volume. Age, race, sex, and BMI have statistically significant effects on intracranial measurements that must be considered, particularly with respect to posterior fossa volume in Chiari malformation type 1. Even when these demographic variables are appropriately accounted for, other similarly presenting diseases may show small posterior fossa volumes.

Regression Model Term Selection for the Analysis of Strain-Gage Balance Calibration Data

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert Manfred; Volden, Thomas R.

2010-01-01

The paper discusses the selection of regression model terms for the analysis of wind tunnel strain-gage balance calibration data. Different function class combinations are presented that may be used to analyze calibration data using either a non-iterative or an iterative method. The role of the intercept term in a regression model of calibration data is reviewed. In addition, useful algorithms and metrics originating from linear algebra and statistics are recommended that will help an analyst (i) to identify and avoid both linear and near-linear dependencies between regression model terms and (ii) to make sure that the selected regression model of the calibration data uses only statistically significant terms. Three different tests are suggested that may be used to objectively assess the predictive capability of the final regression model of the calibration data. These tests use both the original data points and regression model independent confirmation points. Finally, data from a simplified manual calibration of the Ames MK40 balance is used to illustrate the application of some of the metrics and tests to a realistic calibration data set.

An operational definition of a statistically meaningful trend.

PubMed

Bryhn, Andreas C; Dimberg, Peter H

2011-04-28

Linear trend analysis of time series is standard procedure in many scientific disciplines. If the number of data is large, a trend may be statistically significant even if data are scattered far from the trend line. This study introduces and tests a quality criterion for time trends referred to as statistical meaningfulness, which is a stricter quality criterion for trends than high statistical significance. The time series is divided into intervals and interval mean values are calculated. Thereafter, r(2) and p values are calculated from regressions concerning time and interval mean values. If r(2) ≥ 0.65 at p ≤ 0.05 in any of these regressions, then the trend is regarded as statistically meaningful. Out of ten investigated time series from different scientific disciplines, five displayed statistically meaningful trends. A Microsoft Excel application (add-in) was developed which can perform statistical meaningfulness tests and which may increase the operationality of the test. The presented method for distinguishing statistically meaningful trends should be reasonably uncomplicated for researchers with basic statistics skills and may thus be useful for determining which trends are worth analysing further, for instance with respect to causal factors. The method can also be used for determining which segments of a time trend may be particularly worthwhile to focus on.

Tests of Alignment among Assessment, Standards, and Instruction Using Generalized Linear Model Regression

ERIC Educational Resources Information Center

Fulmer, Gavin W.; Polikoff, Morgan S.

2014-01-01

An essential component in school accountability efforts is for assessments to be well-aligned with the standards or curriculum they are intended to measure. However, relatively little prior research has explored methods to determine statistical significance of alignment or misalignment. This study explores analyses of alignment as a special case…

Statistical properties of the radiation from SASE FEL operating in the linear regime

NASA Astrophysics Data System (ADS)

Saldin, E. L.; Schneidmiller, E. A.; Yurkov, M. V.

1998-02-01

The paper presents comprehensive analysis of statistical properties of the radiation from self amplified spontaneous emission (SASE) free electron laser operating in linear mode. The investigation has been performed in a one-dimensional approximation, assuming the electron pulse length to be much larger than a coherence length of the radiation. The following statistical properties of the SASE FEL radiation have been studied: field correlations, distribution of the radiation energy after monochromator installed at the FEL amplifier exit and photoelectric counting statistics of SASE FEL radiation. It is shown that the radiation from SASE FEL operating in linear regime possesses all the features corresponding to completely chaotic polarized radiation.

Non-linear scaling of a musculoskeletal model of the lower limb using statistical shape models.

PubMed

Nolte, Daniel; Tsang, Chui Kit; Zhang, Kai Yu; Ding, Ziyun; Kedgley, Angela E; Bull, Anthony M J

2016-10-03

Accurate muscle geometry for musculoskeletal models is important to enable accurate subject-specific simulations. Commonly, linear scaling is used to obtain individualised muscle geometry. More advanced methods include non-linear scaling using segmented bone surfaces and manual or semi-automatic digitisation of muscle paths from medical images. In this study, a new scaling method combining non-linear scaling with reconstructions of bone surfaces using statistical shape modelling is presented. Statistical Shape Models (SSMs) of femur and tibia/fibula were used to reconstruct bone surfaces of nine subjects. Reference models were created by morphing manually digitised muscle paths to mean shapes of the SSMs using non-linear transformations and inter-subject variability was calculated. Subject-specific models of muscle attachment and via points were created from three reference models. The accuracy was evaluated by calculating the differences between the scaled and manually digitised models. The points defining the muscle paths showed large inter-subject variability at the thigh and shank - up to 26mm; this was found to limit the accuracy of all studied scaling methods. Errors for the subject-specific muscle point reconstructions of the thigh could be decreased by 9% to 20% by using the non-linear scaling compared to a typical linear scaling method. We conclude that the proposed non-linear scaling method is more accurate than linear scaling methods. Thus, when combined with the ability to reconstruct bone surfaces from incomplete or scattered geometry data using statistical shape models our proposed method is an alternative to linear scaling methods. Copyright © 2016 The Author. Published by Elsevier Ltd.. All rights reserved.

Critical Fluctuations in Cortical Models Near Instability

PubMed Central

Aburn, Matthew J.; Holmes, C. A.; Roberts, James A.; Boonstra, Tjeerd W.; Breakspear, Michael

2012-01-01

Computational studies often proceed from the premise that cortical dynamics operate in a linearly stable domain, where fluctuations dissipate quickly and show only short memory. Studies of human electroencephalography (EEG), however, have shown significant autocorrelation at time lags on the scale of minutes, indicating the need to consider regimes where non-linearities influence the dynamics. Statistical properties such as increased autocorrelation length, increased variance, power law scaling, and bistable switching have been suggested as generic indicators of the approach to bifurcation in non-linear dynamical systems. We study temporal fluctuations in a widely-employed computational model (the Jansen–Rit model) of cortical activity, examining the statistical signatures that accompany bifurcations. Approaching supercritical Hopf bifurcations through tuning of the background excitatory input, we find a dramatic increase in the autocorrelation length that depends sensitively on the direction in phase space of the input fluctuations and hence on which neuronal subpopulation is stochastically perturbed. Similar dependence on the input direction is found in the distribution of fluctuation size and duration, which show power law scaling that extends over four orders of magnitude at the Hopf bifurcation. We conjecture that the alignment in phase space between the input noise vector and the center manifold of the Hopf bifurcation is directly linked to these changes. These results are consistent with the possibility of statistical indicators of linear instability being detectable in real EEG time series. However, even in a simple cortical model, we find that these indicators may not necessarily be visible even when bifurcations are present because their expression can depend sensitively on the neuronal pathway of incoming fluctuations. PMID:22952464

Photometric analysis of esthetically pleasant and unpleasant facial profile.

PubMed

Fortes, Helena Nunes da Rocha; Guimarães, Thamirys Correia; Belo, Ivana Mara Lira; da Matta, Edgard Norões Rodrigues

2014-01-01

To identify which linear, angular and proportionality measures could influence a profile to be considered esthetically pleasant or unpleasant, and to assess sexual dimorphism. 150 standardized facial profile photographs of dental students of both sexes were obtained and printed on photographic paper. Ten plastic surgeons, ten orthodontists and ten layperson answered a questionnaire characterizing each profile as pleasant, acceptable or unpleasant. With the use of a score system, the 15 most pleasant and unpleasant profiles of each sex were selected. The photographs were scanned into AutoCAD computer software. Linear, angular and proportion measurements were obtained using the software tools. The average values between groups were compared by the Student's t-test and the Mann-Whitney test at a significance level of 5%. The linear measures LL-S, LL-H, LL-E, LL-B and Pn-H showed statistically significant differences (p < 0.05). Statistical differences were also found in the angular measures G'.Pn.Pg', G'.Sn.Pg' and Sn.Me'.C and in the proportions G'-Sn:Sn-Me' and Sn-Gn':Gn'-C (p < 0.05). Differences between sexes were found for the linear measure Ala-Pn, angles G'-Pg'.N-Pn, Sn.Me'.C, and proportions Gn'-Sn:Sn-Me' and Ala-Pn:N'-Sn. (p < 0.05). The anteroposterior position of the lower lip, the amount of nose that influences the profile, facial convexity, total vertical proportion and lip-chin proportion appear to influence pleasantness of facial profile. Sexual dimorphism was identified in nasal length, nasofacial and lower third of the face angles, total vertical and nasal height/length proportions.

Community air pollution and mortality: Analysis of 1980 data from US metropolitan areas. 1: Particulate air pollution

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

Lipfert, F.W.

1992-11-01

1980 data from up to 149 metropolitan areas were used to define cross-sectional associations between community air pollution and excess human mortality. The regression model proposed by Oezkaynak and Thurston, which accounted for age, race, education, poverty, and population density, was evaluated and several new models were developed. The new models also accounted for population change, drinking water hardness, and smoking, and included a more detailed description of race. Cause-of-death categories analyzed include all causes, all non-external causes, major cardiovascular diseases, and chronic obstructive pulmonary diseases (COPD). Both annual mortality rates and their logarithms were analyzed. The data on particulatesmore » were averaged across all monitoring stations available for each SMSA and the TSP data were restricted to the year 1980. The associations between mortality and air pollution were found to be dependent on the socioeconomic factors included in the models, the specific locations included din the data set, and the type of statistical model used. Statistically significant associations were found between TSP and mortality due to non-external causes with log-linear models, but not with a linear model, and between TS and COPD mortality for both linear and log-linear models. When the sulfate contribution to TSP was subtracted, the relationship with COPD mortality was strengthened. Scatter plots and quintile analyses suggested a TSP threshold for COPD mortality at around 65 ug/m{sup 3} (annual average). SO{sub 4}{sup {minus}2}, Mn, PM{sup 15}, and PM{sub 2.5} were not significantly associated with mortality using the new models.« less

Statistics of Statisticians: Critical Mass of Statistics and Operational Research Groups

NASA Astrophysics Data System (ADS)

Kenna, Ralph; Berche, Bertrand

Using a recently developed model, inspired by mean field theory in statistical physics, and data from the UK's Research Assessment Exercise, we analyse the relationship between the qualities of statistics and operational research groups and the quantities of researchers in them. Similar to other academic disciplines, we provide evidence for a linear dependency of quality on quantity up to an upper critical mass, which is interpreted as the average maximum number of colleagues with whom a researcher can communicate meaningfully within a research group. The model also predicts a lower critical mass, which research groups should strive to achieve to avoid extinction. For statistics and operational research, the lower critical mass is estimated to be 9 ± 3. The upper critical mass, beyond which research quality does not significantly depend on group size, is 17 ± 6.

Occupational dust and radiation exposure and mortality from stomach cancer among German uranium miners, 1946-2003.

PubMed

Kreuzer, M; Straif, K; Marsh, J W; Dufey, F; Grosche, B; Nosske, D; Sogl, M

2012-03-01

'Dusty occupations' and exposure to low-dose radiation have been suggested as potential risk factors for stomach cancer. Data from the German uranium miner cohort study are used to further evaluate this topic. The cohort includes 58 677 miners with complete information on occupational exposure to dust, arsenic and radiation dose based on a detailed job-exposure matrix. A total of 592 stomach cancer deaths occurred in the follow-up period from 1946 to 2003. A Poisson regression model stratified by age and calendar year was used to calculate the excess relative risk (ERR) per unit of cumulative exposure to fine dust or from cumulative absorbed dose to stomach from α or low-LET (low linear energy transfer) radiation. For arsenic exposure, a binary quadratic model was applied. After adjustment for each of the three other variables, a statistically non-significant linear relationship was observed for absorbed dose from low-LET radiation (ERR/Gy=0.30, 95% CI -1.26 to 1.87), α radiation (ERR/Gy=22.5, 95% CI -26.5 to 71.5) and fine dust (ERR/dust-year=0.0012, 95% CI -0.0020 to 0.0043). The relationship between stomach cancer and arsenic exposure was non-linear with a 2.1-fold higher RR (95% CI 0.9 to 3.3) in the exposure category above 500 compared with 0 dust-years. Positive statistically non-significant relationships between stomach cancer and arsenic dust, fine dust and absorbed dose from α and low-LET radiation were found. Overall, low statistical power due to low doses from radiation and dust are of concern.

Validating Variational Bayes Linear Regression Method With Multi-Central Datasets.

PubMed

Murata, Hiroshi; Zangwill, Linda M; Fujino, Yuri; Matsuura, Masato; Miki, Atsuya; Hirasawa, Kazunori; Tanito, Masaki; Mizoue, Shiro; Mori, Kazuhiko; Suzuki, Katsuyoshi; Yamashita, Takehiro; Kashiwagi, Kenji; Shoji, Nobuyuki; Asaoka, Ryo

2018-04-01

To validate the prediction accuracy of variational Bayes linear regression (VBLR) with two datasets external to the training dataset. The training dataset consisted of 7268 eyes of 4278 subjects from the University of Tokyo Hospital. The Japanese Archive of Multicentral Databases in Glaucoma (JAMDIG) dataset consisted of 271 eyes of 177 patients, and the Diagnostic Innovations in Glaucoma Study (DIGS) dataset includes 248 eyes of 173 patients, which were used for validation. Prediction accuracy was compared between the VBLR and ordinary least squared linear regression (OLSLR). First, OLSLR and VBLR were carried out using total deviation (TD) values at each of the 52 test points from the second to fourth visual fields (VFs) (VF2-4) to 2nd to 10th VF (VF2-10) of each patient in JAMDIG and DIGS datasets, and the TD values of the 11th VF test were predicted every time. The predictive accuracy of each method was compared through the root mean squared error (RMSE) statistic. OLSLR RMSEs with the JAMDIG and DIGS datasets were between 31 and 4.3 dB, and between 19.5 and 3.9 dB. On the other hand, VBLR RMSEs with JAMDIG and DIGS datasets were between 5.0 and 3.7, and between 4.6 and 3.6 dB. There was statistically significant difference between VBLR and OLSLR for both datasets at every series (VF2-4 to VF2-10) (P < 0.01 for all tests). However, there was no statistically significant difference in VBLR RMSEs between JAMDIG and DIGS datasets at any series of VFs (VF2-2 to VF2-10) (P > 0.05). VBLR outperformed OLSLR to predict future VF progression, and the VBLR has a potential to be a helpful tool at clinical settings.

Two Computer Programs for the Statistical Evaluation of a Weighted Linear Composite.

ERIC Educational Resources Information Center

Sands, William A.

1978-01-01

Two computer programs (one batch, one interactive) are designed to provide statistics for a weighted linear combination of several component variables. Both programs provide mean, variance, standard deviation, and a validity coefficient. (Author/JKS)

Statistical aspects of solar flares

NASA Technical Reports Server (NTRS)

Wilson, Robert M.

1987-01-01

A survey of the statistical properties of 850 H alpha solar flares during 1975 is presented. Comparison of the results found here with those reported elsewhere for different epochs is accomplished. Distributions of rise time, decay time, and duration are given, as are the mean, mode, median, and 90th percentile values. Proportions by selected groupings are also determined. For flares in general, mean values for rise time, decay time, and duration are 5.2 + or - 0.4 min, and 18.1 + or 1.1 min, respectively. Subflares, accounting for nearly 90 percent of the flares, had mean values lower than those found for flares of H alpha importance greater than 1, and the differences are statistically significant. Likewise, flares of bright and normal relative brightness have mean values of decay time and duration that are significantly longer than those computed for faint flares, and mass-motion related flares are significantly longer than non-mass-motion related flares. Seventy-three percent of the mass-motion related flares are categorized as being a two-ribbon flare and/or being accompanied by a high-speed dark filament. Slow rise time flares (rise time greater than 5 min) have a mean value for duration that is significantly longer than that computed for fast rise time flares, and long-lived duration flares (duration greater than 18 min) have a mean value for rise time that is significantly longer than that computed for short-lived duration flares, suggesting a positive linear relationship between rise time and duration for flares. Monthly occurrence rates for flares in general and by group are found to be linearly related in a positive sense to monthly sunspot number. Statistical testing reveals the association between sunspot number and numbers of flares to be significant at the 95 percent level of confidence, and the t statistic for slope is significant at greater than 99 percent level of confidence. Dependent upon the specific fit, between 58 percent and 94 percent of the variation can be accounted for with the linear fits. A statistically significant Northern Hemisphere flare excess (P less than 1 percent) was found, as was a Western Hemisphere excess (P approx 3 percent). Subflares were more prolific within 45 deg of central meridian (P less than 1 percent), while flares of H alpha importance or = 1 were more prolific near the limbs greater than 45 deg from central meridian; P approx 2 percent). Two-ribbon flares were more frequent within 45 deg of central meridian (P less than 1 percent). Slow rise time flares occurred more frequently in the western hemisphere (P approx 2 percent), as did short-lived duration flares (P approx 9 percent), but fast rise time flares were not preferentially distributed (in terms of east-west or limb-disk). Long-lived duration flares occurred more often within 45 deg 0 central meridian (P approx 7 percent). Mean durations for subflares and flares of H alpha importance or + 1, found within 45 deg of central meridian, are 14 percent and 70 percent, respectively, longer than those found for flares closer to the limb. As compared to flares occurring near cycle maximum, the flares of 1975 (near solar minimum) have mean values of rise time, decay time, and duration that are significantly shorter. A flare near solar maximum, on average, is about 1.6 times longer than one occurring near solar minimum.

Patterns of medicinal plant use: an examination of the Ecuadorian Shuar medicinal flora using contingency table and binomial analyses.

PubMed

Bennett, Bradley C; Husby, Chad E

2008-03-28

Botanical pharmacopoeias are non-random subsets of floras, with some taxonomic groups over- or under-represented. Moerman [Moerman, D.E., 1979. Symbols and selectivity: a statistical analysis of Native American medical ethnobotany, Journal of Ethnopharmacology 1, 111-119] introduced linear regression/residual analysis to examine these patterns. However, regression, the commonly-employed analysis, suffers from several statistical flaws. We use contingency table and binomial analyses to examine patterns of Shuar medicinal plant use (from Amazonian Ecuador). We first analyzed the Shuar data using Moerman's approach, modified to better meet requirements of linear regression analysis. Second, we assessed the exact randomization contingency table test for goodness of fit. Third, we developed a binomial model to test for non-random selection of plants in individual families. Modified regression models (which accommodated assumptions of linear regression) reduced R(2) to from 0.59 to 0.38, but did not eliminate all problems associated with regression analyses. Contingency table analyses revealed that the entire flora departs from the null model of equal proportions of medicinal plants in all families. In the binomial analysis, only 10 angiosperm families (of 115) differed significantly from the null model. These 10 families are largely responsible for patterns seen at higher taxonomic levels. Contingency table and binomial analyses offer an easy and statistically valid alternative to the regression approach.

Improving validation methods for molecular diagnostics: application of Bland-Altman, Deming and simple linear regression analyses in assay comparison and evaluation for next-generation sequencing

PubMed Central

Misyura, Maksym; Sukhai, Mahadeo A; Kulasignam, Vathany; Zhang, Tong; Kamel-Reid, Suzanne; Stockley, Tracy L

2018-01-01

Aims A standard approach in test evaluation is to compare results of the assay in validation to results from previously validated methods. For quantitative molecular diagnostic assays, comparison of test values is often performed using simple linear regression and the coefficient of determination (R2), using R2 as the primary metric of assay agreement. However, the use of R2 alone does not adequately quantify constant or proportional errors required for optimal test evaluation. More extensive statistical approaches, such as Bland-Altman and expanded interpretation of linear regression methods, can be used to more thoroughly compare data from quantitative molecular assays. Methods We present the application of Bland-Altman and linear regression statistical methods to evaluate quantitative outputs from next-generation sequencing assays (NGS). NGS-derived data sets from assay validation experiments were used to demonstrate the utility of the statistical methods. Results Both Bland-Altman and linear regression were able to detect the presence and magnitude of constant and proportional error in quantitative values of NGS data. Deming linear regression was used in the context of assay comparison studies, while simple linear regression was used to analyse serial dilution data. Bland-Altman statistical approach was also adapted to quantify assay accuracy, including constant and proportional errors, and precision where theoretical and empirical values were known. Conclusions The complementary application of the statistical methods described in this manuscript enables more extensive evaluation of performance characteristics of quantitative molecular assays, prior to implementation in the clinical molecular laboratory. PMID:28747393

Analysis of broadcasting satellite service feeder link power control and polarization

NASA Technical Reports Server (NTRS)

Sullivan, T. M.

1982-01-01

Statistical analyses of carrier to interference power ratios (C/Is) were performed in assessing 17.5 GHz feeder links using (1) fixed power and power control, and (2) orthogonal linear and orthogonal circular polarizations. The analysis methods and attenuation/depolarization data base were based on CCIR findings to the greatest possible extent. Feeder links using adaptive power control were found to neither cause or suffer significant C/I degradation relative to that for fixed power feeder links having similar or less stringent availability objectives. The C/Is for sharing between orthogonal linearly polarized feeder links were found to be significantly higher than those for circular polarization only in links to nominally colocated satellites from nominally colocated Earth stations in high attenuation environments.

A comparison of linear and nonlinear statistical techniques in performance attribution.

PubMed

Chan, N H; Genovese, C R

2001-01-01

Performance attribution is usually conducted under the linear framework of multifactor models. Although commonly used by practitioners in finance, linear multifactor models are known to be less than satisfactory in many situations. After a brief survey of nonlinear methods, nonlinear statistical techniques are applied to performance attribution of a portfolio constructed from a fixed universe of stocks using factors derived from some commonly used cross sectional linear multifactor models. By rebalancing this portfolio monthly, the cumulative returns for procedures based on standard linear multifactor model and three nonlinear techniques-model selection, additive models, and neural networks-are calculated and compared. It is found that the first two nonlinear techniques, especially in combination, outperform the standard linear model. The results in the neural-network case are inconclusive because of the great variety of possible models. Although these methods are more complicated and may require some tuning, toolboxes are developed and suggestions on calibration are proposed. This paper demonstrates the usefulness of modern nonlinear statistical techniques in performance attribution.

Prediction of rainfall anomalies during the dry to wet transition season over the Southern Amazonia using machine learning tools

NASA Astrophysics Data System (ADS)

Shan, X.; Zhang, K.; Zhuang, Y.; Fu, R.; Hong, Y.

2017-12-01

Seasonal prediction of rainfall during the dry-to-wet transition season in austral spring (September-November) over southern Amazonia is central for improving planting crops and fire mitigation in that region. Previous studies have identified the key large-scale atmospheric dynamic and thermodynamics pre-conditions during the dry season (June-August) that influence the rainfall anomalies during the dry to wet transition season over Southern Amazonia. Based on these key pre-conditions during dry season, we have evaluated several statistical models and developed a Neural Network based statistical prediction system to predict rainfall during the dry to wet transition for Southern Amazonia (5-15°S, 50-70°W). Multivariate Empirical Orthogonal Function (EOF) Analysis is applied to the following four fields during JJA from the ECMWF Reanalysis (ERA-Interim) spanning from year 1979 to 2015: geopotential height at 200 hPa, surface relative humidity, convective inhibition energy (CIN) index and convective available potential energy (CAPE), to filter out noise and highlight the most coherent spatial and temporal variations. The first 10 EOF modes are retained for inputs to the statistical models, accounting for at least 70% of the total variance in the predictor fields. We have tested several linear and non-linear statistical methods. While the regularized Ridge Regression and Lasso Regression can generally capture the spatial pattern and magnitude of rainfall anomalies, we found that that Neural Network performs best with an accuracy greater than 80%, as expected from the non-linear dependence of the rainfall on the large-scale atmospheric thermodynamic conditions and circulation. Further tests of various prediction skill metrics and hindcasts also suggest this Neural Network prediction approach can significantly improve seasonal prediction skill than the dynamic predictions and regression based statistical predictions. Thus, this statistical prediction system could have shown potential to improve real-time seasonal rainfall predictions in the future.

Scoring and staging systems using cox linear regression modeling and recursive partitioning.

PubMed

Lee, J W; Um, S H; Lee, J B; Mun, J; Cho, H

2006-01-01

Scoring and staging systems are used to determine the order and class of data according to predictors. Systems used for medical data, such as the Child-Turcotte-Pugh scoring and staging systems for ordering and classifying patients with liver disease, are often derived strictly from physicians' experience and intuition. We construct objective and data-based scoring/staging systems using statistical methods. We consider Cox linear regression modeling and recursive partitioning techniques for censored survival data. In particular, to obtain a target number of stages we propose cross-validation and amalgamation algorithms. We also propose an algorithm for constructing scoring and staging systems by integrating local Cox linear regression models into recursive partitioning, so that we can retain the merits of both methods such as superior predictive accuracy, ease of use, and detection of interactions between predictors. The staging system construction algorithms are compared by cross-validation evaluation of real data. The data-based cross-validation comparison shows that Cox linear regression modeling is somewhat better than recursive partitioning when there are only continuous predictors, while recursive partitioning is better when there are significant categorical predictors. The proposed local Cox linear recursive partitioning has better predictive accuracy than Cox linear modeling and simple recursive partitioning. This study indicates that integrating local linear modeling into recursive partitioning can significantly improve prediction accuracy in constructing scoring and staging systems.

Findings regarding the relationships between sociodemographic, psychological, comorbidity factors, and functional status, in geriatric inpatients.

PubMed

Capisizu, Ana; Aurelian, Sorina; Zamfirescu, Andreea; Omer, Ioana; Haras, Monica; Ciobotaru, Camelia; Onose, Liliana; Spircu, Tiberiu; Onose, Gelu

2015-01-01

To assess the impact of socio-demographic and comorbidity factors, and quantified depressive symptoms on disability in inpatients. Observational cross-sectional study, including a number of 80 elderly (16 men, 64 women; mean age 72.48 years; standard deviation 9.95 years) admitted in the Geriatrics Clinic of "St. Luca" Hospital, Bucharest, between May-July, 2012. We used the Functional Independence Measure, Geriatric Depression Scale and an array of socio-demographic and poly-pathology parameters. Statistical analysis included Wilcoxon and Kruskal-Wallis tests for ordinal variables, linear bivariate correlations, general linear model analysis, ANOVA. FIM scores were negatively correlated with age (R=-0.301; 95%CI=-0.439 -0.163; p=0.007); GDS scores had a statistically significant negative correlation (R=-0.322; 95% CI=-0.324 -0.052; p=0.004) with FIM scores. A general linear model, including other variables (gender, age, provenance, matrimonial state, living conditions, education, respectively number of chronic illnesses) as factors, found living conditions (p=0.027) and the combination of matrimonial state and gender (p=0.004) to significantly influence FIM scores. ANOVA showed significant differences in FIM scores stratified by the number of chronic diseases (p=0.035). Our study objectified the negative impact of depression on functional status; interestingly, education had no influence on FIM scores; living conditions and a combination of matrimonial state and gender had an important impact: patients with living spouses showed better functional scores than divorced/widowers; the number of chronic diseases also affected the FIM scores: lower in patients with significant polypathology. These findings should be considered when designing geriatric rehabilitation programs, especially for home--including skilled--cares.

A simple linear regression method for quantitative trait loci linkage analysis with censored observations.

PubMed

Anderson, Carl A; McRae, Allan F; Visscher, Peter M

2006-07-01

Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using simulation we compare this method to both the Cox and Weibull proportional hazards models and a standard linear regression method that ignores censoring. The grouped linear regression method is of equivalent power to both the Cox and Weibull proportional hazards methods and is significantly better than the standard linear regression method when censored observations are present. The method is also robust to the proportion of censored individuals and the underlying distribution of the trait. On the basis of linear regression methodology, the grouped linear regression model is computationally simple and fast and can be implemented readily in freely available statistical software.

Statistics of the stochastically forced Lorenz attractor by the Fokker-Planck equation and cumulant expansions.

PubMed

Allawala, Altan; Marston, J B

2016-11-01

We investigate the Fokker-Planck description of the equal-time statistics of the three-dimensional Lorenz attractor with additive white noise. The invariant measure is found by computing the zero (or null) mode of the linear Fokker-Planck operator as a problem of sparse linear algebra. Two variants are studied: a self-adjoint construction of the linear operator and the replacement of diffusion with hyperdiffusion. We also access the low-order statistics of the system by a perturbative expansion in equal-time cumulants. A comparison is made to statistics obtained by the standard approach of accumulation via direct numerical simulation. Theoretical and computational aspects of the Fokker-Planck and cumulant expansion methods are discussed.

Numeracy moderates the influence of task-irrelevant affect on probability weighting.

PubMed

Traczyk, Jakub; Fulawka, Kamil

2016-06-01

Statistical numeracy, defined as the ability to understand and process statistical and probability information, plays a significant role in superior decision making. However, recent research has demonstrated that statistical numeracy goes beyond simple comprehension of numbers and mathematical operations. On the contrary to previous studies that were focused on emotions integral to risky prospects, we hypothesized that highly numerate individuals would exhibit more linear probability weighting because they would be less biased by incidental and decision-irrelevant affect. Participants were instructed to make a series of insurance decisions preceded by negative (i.e., fear-inducing) or neutral stimuli. We found that incidental negative affect increased the curvature of the probability weighting function (PWF). Interestingly, this effect was significant only for less numerate individuals, while probability weighting in more numerate people was not altered by decision-irrelevant affect. We propose two candidate mechanisms for the observed effect. Copyright © 2016 Elsevier B.V. All rights reserved.

Estimating the color of maxillary central incisors based on age and gender

PubMed Central

Gozalo-Diaz, David; Johnston, William M.; Wee, Alvin G.

2008-01-01

Statement of problem There is no scientific information regarding the selection of the color of teeth for edentulous patients. Purpose The purpose of this study was to evaluate linear regression models that may be used to predict color parameters for central incisors of edentulous patients based on some characteristics of dentate subjects. Material and methods A spectroradiometer and an external light source were set in a noncontacting 45/0 degree (45-degree illumination and 0-degree observer) optical configuration to measure the color of subjects’ vital craniofacial structures (maxillary central incisor, attached gingiva, and facial skin). The subjects (n=120) were stratified into 5 age groups with 4 racial groups and balanced for gender. Linear first-order regression was used to determine the significant factors (α=.05) in the prediction model for each color direction of the color of the maxillary central incisor. Age, gender, and color of the other craniofacial structures were studied as potential predictors. Final predictions in each color direction were based only on the statistically significant factors, and then the color differences between observed and predicted CIELAB values for the central incisors were calculated and summarized. Results The statistically significant predictors of age and gender accounted for 36% of the total variability in L*. The statistically significant predictor of age accounted for 16% of the total variability in a*. The statistically significant predictors of age and gender accounted for 21% of the variability in b*. The mean ΔE (SD) between predicted and observed CIELAB values for the central incisor was 5.8 (3.2). Conclusions Age and gender were found to be statistically significant determinants in predicting the natural color of central incisors. Although the precision of these predictions was less than the median color difference found for all pairs of teeth studied, and may be considered an acceptable precision, further study is needed to reduce this precision to the limit of detection. Clinical Implications Age is highly correlated with the natural color of the central incisors. When age increases, the central incisor becomes darker, more reddish, and more yellow. Also, the women subjects in this study had lighter and less yellow central incisors than the men. PMID:18672125

[Comparison of thromboelastography and routine coagulation tests for evaluation of blood coagulation function in patients].

PubMed

Chen, Guan-Yi; Ou Yang, Xi-Lin; Wu, Jing-Hui; Wang, Li-Hua; Yang, Jin-Hua; Gu, Li-Nan; Lu, Zhu-Jie; Zhao, Xiao-Zi

2015-04-01

To investigate the correlation and consistency between thromboelastography(TEG) and routine coagulation tests, and to evaluate the value of the two methods in determining the blood coagulation of patients. The TEG, routine coagulation tests and platelet counts of 182 patients from the Intensive Care Unit(ICU) and Department of Gastroenterology in our hospital from January to September 2014 were performed and analyzed retrospectively for their correlation, Kappa identity test analysis and chi-square test, and the diagnostic sensitivity and specificity of both methods in the patients with bleeding were evaluated. The TEG R time and PT, R time and APTT showed a linear dependence (P<0.01). The relationship between the TEG K value, α-Angle, MA and Fibrinogen showed a linear dependence (P<0.001). And the relationship between the TEG K value, α-Angle, MA and the platelet count were in a linear dependent way (P<0.001). The Kappa values of the TEG R time with PT and APTT were 0.038 (P>0.05) and 0.061 (P>0.05), respectively. The chi-square test values of the TEG R time with PT and APTT were 35.309 (P<0.001) and 15.848 (P<0.001), respectively. The Fibrinogen and the TEG K value, α-Angle, MA value had statistical significance (P<0.001), with a Kappa value of 0.323, 0.288 and 0.427, respectively. The chi-square test values between Fibrinogen and the TEG K value, α-Angle, MA value were not statistically significant, with X2=1.091 (P=0.296), X2=1.361 (P=0.243), X2=0.108 (P=0.742). The Kappa values of the platelet count and the TEG K value, α-Angle, MA value were 0.379, 0.208 and 0.352, respectively, which were also statistically significant difference (P<0.001). The chi-square test values between the platelet count and the TEG K value, α-Angle, MA value showed a statistically significant difference (P<0.001), with X2=37.5, X2=37.23, X2=26.630. The diagnostic sensitivity of the two methods for the patients with bleeding was less than 50%. There was a significant correlation between some TEG parameters and routine coagulation tests, but the consistency is weak. Moreover, the diagnostic sensitivity of two methods in the patients with bleeding is low. It was concluded that the TEG cannot replace the conventional coagulation tests, and the preferable method remains uncertain which could reflect the risk of bleeding.

Sex-related shape dimorphism in the human radiocarpal and midcarpal joints.

PubMed

Kivell, Tracy L; Guimont, Isabelle; Wall, Christine E

2013-01-01

Previous research has revealed significant size differences between human male and female carpal bones but it is unknown if there are significant shape differences as well. This study investigated sex-related shape variation and allometric patterns in five carpal bones that make up the radiocarpal and midcarpal joints in modern humans. We found that many aspects of carpal shape (76% of all variables quantified) were similar between males and females, despite variation in size. However, 10 of the shape ratios were significantly different between males and females, with at least one significant shape difference observed in each carpal bone. Within-sex standard major axis regressions (SMA) of the numerator (i.e., the linear variables) on the denominator (i.e., the geometric mean) for each significantly different shape ratio indicated that most linear variables scaled with positive allometry in both males and females, and that for eight of the shape ratios, sex-related shape variation is associated with statistically similar sex-specific scaling relationships. Only the length of the scaphoid body and the height of the lunate triquetrum facet showed a significantly higher SMA slope in females compared with males. These findings indicate that the significant differences in the majority of the shape ratios are a function of subtle (i.e., not statistically significant) scaling differences between males and females. There are a number of potential developmental, functional, and evolutionary factors that may cause sex-related shape differences in the human carpus. The results highlight the potential for subtle differences in scaling to result in functionally significant differences in shape. Copyright © 2012 Wiley Periodicals, Inc.

Intraoperative optical biopsy for brain tumors using spectro-lifetime properties of intrinsic fluorophores

NASA Astrophysics Data System (ADS)

Vasefi, Fartash; Kittle, David S.; Nie, Zhaojun; Falcone, Christina; Patil, Chirag G.; Chu, Ray M.; Mamelak, Adam N.; Black, Keith L.; Butte, Pramod V.

2016-04-01

We have developed and tested a system for real-time intra-operative optical identification and classification of brain tissues using time-resolved fluorescence spectroscopy (TRFS). A supervised learning algorithm using linear discriminant analysis (LDA) employing selected intrinsic fluorescence decay temporal points in 6 spectral bands was employed to maximize statistical significance difference between training groups. The linear discriminant analysis on in vivo human tissues obtained by TRFS measurements (N = 35) were validated by histopathologic analysis and neuronavigation correlation to pre-operative MRI images. These results demonstrate that TRFS can differentiate between normal cortex, white matter and glioma.

On the thermopower and thermomagnetic properties of Er{sub x}Sn{sub 1–x}Se solid solutions

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

Huseynov, J. I., E-mail: cih-58@mail.ru; Murguzov, M. I.; Ismayilov, Sh. S.

2017-02-15

The Er{sub x}Sn{sub 1–x}Se system is characterized by a significant deviation of the temperature dependence of the differential thermopower from linearity at temperatures below room temperature and a change in the sign of the thermomagnetic coefficient. The deviation of the thermopower of Er{sub x}Sn{sub 1–x}Se samples in the nonequilibrium state from linearity is found to be caused mainly by the entrainment of charge carriers by phonons α{sub ph}. The statistical forces of electronic entrainment, A{sub ph}(ε), are estimated.

Statistically accurate low-order models for uncertainty quantification in turbulent dynamical systems.

PubMed

Sapsis, Themistoklis P; Majda, Andrew J

2013-08-20

A framework for low-order predictive statistical modeling and uncertainty quantification in turbulent dynamical systems is developed here. These reduced-order, modified quasilinear Gaussian (ROMQG) algorithms apply to turbulent dynamical systems in which there is significant linear instability or linear nonnormal dynamics in the unperturbed system and energy-conserving nonlinear interactions that transfer energy from the unstable modes to the stable modes where dissipation occurs, resulting in a statistical steady state; such turbulent dynamical systems are ubiquitous in geophysical and engineering turbulence. The ROMQG method involves constructing a low-order, nonlinear, dynamical system for the mean and covariance statistics in the reduced subspace that has the unperturbed statistics as a stable fixed point and optimally incorporates the indirect effect of non-Gaussian third-order statistics for the unperturbed system in a systematic calibration stage. This calibration procedure is achieved through information involving only the mean and covariance statistics for the unperturbed equilibrium. The performance of the ROMQG algorithm is assessed on two stringent test cases: the 40-mode Lorenz 96 model mimicking midlatitude atmospheric turbulence and two-layer baroclinic models for high-latitude ocean turbulence with over 125,000 degrees of freedom. In the Lorenz 96 model, the ROMQG algorithm with just a single mode captures the transient response to random or deterministic forcing. For the baroclinic ocean turbulence models, the inexpensive ROMQG algorithm with 252 modes, less than 0.2% of the total, captures the nonlinear response of the energy, the heat flux, and even the one-dimensional energy and heat flux spectra.

Text-Based Recall and Extra-Textual Generations Resulting from Simplified and Authentic Texts

ERIC Educational Resources Information Center

Crossley, Scott A.; McNamara, Danielle S.

2016-01-01

This study uses a moving windows self-paced reading task to assess text comprehension of beginning and intermediate-level simplified texts and authentic texts by L2 learners engaged in a text-retelling task. Linear mixed effects (LME) models revealed statistically significant main effects for reading proficiency and text level on the number of…

Deja Vu: Another Call for Replications of Research, Again.

ERIC Educational Resources Information Center

Newman, Isadore; McNeil, Keith; Fraas, John W.

Over the last few years, there has been evolution, although not a linear one, that has progressed from an emphasis on statistical significance to an emphasis on effect size to an emphasis on both of these concepts to what is believed to be a pragmatic emphasis on replicability. This paper presented two methods of estimating a study's replicability…

A comparative evaluation of Oratest with the microbiological method of assessing caries activity in children

PubMed Central

Sundaram, Meenakshi; Nayak, Ullal Anand; Ramalingam, Krishnakumar; Reddy, Venugopal; Rao, Arun Prasad; Mathian, Mahesh

2013-01-01

Aims: The aim of this study is to find out whether Oratest can be used as a diagnostic tool in assessing the caries activity by evaluating its relationship to the existing caries status and the salivary streptococcus mutans level. Materials and Methods: The study sample consists of 90 students divided into two groups. Group I (test group) and Group II (control group) consisting of 30 children for control group and 60 children for test group. The sampling of unstimulated saliva for the estimation of streptococcus mutans was done as per the method suggested by Kohler and Bratthall. The plates were then incubated. Rough surface colonies were identified as streptococcus mutans on a pre-determined area of the tip (approximately 1.5 cm2) were counted for each side of spatula pressed against mitis salivarius bacitracin agar using digital colony counter. The results were expressed in colony forming units (CFU). Oratest was carried out in the same patients after the collection of salivary sample for the microbiological method to evaluate the relationship between the two tests. Statistical Analysis Used: The tests used were ANOVA, Pearson Chi-square test, Pearson′s correlation analysis, Mann-Whitney U test and Student′s independent t-test. Results: In the control group and test group, when the streptococcus mutans count (CFU) and Oratest time (minutes) were correlated using Pearson′s correlation analysis, the streptococcus mutans counts was found to be in a statistically significant negative linear relationship with the Oratest time. When the caries status of the children, participated in the test group were correlated with mutans count (CFU) and Oratest time, caries status were found to be in a statistically significant positive linear relationship with streptococcus mutans count and in a significant negative linear relationship with Oratest time. Conclusions: The test proved to be a simple, inexpensive and rapid technique for assessing caries activity since a significant relationship exists clinically with caries status and microbiologically with the streptococcus mutans count of the individual. PMID:23946577

An open-access CMIP5 pattern library for temperature and precipitation: Description and methodology

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

Lynch, Cary D.; Hartin, Corinne A.; Bond-Lamberty, Benjamin

Pattern scaling is used to efficiently emulate general circulation models and explore uncertainty in climate projections under multiple forcing scenarios. Pattern scaling methods assume that local climate changes scale with a global mean temperature increase, allowing for spatial patterns to be generated for multiple models for any future emission scenario. For uncertainty quantification and probabilistic statistical analysis, a library of patterns with descriptive statistics for each file would be beneficial, but such a library does not presently exist. Of the possible techniques used to generate patterns, the two most prominent are the delta and least squared regression methods. We exploremore » the differences and statistical significance between patterns generated by each method and assess performance of the generated patterns across methods and scenarios. Differences in patterns across seasons between methods and epochs were largest in high latitudes (60-90°N/S). Bias and mean errors between modeled and pattern predicted output from the linear regression method were smaller than patterns generated by the delta method. Across scenarios, differences in the linear regression method patterns were more statistically significant, especially at high latitudes. We found that pattern generation methodologies were able to approximate the forced signal of change to within ≤ 0.5°C, but choice of pattern generation methodology for pattern scaling purposes should be informed by user goals and criteria. As a result, this paper describes our library of least squared regression patterns from all CMIP5 models for temperature and precipitation on an annual and sub-annual basis, along with the code used to generate these patterns.« less

An open-access CMIP5 pattern library for temperature and precipitation: Description and methodology

DOE PAGES

Lynch, Cary D.; Hartin, Corinne A.; Bond-Lamberty, Benjamin; ...

2017-05-15

Pattern scaling is used to efficiently emulate general circulation models and explore uncertainty in climate projections under multiple forcing scenarios. Pattern scaling methods assume that local climate changes scale with a global mean temperature increase, allowing for spatial patterns to be generated for multiple models for any future emission scenario. For uncertainty quantification and probabilistic statistical analysis, a library of patterns with descriptive statistics for each file would be beneficial, but such a library does not presently exist. Of the possible techniques used to generate patterns, the two most prominent are the delta and least squared regression methods. We exploremore » the differences and statistical significance between patterns generated by each method and assess performance of the generated patterns across methods and scenarios. Differences in patterns across seasons between methods and epochs were largest in high latitudes (60-90°N/S). Bias and mean errors between modeled and pattern predicted output from the linear regression method were smaller than patterns generated by the delta method. Across scenarios, differences in the linear regression method patterns were more statistically significant, especially at high latitudes. We found that pattern generation methodologies were able to approximate the forced signal of change to within ≤ 0.5°C, but choice of pattern generation methodology for pattern scaling purposes should be informed by user goals and criteria. As a result, this paper describes our library of least squared regression patterns from all CMIP5 models for temperature and precipitation on an annual and sub-annual basis, along with the code used to generate these patterns.« less

Analyzing longitudinal data with the linear mixed models procedure in SPSS.

PubMed

West, Brady T

2009-09-01

Many applied researchers analyzing longitudinal data share a common misconception: that specialized statistical software is necessary to fit hierarchical linear models (also known as linear mixed models [LMMs], or multilevel models) to longitudinal data sets. Although several specialized statistical software programs of high quality are available that allow researchers to fit these models to longitudinal data sets (e.g., HLM), rapid advances in general purpose statistical software packages have recently enabled analysts to fit these same models when using preferred packages that also enable other more common analyses. One of these general purpose statistical packages is SPSS, which includes a very flexible and powerful procedure for fitting LMMs to longitudinal data sets with continuous outcomes. This article aims to present readers with a practical discussion of how to analyze longitudinal data using the LMMs procedure in the SPSS statistical software package.

Nonlinear wave chaos: statistics of second harmonic fields.

PubMed

Zhou, Min; Ott, Edward; Antonsen, Thomas M; Anlage, Steven M

2017-10-01

Concepts from the field of wave chaos have been shown to successfully predict the statistical properties of linear electromagnetic fields in electrically large enclosures. The Random Coupling Model (RCM) describes these properties by incorporating both universal features described by Random Matrix Theory and the system-specific features of particular system realizations. In an effort to extend this approach to the nonlinear domain, we add an active nonlinear frequency-doubling circuit to an otherwise linear wave chaotic system, and we measure the statistical properties of the resulting second harmonic fields. We develop an RCM-based model of this system as two linear chaotic cavities coupled by means of a nonlinear transfer function. The harmonic field strengths are predicted to be the product of two statistical quantities and the nonlinearity characteristics. Statistical results from measurement-based calculation, RCM-based simulation, and direct experimental measurements are compared and show good agreement over many decades of power.

Improving validation methods for molecular diagnostics: application of Bland-Altman, Deming and simple linear regression analyses in assay comparison and evaluation for next-generation sequencing.

PubMed

Misyura, Maksym; Sukhai, Mahadeo A; Kulasignam, Vathany; Zhang, Tong; Kamel-Reid, Suzanne; Stockley, Tracy L

2018-02-01

A standard approach in test evaluation is to compare results of the assay in validation to results from previously validated methods. For quantitative molecular diagnostic assays, comparison of test values is often performed using simple linear regression and the coefficient of determination (R 2 ), using R 2 as the primary metric of assay agreement. However, the use of R 2 alone does not adequately quantify constant or proportional errors required for optimal test evaluation. More extensive statistical approaches, such as Bland-Altman and expanded interpretation of linear regression methods, can be used to more thoroughly compare data from quantitative molecular assays. We present the application of Bland-Altman and linear regression statistical methods to evaluate quantitative outputs from next-generation sequencing assays (NGS). NGS-derived data sets from assay validation experiments were used to demonstrate the utility of the statistical methods. Both Bland-Altman and linear regression were able to detect the presence and magnitude of constant and proportional error in quantitative values of NGS data. Deming linear regression was used in the context of assay comparison studies, while simple linear regression was used to analyse serial dilution data. Bland-Altman statistical approach was also adapted to quantify assay accuracy, including constant and proportional errors, and precision where theoretical and empirical values were known. The complementary application of the statistical methods described in this manuscript enables more extensive evaluation of performance characteristics of quantitative molecular assays, prior to implementation in the clinical molecular laboratory. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Correction of the significance level when attempting multiple transformations of an explanatory variable in generalized linear models

PubMed Central

2013-01-01

Background In statistical modeling, finding the most favorable coding for an exploratory quantitative variable involves many tests. This process involves multiple testing problems and requires the correction of the significance level. Methods For each coding, a test on the nullity of the coefficient associated with the new coded variable is computed. The selected coding corresponds to that associated with the largest statistical test (or equivalently the smallest pvalue). In the context of the Generalized Linear Model, Liquet and Commenges (Stat Probability Lett,71:33–38,2005) proposed an asymptotic correction of the significance level. This procedure, based on the score test, has been developed for dichotomous and Box-Cox transformations. In this paper, we suggest the use of resampling methods to estimate the significance level for categorical transformations with more than two levels and, by definition those that involve more than one parameter in the model. The categorical transformation is a more flexible way to explore the unknown shape of the effect between an explanatory and a dependent variable. Results The simulations we ran in this study showed good performances of the proposed methods. These methods were illustrated using the data from a study of the relationship between cholesterol and dementia. Conclusion The algorithms were implemented using R, and the associated CPMCGLM R package is available on the CRAN. PMID:23758852

Parametric and nonparametric Granger causality testing: Linkages between international stock markets

NASA Astrophysics Data System (ADS)

De Gooijer, Jan G.; Sivarajasingham, Selliah

2008-04-01

This study investigates long-term linear and nonlinear causal linkages among eleven stock markets, six industrialized markets and five emerging markets of South-East Asia. We cover the period 1987-2006, taking into account the on-set of the Asian financial crisis of 1997. We first apply a test for the presence of general nonlinearity in vector time series. Substantial differences exist between the pre- and post-crisis period in terms of the total number of significant nonlinear relationships. We then examine both periods, using a new nonparametric test for Granger noncausality and the conventional parametric Granger noncausality test. One major finding is that the Asian stock markets have become more internationally integrated after the Asian financial crisis. An exception is the Sri Lankan market with almost no significant long-term linear and nonlinear causal linkages with other markets. To ensure that any causality is strictly nonlinear in nature, we also examine the nonlinear causal relationships of VAR filtered residuals and VAR filtered squared residuals for the post-crisis sample. We find quite a few remaining significant bi- and uni-directional causal nonlinear relationships in these series. Finally, after filtering the VAR-residuals with GARCH-BEKK models, we show that the nonparametric test statistics are substantially smaller in both magnitude and statistical significance than those before filtering. This indicates that nonlinear causality can, to a large extent, be explained by simple volatility effects.

[Size of testes and epididymes in boys up to 17 years of life assessed by ultrasound method and method of external linear measurements].

PubMed

Osemlak, Paweł

2011-01-01

1. Determination of the size of testes and epididymes on the right and left side, in healthy boys in various age groups with use of non-invasive ultrasound examination method and the method of external linear measurements. 2. Determination of age, when intensive growth of testicular and epididymal size starts. 3. Determination whether there are statistically significant differences between the size of the right and the left testis, as well as between the right and left epididymis. 4. Evaluation of the ultrasound method and method of external linear measurements in their use for scientific investigations. 309 boys, aged from 1 day to 17 years of life, treated in the Clinical Department of Paediatric Surgery and Traumatology of the Medical University in Lublin from 2009 to 2010 due to diseases needed to be treated surgically, but not the scrotum, were examined in this study. No pathologies influencing the development of genital organs were found in these boys. Dimension of the testes was studied with ultrasound method and with method of external linear measurements. Dimension of epididymes was only examined with ultrasound method. In every age group the author calculated mean arithmetical values for: testiscular length, thickness, width and volume, as well as epididymal depth and basis. With consideration of standard deviation (X+/-1 SD) it was possible to define the range of dimension of healthy testes and epididymes and their change with age. Final dimensions of the right and left testis as well as of the right and left epididymis were compared. Dimensions of the testis on the same side of body acquired with the ultrasound method and acquired with the method of external linear measurements were compared. Statistical work-up with Wilcoxon test for two dependent groups was implemented. Ultrasound evaluation pointed to intensive 2.5-times increase in testicular length and width, and 2-times increase in testicular thickness in boys aged 10 to 17 years. Mean volume of neonatal testis is 0.35 ml. From 10th year of life, the testicular volume increases 10-times from 1.36 ml to 12.83 ml in 17th year of life. Depth of epididymis measured with ultrasound method is always greater than its basis. Both these dimensions increase quickly from the 10th year of life. Measurements done with the caliper on the average overestimate testicular length by 5.7 mm, its thickness by 2.9 mm and its width by 1.4 mm, comparing with ultrasound method. There were no statistically important differences between dimension of the right and left testis. Differences between dimension of the right and left epididymis are statistically significant. 1. Age is the main factor influencing testicular size in boys. 2. Intensive growth of testes starts in the 10th year of life, of epididymes in 12th year of life. 3. Testicular volume is the most precise description of its size. There are no statisticallysignificant differences between volume of the right and left testis. Differences between dimension, described by the depth and basis of the right and left epididymis are statistically significant. 4. Ultrasound method and method of external linear measurements with the caliper have similar diagnostic value in comparing the size of both testes. 5. Measurements of testicular size with ultrasound method have much greater value for detail evaluation than the method of external linear measurements with the caliper, which does not regard thickness of the skin and testicular coats, as well as the epididymal head which is often situated on the upper end of the testis.

Applicational possibilities of linear and non-linear (polynomial) regression and analysis of variance. III. Stability determination of pharmaceutical preparations: stability of diclofenac-sodium in Diclofen injections.

PubMed

Arambasić, M B; Jatić-Slavković, D

2004-05-01

This paper presents the application of the regression analysis program and the program for comparing linear regressions (modified method for one-way, analysis of variance), writtens in BASIC program language, for instance, determination of content of Diclofenac-Sodium (active ingredient in DIKLOFEN injections, ampules á 75 mg/3 ml). Stability testing of Diclofenac-Sodium was done by isothermic method of accelerated aging at 4 different temperatures (30 degrees, 40 degrees, 50 degrees and 60 degrees C) as a function of time (4 different duration of treatment: (0-155, 0-145, 0-74 and 0-44 days). The decrease in stability (decrease in the mean value of the content of Diclofenac-Sodium (in %), at different temperatures as a function of time, is possible to describe by, linear dependance. According to the value for regression equation values, the times are assessed in which the content of Diclofenac-Sodium (in %) will decrease by 10%, of the initial value. The times are follows at 30 degrees C 761.02 days, at 40 degrees C 397.26 days, at 50 degrees C 201.96 days and at 60 degrees C 58.85 days. The estimated times (in days) in which the mean value for Diclofenac-Sodium content (in %) will by 10% of the initial values, as a junction of time, are most suitably described by 3rd order parabola. Based on the parameter values which describe the 3rd order parabola, the time was estimated in which Diclofenac-Sodium content mean value (in %) will fall by 10% of the initial one at average ambient temperatures of 20 degrees C and 25 degrees C. The times are: 1409.47 days (20 degrees C) and 1042.39 days (25 degrees C). Based on the value for Fischer's coefficien (F), the comparison of trenf of Diclofenac-Sodium content (in %) shows that, under the influence of different temperatures as a function of time, among them, depending on temperature value, there is: statistically very significant difference (P < .05) at 50 degrees C and lower toward 60 degrees C, i.e. statistically probably significant difference (P > 0.01) at 40 degrees C and lower towards 50 degrees C and there is no statistically significance difference (P > 0.05) at 30 degrees C towards 40 degrees C.

Validation of the Omni Scale of Perceived Exertion in a sample of Spanish-speaking youth from the USA.

PubMed

Suminski, Richard R; Robertson, Robert J; Goss, Fredric L; Olvera, Norma

2008-08-01

Whether the translation of verbal descriptors from English to Spanish affects the validity of the Children's OMNI Scale of Perceived Exertion is not known, so the validity of a Spanish version of the OMNI was examined with 32 boys and 36 girls (9 to 12 years old) for whom Spanish was the primary language. Oxygen consumption, ventilation, respiratory rate, respiratory exchange ratio, heart rate, and ratings of perceived exertion for the overall body (RPE-O) were measured during an incremental treadmill test. All response values displayed significant linear increases across test stages. The linear regression analyses indicated RPE-O values were distributed as positive linear functions of oxygen consumption, ventilation, respiratory rate, respiratory exchange ratio, heart rate, and percent of maximal oxygen consumption. All regression models were statistically significant. The Spanish OMNI Scale is valid for estimating exercise effort during walking and running amongst Hispanic youth whose primary language is Spanish.

Managing Clustered Data Using Hierarchical Linear Modeling

ERIC Educational Resources Information Center

Warne, Russell T.; Li, Yan; McKyer, E. Lisako J.; Condie, Rachel; Diep, Cassandra S.; Murano, Peter S.

2012-01-01

Researchers in nutrition research often use cluster or multistage sampling to gather participants for their studies. These sampling methods often produce violations of the assumption of data independence that most traditional statistics share. Hierarchical linear modeling is a statistical method that can overcome violations of the independence…

Noise limitations in optical linear algebra processors.

PubMed

Batsell, S G; Jong, T L; Walkup, J F; Krile, T F

1990-05-10

A general statistical noise model is presented for optical linear algebra processors. A statistical analysis which includes device noise, the multiplication process, and the addition operation is undertaken. We focus on those processes which are architecturally independent. Finally, experimental results which verify the analytical predictions are also presented.

Effects of a Multi-Ingredient Energy Supplement on Cognitive Performance and Cerebral-Cortical Activation.

PubMed

Daou, Marcos; Sassi, Julia Montagner; Miller, Matthew W; Gonzalez, Adam M

2018-03-13

This study assessed whether a multi-ingredient energy supplement (MIES) could enhance cerebral-cortical activation and cognitive performance during an attention-switching task. Cerebral-cortical activation was recorded in 24 young adults (12 males, 12 females; 22.8 ± 3.8 yrs) via electroencephalography (EEG) both at rest and during the attention-switching task before (pretest) and 30 min after (posttest) consumption of a single serving of a MIES (MIES-1), two servings of a MIES (MIES-2), or a placebo (PL) in a double-blinded, randomized crossover experimental design. EEG upper-alpha power was assessed at rest and during the task, wherein d' (Z[hit rate]-Z[false alarm rate]) and median reaction time (RT) for correct responses to targets on attention-hold and attention-switch trials were analyzed. For both d' and RT, the Session (MIES-1, MIES-2, PL) × Time (pretest, posttest) interaction approached statistical significance (p = .07, η 2 p = 0.106). Exploring these interactions with linear contrasts, a significant linear effect of supplement dose on the linear effect of time was observed (ps ≤.034), suggesting the pretest-to-posttest improvement in sensitivity to task target stimuli (d') and RT increased as a function of supplement dose. With respect to upper-alpha power, the Session × Time interaction was significant (p < .001, η 2 p = 0.422). Exploring this interaction with linear contrasts, a significant linear effect of supplement dose on the linear effect of time was observed (p < .001), suggesting pretest-to-posttest increases in cerebral-cortical activation were a function of supplement dose. In conclusion, our findings suggest that MIES can increase cerebral-cortical activation and RT during task performance while increasing sensitivity to target stimuli in a dose-dependent manner.

Functional integration changes in regional brain glucose metabolism from childhood to adulthood.

PubMed

Trotta, Nicola; Archambaud, Frédérique; Goldman, Serge; Baete, Kristof; Van Laere, Koen; Wens, Vincent; Van Bogaert, Patrick; Chiron, Catherine; De Tiège, Xavier

2016-08-01

The aim of this study was to investigate the age-related changes in resting-state neurometabolic connectivity from childhood to adulthood (6-50 years old). Fifty-four healthy adult subjects and twenty-three pseudo-healthy children underwent [(18) F]-fluorodeoxyglucose positron emission tomography at rest. Using statistical parametric mapping (SPM8), age and age squared were first used as covariate of interest to identify linear and non-linear age effects on the regional distribution of glucose metabolism throughout the brain. Then, by selecting voxels of interest (VOI) within the regions showing significant age-related metabolic changes, a psychophysiological interaction (PPI) analysis was used to search for age-induced changes in the contribution of VOIs to the metabolic activity in other brain areas. Significant linear or non-linear age-related changes in regional glucose metabolism were found in prefrontal cortices (DMPFC/ACC), cerebellar lobules, and thalamo-hippocampal areas bilaterally. Decreases were found in the contribution of thalamic, hippocampal, and cerebellar regions to DMPFC/ACC metabolic activity as well as in the contribution of hippocampi to preSMA and right IFG metabolic activities. Increases were found in the contribution of the right hippocampus to insular cortex and of the cerebellar lobule IX to superior parietal cortex metabolic activities. This study evidences significant linear or non-linear age-related changes in regional glucose metabolism of mesial prefrontal, thalamic, mesiotemporal, and cerebellar areas, associated with significant modifications in neurometabolic connectivity involving fronto-thalamic, fronto-hippocampal, and fronto-cerebellar networks. These changes in functional brain integration likely represent a metabolic correlate of age-dependent effects on sensory, motor, and high-level cognitive functional networks. Hum Brain Mapp 37:3017-3030, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

The trend of changes in the evaluation scores of faculty members from administrators' and students' perspectives at the medical school over 10 years.

PubMed

Yamani, Nikoo; Changiz, Tahereh; Feizi, Awat; Kamali, Farahnaz

2018-01-01

To assess the trend of changes in the evaluation scores of faculty members and discrepancy between administrators' and students' perspectives in a medical school from 2006 to 2015. This repeated cross-sectional study was conducted on the 10-year evaluation scores of all faculty members of a medical school (n=579) in an urban area of Iran. Data on evaluation scores given by students and administrators and the total of these scores were evaluated. Data were analyzed using descriptive and inferential statistics including linear mixed effect models for repeated measures via the SPSS software. There were statistically significant differences between the students' and administrators' perspectives over time ( p <0.001). The mean of the total evaluation scores also showed a statistically significant change over time ( p <0.001). Furthermore, the mean of changes over time in the total evaluation score between different departments was statistically significant ( p <0.001). The trend of changes in the student's evaluations was clear and positive, but the trend of administrators' evaluation was unclear. Since the evaluation of faculty members is affected by many other factors, there is a need for more future studies.

Inter-Ethnic/Racial Facial Variations: A Systematic Review and Bayesian Meta-Analysis of Photogrammetric Studies

PubMed Central

Wen, Yi Feng; Wong, Hai Ming; Lin, Ruitao; Yin, Guosheng; McGrath, Colman

2015-01-01

Background Numerous facial photogrammetric studies have been published around the world. We aimed to critically review these studies so as to establish population norms for various angular and linear facial measurements; and to determine inter-ethnic/racial facial variations. Methods and Findings A comprehensive and systematic search of PubMed, ISI Web of Science, Embase, and Scopus was conducted to identify facial photogrammetric studies published before December, 2014. Subjects of eligible studies were either Africans, Asians or Caucasians. A Bayesian hierarchical random effects model was developed to estimate posterior means and 95% credible intervals (CrI) for each measurement by ethnicity/race. Linear contrasts were constructed to explore inter-ethnic/racial facial variations. We identified 38 eligible studies reporting 11 angular and 18 linear facial measurements. Risk of bias of the studies ranged from 0.06 to 0.66. At the significance level of 0.05, African males were found to have smaller nasofrontal angle (posterior mean difference: 8.1°, 95% CrI: 2.2°–13.5°) compared to Caucasian males and larger nasofacial angle (7.4°, 0.1°–13.2°) compared to Asian males. Nasolabial angle was more obtuse in Caucasian females than in African (17.4°, 0.2°–35.3°) and Asian (9.1°, 0.4°–17.3°) females. Additional inter-ethnic/racial variations were revealed when the level of statistical significance was set at 0.10. Conclusions A comprehensive database for angular and linear facial measurements was established from existing studies using the statistical model and inter-ethnic/racial variations of facial features were observed. The results have implications for clinical practice and highlight the need and value for high quality photogrammetric studies. PMID:26247212

A Novel Weighted Kernel PCA-Based Method for Optimization and Uncertainty Quantification

NASA Astrophysics Data System (ADS)

Thimmisetty, C.; Talbot, C.; Chen, X.; Tong, C. H.

2016-12-01

It has been demonstrated that machine learning methods can be successfully applied to uncertainty quantification for geophysical systems through the use of the adjoint method coupled with kernel PCA-based optimization. In addition, it has been shown through weighted linear PCA how optimization with respect to both observation weights and feature space control variables can accelerate convergence of such methods. Linear machine learning methods, however, are inherently limited in their ability to represent features of non-Gaussian stochastic random fields, as they are based on only the first two statistical moments of the original data. Nonlinear spatial relationships and multipoint statistics leading to the tortuosity characteristic of channelized media, for example, are captured only to a limited extent by linear PCA. With the aim of coupling the kernel-based and weighted methods discussed, we present a novel mathematical formulation of kernel PCA, Weighted Kernel Principal Component Analysis (WKPCA), that both captures nonlinear relationships and incorporates the attribution of significance levels to different realizations of the stochastic random field of interest. We also demonstrate how new instantiations retaining defining characteristics of the random field can be generated using Bayesian methods. In particular, we present a novel WKPCA-based optimization method that minimizes a given objective function with respect to both feature space random variables and observation weights through which optimal snapshot significance levels and optimal features are learned. We showcase how WKPCA can be applied to nonlinear optimal control problems involving channelized media, and in particular demonstrate an application of the method to learning the spatial distribution of material parameter values in the context of linear elasticity, and discuss further extensions of the method to stochastic inversion.

Inter-Ethnic/Racial Facial Variations: A Systematic Review and Bayesian Meta-Analysis of Photogrammetric Studies.

PubMed

Wen, Yi Feng; Wong, Hai Ming; Lin, Ruitao; Yin, Guosheng; McGrath, Colman

2015-01-01

Numerous facial photogrammetric studies have been published around the world. We aimed to critically review these studies so as to establish population norms for various angular and linear facial measurements; and to determine inter-ethnic/racial facial variations. A comprehensive and systematic search of PubMed, ISI Web of Science, Embase, and Scopus was conducted to identify facial photogrammetric studies published before December, 2014. Subjects of eligible studies were either Africans, Asians or Caucasians. A Bayesian hierarchical random effects model was developed to estimate posterior means and 95% credible intervals (CrI) for each measurement by ethnicity/race. Linear contrasts were constructed to explore inter-ethnic/racial facial variations. We identified 38 eligible studies reporting 11 angular and 18 linear facial measurements. Risk of bias of the studies ranged from 0.06 to 0.66. At the significance level of 0.05, African males were found to have smaller nasofrontal angle (posterior mean difference: 8.1°, 95% CrI: 2.2°-13.5°) compared to Caucasian males and larger nasofacial angle (7.4°, 0.1°-13.2°) compared to Asian males. Nasolabial angle was more obtuse in Caucasian females than in African (17.4°, 0.2°-35.3°) and Asian (9.1°, 0.4°-17.3°) females. Additional inter-ethnic/racial variations were revealed when the level of statistical significance was set at 0.10. A comprehensive database for angular and linear facial measurements was established from existing studies using the statistical model and inter-ethnic/racial variations of facial features were observed. The results have implications for clinical practice and highlight the need and value for high quality photogrammetric studies.

Use of Statistical Analysis of Acoustic Emission Data on Carbon-Epoxy COPV Materials-of-Construction for Enhanced Felicity Ratio Onset Determination

NASA Technical Reports Server (NTRS)

Abraham, Arick Reed A.; Johnson, Kenneth L.; Nichols, Charles T.; Saulsberry, Regor L.; Waller, Jess M.

2012-01-01

Broadband modal acoustic emission (AE) data were acquired during intermittent load hold tensile test profiles on Toray T1000G carbon fiber-reinforced epoxy (C/Ep) single tow specimens. A novel trend seeking statistical method to determine the onset of significant AE was developed, resulting in more linear decreases in the Felicity ratio (FR) with load, potentially leading to more accurate failure prediction. The method developed uses an exponentially weighted moving average (EWMA) control chart. Comparison of the EWMA with previously used FR onset methods, namely the discrete (n), mean (n (raised bar)), normalized (n%) and normalized mean (n(raised bar)%) methods, revealed the EWMA method yields more consistently linear FR versus load relationships between specimens. Other findings include a correlation between AE data richness and FR linearity based on the FR methods discussed in this paper, and evidence of premature failure at lower than expected loads. Application of the EWMA method should be extended to other composite materials and, eventually, composite components such as composite overwrapped pressure vessels. Furthermore, future experiments should attempt to uncover the factors responsible for infant mortality in C/Ep strands.

Respiratory Disease Related Mortality and Morbidity on an Island of Greece Exposed to Perlite and Bentonite Mining Dust

PubMed Central

Sampatakakis, Stefanos; Linos, Athena; Papadimitriou, Eleni; Petralias, Athanasios; Dalma, Archontoula; Papasaranti, Eirini Saranti; Christoforidou, Eleni; Stoltidis, Melina

2013-01-01

A morbidity and mortality study took place, focused on Milos Island, where perlite and bentonite mining sites are located. Official data concerning number and cause of deaths, regarding specific respiratory diseases and the total of respiratory diseases, for both Milos Island and the Cyclades Prefecture were used. Standardized Mortality Ratios (SMRs) were computed, adjusted specifically for age, gender and calendar year. Tests of linear trend were performed. By means of a predefined questionnaire, the morbidity rates of specific respiratory diseases in Milos, were compared to those of the municipality of Oinofita, an industrial region. Chi-square analysis was used and the confounding factors of age, gender and smoking were taken into account, by estimating binary logistic regression models. The SMRs for Pneumonia and Chronic Obstructive Pulmonary Disease (COPD) were found elevated for both genders, although they did not reach statistical significance. For the total of respiratory diseases, a statistically significant SMR was identified regarding the decade 1989–1998. The morbidity study revealed elevated and statistically significant Odds Ratios (ORs), associated with allergic rhinitis, pneumonia, COPD and bronchiectasis. An elevated OR was also identified for asthma. After controlling for age, gender and smoking, the ORs were statistically significant and towards the same direction. PMID:24129114

Respiratory disease related mortality and morbidity on an island of Greece exposed to perlite and bentonite mining dust.

PubMed

Sampatakakis, Stefanos; Linos, Athena; Papadimitriou, Eleni; Petralias, Athanasios; Dalma, Archontoula; Papasaranti, Eirini Saranti; Christoforidou, Eleni; Stoltidis, Melina

2013-10-14

A morbidity and mortality study took place, focused on Milos Island, where perlite and bentonite mining sites are located. Official data concerning number and cause of deaths, regarding specific respiratory diseases and the total of respiratory diseases, for both Milos Island and the Cyclades Prefecture were used. Standardized Mortality Ratios (SMRs) were computed, adjusted specifically for age, gender and calendar year. Tests of linear trend were performed. By means of a predefined questionnaire, the morbidity rates of specific respiratory diseases in Milos, were compared to those of the municipality of Oinofita, an industrial region. Chi-square analysis was used and the confounding factors of age, gender and smoking were taken into account, by estimating binary logistic regression models. The SMRs for Pneumonia and Chronic Obstructive Pulmonary Disease (COPD) were found elevated for both genders, although they did not reach statistical significance. For the total of respiratory diseases, a statistically significant SMR was identified regarding the decade 1989-1998. The morbidity study revealed elevated and statistically significant Odds Ratios (ORs), associated with allergic rhinitis, pneumonia, COPD and bronchiectasis. An elevated OR was also identified for asthma. After controlling for age, gender and smoking, the ORs were statistically significant and towards the same direction.

Reversed inverse regression for the univariate linear calibration and its statistical properties derived using a new methodology

NASA Astrophysics Data System (ADS)

Kang, Pilsang; Koo, Changhoi; Roh, Hokyu

2017-11-01

Since simple linear regression theory was established at the beginning of the 1900s, it has been used in a variety of fields. Unfortunately, it cannot be used directly for calibration. In practical calibrations, the observed measurements (the inputs) are subject to errors, and hence they vary, thus violating the assumption that the inputs are fixed. Therefore, in the case of calibration, the regression line fitted using the method of least squares is not consistent with the statistical properties of simple linear regression as already established based on this assumption. To resolve this problem, "classical regression" and "inverse regression" have been proposed. However, they do not completely resolve the problem. As a fundamental solution, we introduce "reversed inverse regression" along with a new methodology for deriving its statistical properties. In this study, the statistical properties of this regression are derived using the "error propagation rule" and the "method of simultaneous error equations" and are compared with those of the existing regression approaches. The accuracy of the statistical properties thus derived is investigated in a simulation study. We conclude that the newly proposed regression and methodology constitute the complete regression approach for univariate linear calibrations.

The swan-song phenomenon: last-works effects for 172 classical composers.

PubMed

Simonton, D K

1989-03-01

Creative individuals approaching their final years of life may undergo a transformation in outlook that is reflected in their last works. This hypothesized effect was quantitatively assessed for an extensive sample of 1,919 works by 172 classical composers. The works were independently gauged on seven aesthetic attributes (melodic originality, melodic variation, repertoire popularity, aesthetic significance, listener accessibility, performance duration, and thematic size), and potential last-works effects were operationally defined two separate ways (linearly and exponentially). Statistical controls were introduced for both longitudinal changes (linear, quadratic, and cubic age functions) and individual differences (eminence and lifetime productivity). Hierarchical regression analyses indicated that composers' swan songs tend to score lower in melodic originality and performance duration but higher in repertoire popularity and aesthetic significance. These last-works effects survive control for total compositional output, eminence, and most significantly, the composer's age when the last works were created.

Modifying effect of dynamic space flight factors on radiation damage of air-dry seeds of Crepis capillaris (L) Wallr.

PubMed

Vaulina, E N; Kostina, L N

1975-01-01

The influence of dynamic factors (vibration and linear acceleration) on the rate of chromosome aberrations in Crepis capillaris was studied. The vibrational process simulated was similar in its characteristics to that occurring at the launch of spaceships. In combination with linear acceleration it caused a statistically significant increase in the rate of chromosome aberrations compared with the control (R=7.70). The dynamic factors modified the effect of radiation damage induced by acute gamma-irradiation (3 krad). Pre-radiation treatment with vibration and acceleration on the seeds caused a significant decrease (R=10.23) of the effect of radiation damage, from 15.57% to 9.74%. The post-radiation treatment of C. capillaris seeds with the dynamic factors did not change the rate of chromosome aberrations significantly (from 15.57% to 15.90%).

Perception of linear acceleration in weightlessness

NASA Technical Reports Server (NTRS)

Arrott, Anthony P.; Young, Laurence R.; Merfeld, Daniel M.

1991-01-01

Tests of the perception and use of linear acceleration sensory information were performed on the science crews of the Spacelab 1 (SL-1) and D-1 missions using linear 'sleds' in-flight (D-1) and pre-post flight. The time delay between the acceleration step stimulus and the subjective response was consistently reduced during weightlessness, but was neither statistically significant nor of functional importance. Increased variability of responses when going from one environment to the other was apparent from measurements on the first day of the mission and in the first days post-flight. Subjective reports of perceived motion during sinusoidal oscillation in weightlessness were qualitatively similar to reports on earth. In a closed-loop motion nulling task, enhanced performance was observed post-flight in all crewmembers tested in the Y or Z axes.

Perception of linear acceleration in weightlessness

NASA Technical Reports Server (NTRS)

Arrott, A. P.; Young, L. R.; Merfeld, D. M.

1990-01-01

Tests of the perception and use of linear acceleration sensory information were performed on the science crews of the Spacelab 1 (SL-1) and D-1 missions using linear "sleds" in-flight (D-1) and pre-post flight. The time delay between the acceleration step stimulus and the subjective response was consistently reduced during weightlessness, but was neither statistically significant nor of functional importance. Increased variability of responses when going from one environment to the other was apparent from measurements on the first day of the mission and in the first days post-flight. Subjective reports of perceived motion during sinusoidal oscillation in weightlessness were qualitatively similar to reports on earth. In a closed-loop motion nulling task, enhanced performance was observed post-flight in all crewmembers tested in the Y or Z axes.

Impact of isotropic constitutive descriptions on the predicted peak wall stress in abdominal aortic aneurysms.

PubMed

Man, V; Polzer, S; Gasser, T C; Novotny, T; Bursa, J

2018-03-01

Biomechanics-based assessment of Abdominal Aortic Aneurysm (AAA) rupture risk has gained considerable scientific and clinical momentum. However, computation of peak wall stress (PWS) using state-of-the-art finite element models is time demanding. This study investigates which features of the constitutive description of AAA wall are decisive for achieving acceptable stress predictions in it. Influence of five different isotropic constitutive descriptions of AAA wall is tested; models reflect realistic non-linear, artificially stiff non-linear, or artificially stiff pseudo-linear constitutive descriptions of AAA wall. Influence of the AAA wall model is tested on idealized (n=4) and patient-specific (n=16) AAA geometries. Wall stress computations consider a (hypothetical) load-free configuration and include residual stresses homogenizing the stresses across the wall. Wall stress differences amongst the different descriptions were statistically analyzed. When the qualitatively similar non-linear response of the AAA wall with low initial stiffness and subsequent strain stiffening was taken into consideration, wall stress (and PWS) predictions did not change significantly. Keeping this non-linear feature when using an artificially stiff wall can save up to 30% of the computational time, without significant change in PWS. In contrast, a stiff pseudo-linear elastic model may underestimate the PWS and is not reliable for AAA wall stress computations. Copyright © 2018 IPEM. Published by Elsevier Ltd. All rights reserved.

Influence of nonlinear effects on statistical properties of the radiation from SASE FEL

NASA Astrophysics Data System (ADS)

Saldin, E. L.; Schneidmiller, E. A.; Yurkov, M. V.

1998-02-01

The paper presents analysis of statistical properties of the radiation from self-amplified spontaneous emission (SASE) free-electron laser operating in nonlinear mode. The present approach allows one to calculate the following statistical properties of the SASE FEL radiation: time and spectral field correlation functions, distribution of the fluctuations of the instantaneous radiation power, distribution of the energy in the electron bunch, distribution of the radiation energy after monochromator installed at the FEL amplifier exit and the radiation spectrum. It has been observed that the statistics of the instantaneous radiation power from SASE FEL operating in the nonlinear regime changes significantly with respect to the linear regime. All numerical results presented in the paper have been calculated for the 70 nm SASE FEL at the TESLA Test Facility under construction at DESY.

A Statistical Approach to Passive Target Tracking.

DTIC Science & Technology

1981-04-01

a fixed heading of 90 degrees. For 7F. A. Graybill , An Introduction to Linear Statistical Models , Vol. 1, New York: John Wiley&-Sons -Inc. (1961). 13...likelihood estimators. 12 NCSC TM 311-81 The adjustment for a changing error variance is easy using the linear model approach; i.e., use weighted

Validity of linear measurements of the jaws using ultralow-dose MDCT and the iterative techniques of ASIR and MBIR.

PubMed

Al-Ekrish, Asma'a A; Al-Shawaf, Reema; Schullian, Peter; Al-Sadhan, Ra'ed; Hörmann, Romed; Widmann, Gerlig

2016-10-01

To assess the comparability of linear measurements of dental implant sites recorded from multidetector computed tomography (MDCT) images obtained using standard-dose filtered backprojection (FBP) technique with those from various ultralow doses combined with FBP, adaptive statistical iterative reconstruction (ASIR), and model-based iterative reconstruction (MBIR) techniques. The results of the study may contribute to MDCT dose optimization for dental implant site imaging. MDCT scans of two cadavers were acquired using a standard reference protocol and four ultralow-dose test protocols (TP). The volume CT dose index of the different dose protocols ranged from a maximum of 30.48-36.71 mGy to a minimum of 0.44-0.53 mGy. All scans were reconstructed using FBP, ASIR-50, ASIR-100, and MBIR, and either a bone or standard reconstruction kernel. Linear measurements were recorded from standardized images of the jaws by two examiners. Intra- and inter-examiner reliability of the measurements were analyzed using Cronbach's alpha and inter-item correlation. Agreement between the measurements obtained with the reference-dose/FBP protocol and each of the test protocols was determined with Bland-Altman plots and linear regression. Statistical significance was set at a P-value of 0.05. No systematic variation was found between the linear measurements obtained with the reference protocol and the other imaging protocols. The only exceptions were TP3/ASIR-50 (bone kernel) and TP4/ASIR-100 (bone and standard kernels). The mean measurement differences between these three protocols and the reference protocol were within ±0.1 mm, with the 95 % confidence interval limits being within the range of ±1.15 mm. A nearly 97.5 % reduction in dose did not significantly affect the height and width measurements of edentulous jaws regardless of the reconstruction algorithm used.

A Model Comparison for Count Data with a Positively Skewed Distribution with an Application to the Number of University Mathematics Courses Completed

ERIC Educational Resources Information Center

Liou, Pey-Yan

2009-01-01

The current study examines three regression models: OLS (ordinary least square) linear regression, Poisson regression, and negative binomial regression for analyzing count data. Simulation results show that the OLS regression model performed better than the others, since it did not produce more false statistically significant relationships than…

Correlation and simple linear regression.

PubMed

Zou, Kelly H; Tuncali, Kemal; Silverman, Stuart G

2003-06-01

In this tutorial article, the concepts of correlation and regression are reviewed and demonstrated. The authors review and compare two correlation coefficients, the Pearson correlation coefficient and the Spearman rho, for measuring linear and nonlinear relationships between two continuous variables. In the case of measuring the linear relationship between a predictor and an outcome variable, simple linear regression analysis is conducted. These statistical concepts are illustrated by using a data set from published literature to assess a computed tomography-guided interventional technique. These statistical methods are important for exploring the relationships between variables and can be applied to many radiologic studies.

Role of sufficient statistics in stochastic thermodynamics and its implication to sensory adaptation

NASA Astrophysics Data System (ADS)

Matsumoto, Takumi; Sagawa, Takahiro

2018-04-01

A sufficient statistic is a significant concept in statistics, which means a probability variable that has sufficient information required for an inference task. We investigate the roles of sufficient statistics and related quantities in stochastic thermodynamics. Specifically, we prove that for general continuous-time bipartite networks, the existence of a sufficient statistic implies that an informational quantity called the sensory capacity takes the maximum. Since the maximal sensory capacity imposes a constraint that the energetic efficiency cannot exceed one-half, our result implies that the existence of a sufficient statistic is inevitably accompanied by energetic dissipation. We also show that, in a particular parameter region of linear Langevin systems there exists the optimal noise intensity at which the sensory capacity, the information-thermodynamic efficiency, and the total entropy production are optimized at the same time. We apply our general result to a model of sensory adaptation of E. coli and find that the sensory capacity is nearly maximal with experimentally realistic parameters.

Identification of trends in rainfall, rainy days and 24 h maximum rainfall over subtropical Assam in Northeast India

NASA Astrophysics Data System (ADS)

Jhajharia, Deepak; Yadav, Brijesh K.; Maske, Sunil; Chattopadhyay, Surajit; Kar, Anil K.

2012-01-01

Trends in rainfall, rainy days and 24 h maximum rainfall are investigated using the Mann-Kendall non-parametric test at twenty-four sites of subtropical Assam located in the northeastern region of India. The trends are statistically confirmed by both the parametric and non-parametric methods and the magnitudes of significant trends are obtained through the linear regression test. In Assam, the average monsoon rainfall (rainy days) during the monsoon months of June to September is about 1606 mm (70), which accounts for about 70% (64%) of the annual rainfall (rainy days). On monthly time scales, sixteen and seventeen sites (twenty-one sites each) witnessed decreasing trends in the total rainfall (rainy days), out of which one and three trends (seven trends each) were found to be statistically significant in June and July, respectively. On the other hand, seventeen sites witnessed increasing trends in rainfall in the month of September, but none were statistically significant. In December (February), eighteen (twenty-two) sites witnessed decreasing (increasing) trends in total rainfall, out of which five (three) trends were statistically significant. For the rainy days during the months of November to January, twenty-two or more sites witnessed decreasing trends in Assam, but for nine (November), twelve (January) and eighteen (December) sites, these trends were statistically significant. These observed changes in rainfall, although most time series are not convincing as they show predominantly no significance, along with the well-reported climatic warming in monsoon and post-monsoon seasons may have implications for human health and water resources management over bio-diversity rich Northeast India.

The Relationship Between Surface Curvature and Abdominal Aortic Aneurysm Wall Stress.

PubMed

de Galarreta, Sergio Ruiz; Cazón, Aitor; Antón, Raúl; Finol, Ender A

2017-08-01

The maximum diameter (MD) criterion is the most important factor when predicting risk of rupture of abdominal aortic aneurysms (AAAs). An elevated wall stress has also been linked to a high risk of aneurysm rupture, yet is an uncommon clinical practice to compute AAA wall stress. The purpose of this study is to assess whether other characteristics of the AAA geometry are statistically correlated with wall stress. Using in-house segmentation and meshing algorithms, 30 patient-specific AAA models were generated for finite element analysis (FEA). These models were subsequently used to estimate wall stress and maximum diameter and to evaluate the spatial distributions of wall thickness, cross-sectional diameter, mean curvature, and Gaussian curvature. Data analysis consisted of statistical correlations of the aforementioned geometry metrics with wall stress for the 30 AAA inner and outer wall surfaces. In addition, a linear regression analysis was performed with all the AAA wall surfaces to quantify the relationship of the geometric indices with wall stress. These analyses indicated that while all the geometry metrics have statistically significant correlations with wall stress, the local mean curvature (LMC) exhibits the highest average Pearson's correlation coefficient for both inner and outer wall surfaces. The linear regression analysis revealed coefficients of determination for the outer and inner wall surfaces of 0.712 and 0.516, respectively, with LMC having the largest effect on the linear regression equation with wall stress. This work underscores the importance of evaluating AAA mean wall curvature as a potential surrogate for wall stress.

Experimental and environmental factors affect spurious detection of ecological thresholds

USGS Publications Warehouse

Daily, Jonathan P.; Hitt, Nathaniel P.; Smith, David; Snyder, Craig D.

2012-01-01

Threshold detection methods are increasingly popular for assessing nonlinear responses to environmental change, but their statistical performance remains poorly understood. We simulated linear change in stream benthic macroinvertebrate communities and evaluated the performance of commonly used threshold detection methods based on model fitting (piecewise quantile regression [PQR]), data partitioning (nonparametric change point analysis [NCPA]), and a hybrid approach (significant zero crossings [SiZer]). We demonstrated that false detection of ecological thresholds (type I errors) and inferences on threshold locations are influenced by sample size, rate of linear change, and frequency of observations across the environmental gradient (i.e., sample-environment distribution, SED). However, the relative importance of these factors varied among statistical methods and between inference types. False detection rates were influenced primarily by user-selected parameters for PQR (τ) and SiZer (bandwidth) and secondarily by sample size (for PQR) and SED (for SiZer). In contrast, the location of reported thresholds was influenced primarily by SED. Bootstrapped confidence intervals for NCPA threshold locations revealed strong correspondence to SED. We conclude that the choice of statistical methods for threshold detection should be matched to experimental and environmental constraints to minimize false detection rates and avoid spurious inferences regarding threshold location.

Transmission of linear regression patterns between time series: From relationship in time series to complex networks

NASA Astrophysics Data System (ADS)

Gao, Xiangyun; An, Haizhong; Fang, Wei; Huang, Xuan; Li, Huajiao; Zhong, Weiqiong; Ding, Yinghui

2014-07-01

The linear regression parameters between two time series can be different under different lengths of observation period. If we study the whole period by the sliding window of a short period, the change of the linear regression parameters is a process of dynamic transmission over time. We tackle fundamental research that presents a simple and efficient computational scheme: a linear regression patterns transmission algorithm, which transforms linear regression patterns into directed and weighted networks. The linear regression patterns (nodes) are defined by the combination of intervals of the linear regression parameters and the results of the significance testing under different sizes of the sliding window. The transmissions between adjacent patterns are defined as edges, and the weights of the edges are the frequency of the transmissions. The major patterns, the distance, and the medium in the process of the transmission can be captured. The statistical results of weighted out-degree and betweenness centrality are mapped on timelines, which shows the features of the distribution of the results. Many measurements in different areas that involve two related time series variables could take advantage of this algorithm to characterize the dynamic relationships between the time series from a new perspective.

Transmission of linear regression patterns between time series: from relationship in time series to complex networks.

PubMed

Gao, Xiangyun; An, Haizhong; Fang, Wei; Huang, Xuan; Li, Huajiao; Zhong, Weiqiong; Ding, Yinghui

2014-07-01

The linear regression parameters between two time series can be different under different lengths of observation period. If we study the whole period by the sliding window of a short period, the change of the linear regression parameters is a process of dynamic transmission over time. We tackle fundamental research that presents a simple and efficient computational scheme: a linear regression patterns transmission algorithm, which transforms linear regression patterns into directed and weighted networks. The linear regression patterns (nodes) are defined by the combination of intervals of the linear regression parameters and the results of the significance testing under different sizes of the sliding window. The transmissions between adjacent patterns are defined as edges, and the weights of the edges are the frequency of the transmissions. The major patterns, the distance, and the medium in the process of the transmission can be captured. The statistical results of weighted out-degree and betweenness centrality are mapped on timelines, which shows the features of the distribution of the results. Many measurements in different areas that involve two related time series variables could take advantage of this algorithm to characterize the dynamic relationships between the time series from a new perspective.

Linear and nonlinear regression techniques for simultaneous and proportional myoelectric control.

PubMed

Hahne, J M; Biessmann, F; Jiang, N; Rehbaum, H; Farina, D; Meinecke, F C; Muller, K-R; Parra, L C

2014-03-01

In recent years the number of active controllable joints in electrically powered hand-prostheses has increased significantly. However, the control strategies for these devices in current clinical use are inadequate as they require separate and sequential control of each degree-of-freedom (DoF). In this study we systematically compare linear and nonlinear regression techniques for an independent, simultaneous and proportional myoelectric control of wrist movements with two DoF. These techniques include linear regression, mixture of linear experts (ME), multilayer-perceptron, and kernel ridge regression (KRR). They are investigated offline with electro-myographic signals acquired from ten able-bodied subjects and one person with congenital upper limb deficiency. The control accuracy is reported as a function of the number of electrodes and the amount and diversity of training data providing guidance for the requirements in clinical practice. The results showed that KRR, a nonparametric statistical learning method, outperformed the other methods. However, simple transformations in the feature space could linearize the problem, so that linear models could achieve similar performance as KRR at much lower computational costs. Especially ME, a physiologically inspired extension of linear regression represents a promising candidate for the next generation of prosthetic devices.

The three-dimensional structure of cumulus clouds over the ocean. 1: Structural analysis

NASA Technical Reports Server (NTRS)

Kuo, Kwo-Sen; Welch, Ronald M.; Weger, Ronald C.; Engelstad, Mark A.; Sengupta, S. K.

1993-01-01

Thermal channel (channel 6, 10.4-12.5 micrometers) images of five Landsat thematic mapper cumulus scenes over the ocean are examined. These images are thresholded using the standard International Satellite Cloud Climatology Project (ISCCP) thermal threshold algorithm. The individual clouds in the cloud fields are segmented to obtain their structural statistics which include size distribution, orientation angle, horizontal aspect ratio, and perimeter-to-area (PtA) relationship. The cloud size distributions exhibit a double power law with the smaller clouds having a smaller absolute exponent. The cloud orientation angles, horizontal aspect ratios, and PtA exponents are found in good agreement with earlier studies. A technique also is developed to recognize individual cells within a cloud so that statistics of cloud cellular structure can be obtained. Cell structural statistics are computed for each cloud. Unicellular clouds are generally smaller (less than or equal to 1 km) and have smaller PtA exponents, while multicellular clouds are larger (greater than or equal to 1 km) and have larger PtA exponents. Cell structural statistics are similar to those of the smaller clouds. When each cell is approximated as a quadric surface using a linear least squares fit, most cells have the shape of a hyperboloid of one sheet, but about 15% of the cells are best modeled by a hyperboloid of two sheets. Less than 1% of the clouds are ellipsoidal. The number of cells in a cloud increases slightly faster than linearly with increasing cloud size. The mean nearest neighbor distance between cells in a cloud, however, appears to increase linearly with increasing cloud size and to reach a maximum when the cloud effective diameter is about 10 km; then it decreases with increasing cloud size. Sensitivity studies of threshold and lapse rate show that neither has a significant impact upon the results. A goodness-of-fit ratio is used to provide a quantitative measure of the individual cloud results. Significantly improved results are obtained after applying a smoothing operator, suggesting the eliminating subresolution scale variations with higher spatial resolution may yield even better shape analyses.

The association between clinical parameters and glaucoma-specific quality of life in Chinese primary open-angle glaucoma patients.

PubMed

Lee, Jacky W Y; Chan, Catherine W S; Chan, Jonathan C H; Li, Q; Lai, Jimmy S M

2014-08-01

OBJECTIVE. To investigate the association between clinical measurements and glaucoma-specific quality of life in Chinese glaucoma patients. DESIGN. Cross-sectional study. SETTING. An academic hospital in Hong Kong. PATIENTS. A Chinese translation of the Glaucoma Quality of Life-15 questionnaire was completed by 51 consecutive patients with bilateral primary open-angle glaucoma. The binocular means of several clinical measurements were correlated with Glaucoma Quality of Life-15 findings using Pearson's correlation coefficient and linear regression. The measurements were the visual field index and pattern standard deviation from the Humphrey Field Analyzer, Snellen best-corrected visual acuity, presenting intra-ocular pressure, current intra-ocular pressure, average retinal nerve fibre layer thickness via optical coherence tomography, and the number of topical anti-glaucoma medications being used. RESULTS. In these patients, there was a significant correlation and linear relationship between a poorer Glaucoma Quality of Life-15 score and a lower visual field index (r=0.3, r(2)=0.1, P=0.01) and visual acuity (r=0.3, r(2)=0.1, P=0.03). A thinner retinal nerve fibre layer also correlated with a poorer Glaucoma Quality of Life-15 score, but did not attain statistical significance (r=0.3, P=0.07). There were no statistically significant correlations for the other clinical parameters with the Glaucoma Quality of Life-15 scores (all P values being >0.7). The three most problematic activities affecting quality of life were "adjusting to bright lights", "going from a light to a dark room or vice versa", and "seeing at night". CONCLUSION. For Chinese primary open-angle glaucoma patients, binocular visual field index and visual acuity correlated linearly with glaucoma-specific quality of life, and activities involving dark adaptation were the most problematic.

Statistical Methodology for the Analysis of Repeated Duration Data in Behavioral Studies

ERIC Educational Resources Information Center

Letué, Frédérique; Martinez, Marie-José; Samson, Adeline; Vilain, Anne; Vilain, Coriandre

2018-01-01

Purpose: Repeated duration data are frequently used in behavioral studies. Classical linear or log-linear mixed models are often inadequate to analyze such data, because they usually consist of nonnegative and skew-distributed variables. Therefore, we recommend use of a statistical methodology specific to duration data. Method: We propose a…

On the Stability of Jump-Linear Systems Driven by Finite-State Machines with Markovian Inputs

NASA Technical Reports Server (NTRS)

Patilkulkarni, Sudarshan; Herencia-Zapana, Heber; Gray, W. Steven; Gonzalez, Oscar R.

2004-01-01

This paper presents two mean-square stability tests for a jump-linear system driven by a finite-state machine with a first-order Markovian input process. The first test is based on conventional Markov jump-linear theory and avoids the use of any higher-order statistics. The second test is developed directly using the higher-order statistics of the machine s output process. The two approaches are illustrated with a simple model for a recoverable computer control system.

An open-access CMIP5 pattern library for temperature and precipitation: description and methodology

NASA Astrophysics Data System (ADS)

Lynch, Cary; Hartin, Corinne; Bond-Lamberty, Ben; Kravitz, Ben

2017-05-01

Pattern scaling is used to efficiently emulate general circulation models and explore uncertainty in climate projections under multiple forcing scenarios. Pattern scaling methods assume that local climate changes scale with a global mean temperature increase, allowing for spatial patterns to be generated for multiple models for any future emission scenario. For uncertainty quantification and probabilistic statistical analysis, a library of patterns with descriptive statistics for each file would be beneficial, but such a library does not presently exist. Of the possible techniques used to generate patterns, the two most prominent are the delta and least squares regression methods. We explore the differences and statistical significance between patterns generated by each method and assess performance of the generated patterns across methods and scenarios. Differences in patterns across seasons between methods and epochs were largest in high latitudes (60-90° N/S). Bias and mean errors between modeled and pattern-predicted output from the linear regression method were smaller than patterns generated by the delta method. Across scenarios, differences in the linear regression method patterns were more statistically significant, especially at high latitudes. We found that pattern generation methodologies were able to approximate the forced signal of change to within ≤ 0.5 °C, but the choice of pattern generation methodology for pattern scaling purposes should be informed by user goals and criteria. This paper describes our library of least squares regression patterns from all CMIP5 models for temperature and precipitation on an annual and sub-annual basis, along with the code used to generate these patterns. The dataset and netCDF data generation code are available at doi:10.5281/zenodo.495632.

The Ultrachopper tip: a wound temperature study.

PubMed

Barlow, William R; Pettey, Jeff; Olson, Randall J

2013-12-01

To determine the thermal characteristics of the Ultrachopper and its thermal properties in varied viscosurgical substances. Experimental study. Not applicable. The Ultrachopper (Alcon, Inc) tip with the Infiniti (Alcon, Inc) handpiece was attached to a thermistor and placed in a test chamber filled with either an ophthalmic viscosurgical device (OVD) or balanced salt solution (BSS). The thermistor allowed for continuous monitoring of temperature from baseline and the change that occurred over 60 seconds of continuous run time. Mean maximum temperature in each OVD exceeded 50°C over the first 25 seconds of continuous run time. The mean maximum temperature was statistically significantly higher with all OVDs (p < 0.0001) when compared with BSS. A small but statistically significant difference in mean maximum temperature was shown between Healon 5 (AMO, Inc) and Viscoat (Alcon, Inc) (p < 0.05). The linear increase in temperature was statistically significantly different with all OVDs compared with BSS (p < 0.0001). The thermal properties of the Ultrachopper tip demonstrate a heat-generating capacity that achieves published thresholds for risk for wound burn. Copyright © 2013 Canadian Ophthalmological Society. Published by Elsevier Inc. All rights reserved.

Two-Year Trends of Taxane-Induced Neuropathy in Women Enrolled in a Randomized Trial of Acetyl-L-Carnitine (SWOG S0715).

PubMed

Hershman, Dawn L; Unger, Joseph M; Crew, Katherine D; Till, Cathee; Greenlee, Heather; Minasian, Lori M; Moinpour, Carol M; Lew, Danika L; Fehrenbacher, Louis; Wade, James L; Wong, Siu-Fun; Fisch, Michael J; Lynn Henry, N; Albain, Kathy S

2018-06-01

Chemotherapy-induced peripheral neuropathy (CIPN) is a common and disabling side effect of taxanes. Acetyl-L-carnitine (ALC) was unexpectedly found to increase CIPN in a randomized trial. We investigated the long-term patterns of CIPN among patients in this trial. S0715 was a randomized, double-blind, multicenter trial comparing ALC (1000 mg three times a day) with placebo for 24 weeks in women undergoing adjuvant taxane-based chemotherapy for breast cancer. CIPN was measured by the 11-item neurotoxicity (NTX) component of the FACT-Taxane scale at weeks 12, 24, 36, 52, and 104. We examined NTX scores over two years using linear mixed models for longitudinal data. Individual time points were examined using linear regression. Regression analyses included stratification factors and the baseline score as covariates. All statistical tests were two-sided. Four-hundred nine subjects were eligible for evaluation. Patients receiving ALC had a statistically significantly (P = .01) greater reduction in NTX scores (worse CIPN) of -1.39 points (95% confidence interval [CI] = -2.48 to -0.30) than the placebo group. These differences were particularly evident at weeks 24 (-1.68, 95% CI = -3.02 to -0.33), 36 (-1.37, 95% CI = -2.69 to -0.04), and 52 (-1.83, 95% CI = -3.35 to -0.32). At 104 weeks, 39.5% on the ALC arm and 34.4% on the placebo arm reported a five-point (10%) decrease from baseline. For both treatment groups, 104-week NTX scores were statistically significantly different compared with baseline (P < .001). For both groups, NTX scores were reduced from baseline and remained persistently low. Twenty-four weeks of ALC therapy resulted in statistically significantly worse CIPN over two years. Understanding the mechanism of this persistent effect may inform prevention and treatment strategies. Until then, the potential efficacy and harms of commonly used supplements should be rigorously studied.

Quantitative structure-activity relationships by neural networks and inductive logic programming. I. The inhibition of dihydrofolate reductase by pyrimidines

NASA Astrophysics Data System (ADS)

Hirst, Jonathan D.; King, Ross D.; Sternberg, Michael J. E.

1994-08-01

Neural networks and inductive logic programming (ILP) have been compared to linear regression for modelling the QSAR of the inhibition of E. coli dihydrofolate reductase (DHFR) by 2,4-diamino-5-(substitured benzyl)pyrimidines, and, in the subsequent paper [Hirst, J.D., King, R.D. and Sternberg, M.J.E., J. Comput.-Aided Mol. Design, 8 (1994) 421], the inhibition of rodent DHFR by 2,4-diamino-6,6-dimethyl-5-phenyl-dihydrotriazines. Cross-validation trials provide a statistically rigorous assessment of the predictive capabilities of the methods, with training and testing data selected randomly and all the methods developed using identical training data. For the ILP analysis, molecules are represented by attributes other than Hansch parameters. Neural networks and ILP perform better than linear regression using the attribute representation, but the difference is not statistically significant. The major benefit from the ILP analysis is the formulation of understandable rules relating the activity of the inhibitors to their chemical structure.

Non-linear mixed effects modeling - from methodology and software development to driving implementation in drug development science.

PubMed

Pillai, Goonaseelan Colin; Mentré, France; Steimer, Jean-Louis

2005-04-01

Few scientific contributions have made significant impact unless there was a champion who had the vision to see the potential for its use in seemingly disparate areas-and who then drove active implementation. In this paper, we present a historical summary of the development of non-linear mixed effects (NLME) modeling up to the more recent extensions of this statistical methodology. The paper places strong emphasis on the pivotal role played by Lewis B. Sheiner (1940-2004), who used this statistical methodology to elucidate solutions to real problems identified in clinical practice and in medical research and on how he drove implementation of the proposed solutions. A succinct overview of the evolution of the NLME modeling methodology is presented as well as ideas on how its expansion helped to provide guidance for a more scientific view of (model-based) drug development that reduces empiricism in favor of critical quantitative thinking and decision making.

The photon gas formulation of thermal radiation

NASA Technical Reports Server (NTRS)

Ried, R. C., Jr.

1975-01-01

A statistical consideration of the energy, the linear momentum, and the angular momentum of the photons that make up a thermal radiation field was presented. A general nonequilibrium statistical thermodynamics approach toward a macroscopic description of thermal radiation transport was developed and then applied to the restricted equilibrium statistical thermostatics derivation of the energy, linear momentum, and intrinsic angular momentum equations for an isotropic photon gas. A brief treatment of a nonisotropic photon gas, as an example of the results produced by the nonequilibrium statistical thermodynamics approach, was given. The relativistic variation of temperature and the invariance of entropy were illustrated.

Testing the Dose–Response Specification in Epidemiology: Public Health and Policy Consequences for Lead

PubMed Central

Rothenberg, Stephen J.; Rothenberg, Jesse C.

2005-01-01

Statistical evaluation of the dose–response function in lead epidemiology is rarely attempted. Economic evaluation of health benefits of lead reduction usually assumes a linear dose–response function, regardless of the outcome measure used. We reanalyzed a previously published study, an international pooled data set combining data from seven prospective lead studies examining contemporaneous blood lead effect on IQ (intelligence quotient) of 7-year-old children (n = 1,333). We constructed alternative linear multiple regression models with linear blood lead terms (linear–linear dose response) and natural-log–transformed blood lead terms (log-linear dose response). We tested the two lead specifications for nonlinearity in the models, compared the two lead specifications for significantly better fit to the data, and examined the effects of possible residual confounding on the functional form of the dose–response relationship. We found that a log-linear lead–IQ relationship was a significantly better fit than was a linear–linear relationship for IQ (p = 0.009), with little evidence of residual confounding of included model variables. We substituted the log-linear lead–IQ effect in a previously published health benefits model and found that the economic savings due to U.S. population lead decrease between 1976 and 1999 (from 17.1 μg/dL to 2.0 μg/dL) was 2.2 times ($319 billion) that calculated using a linear–linear dose–response function ($149 billion). The Centers for Disease Control and Prevention action limit of 10 μg/dL for children fails to protect against most damage and economic cost attributable to lead exposure. PMID:16140626

Monitoring sleepiness with on-board electrophysiological recordings for preventing sleep-deprived traffic accidents.

PubMed

Papadelis, Christos; Chen, Zhe; Kourtidou-Papadeli, Chrysoula; Bamidis, Panagiotis D; Chouvarda, Ioanna; Bekiaris, Evangelos; Maglaveras, Nikos

2007-09-01

The objective of this study is the development and evaluation of efficient neurophysiological signal statistics, which may assess the driver's alertness level and serve as potential indicators of sleepiness in the design of an on-board countermeasure system. Multichannel EEG, EOG, EMG, and ECG were recorded from sleep-deprived subjects exposed to real field driving conditions. A number of severe driving errors occurred during the experiments. The analysis was performed in two main dimensions: the macroscopic analysis that estimates the on-going temporal evolution of physiological measurements during the driving task, and the microscopic event analysis that focuses on the physiological measurements' alterations just before, during, and after the driving errors. Two independent neurophysiologists visually interpreted the measurements. The EEG data were analyzed by using both linear and non-linear analysis tools. We observed the occurrence of brief paroxysmal bursts of alpha activity and an increased synchrony among EEG channels before the driving errors. The alpha relative band ratio (RBR) significantly increased, and the Cross Approximate Entropy that quantifies the synchrony among channels also significantly decreased before the driving errors. Quantitative EEG analysis revealed significant variations of RBR by driving time in the frequency bands of delta, alpha, beta, and gamma. Most of the estimated EEG statistics, such as the Shannon Entropy, Kullback-Leibler Entropy, Coherence, and Cross-Approximate Entropy, were significantly affected by driving time. We also observed an alteration of eyes blinking duration by increased driving time and a significant increase of eye blinks' number and duration before driving errors. EEG and EOG are promising neurophysiological indicators of driver sleepiness and have the potential of monitoring sleepiness in occupational settings incorporated in a sleepiness countermeasure device. The occurrence of brief paroxysmal bursts of alpha activity before severe driving errors is described in detail for the first time. Clear evidence is presented that eye-blinking statistics are sensitive to the driver's sleepiness and should be considered in the design of an efficient and driver-friendly sleepiness detection countermeasure device.

SU-G-BRC-15: The Potential Clinical Significance of Dose Mapping Error for Intra- Fraction Dose Mapping for Lung Cancer Patients

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

Sayah, N; Weiss, E; Watkins, W

Purpose: To evaluate the dose-mapping error (DME) inherent to conventional dose-mapping algorithms as a function of dose-matrix resolution. Methods: As DME has been reported to be greatest where dose-gradients overlap tissue-density gradients, non-clinical 66 Gy IMRT plans were generated for 11 lung patients with the target edge defined as the maximum 3D density gradient on the 0% (end of inhale) breathing phase. Post-optimization, Beams were copied to 9 breathing phases. Monte Carlo dose computed (with 2*2*2 mm{sup 3} resolution) on all 10 breathing phases was deformably mapped to phase 0% using the Monte Carlo energy-transfer method with congruent mass-mapping (EMCM);more » an externally implemented tri-linear interpolation method with voxel sub-division; Pinnacle’s internal (tri-linear) method; and a post-processing energy-mass voxel-warping method (dTransform). All methods used the same base displacement-vector-field (or it’s pseudo-inverse as appropriate) for the dose mapping. Mapping was also performed at 4*4*4 mm{sup 3} by merging adjacent dose voxels. Results: Using EMCM as the reference standard, no clinically significant (>1 Gy) DMEs were found for the mean lung dose (MLD), lung V20Gy, or esophagus dose-volume indices, although MLD and V20Gy were statistically different (2*2*2 mm{sup 3}). Pinnacle-to-EMCM target D98% DMEs of 4.4 and 1.2 Gy were observed ( 2*2*2 mm{sup 3}). However dTransform, which like EMCM conserves integral dose, had DME >1 Gy for one case. The root mean square RMS of the DME for the tri-linear-to- EMCM methods was lower for the smaller voxel volume for the tumor 4D-D98%, lung V20Gy, and cord D1%. Conclusion: When tissue gradients overlap with dose gradients, organs-at-risk DME was statistically significant but not clinically significant. Target-D98%-DME was deemed clinically significant for 2/11 patients (2*2*2 mm{sup 3}). Since tri-linear RMS-DME between EMCM and tri-linear was reduced at 2*2*2 mm{sup 3}, use of this resolution is recommended for dose mapping. Interpolative dose methods are sufficiently accurate for the majority of cases. J.V. Siebers receives funding support from Varian Medical Systems.« less

Generalized massive optimal data compression

NASA Astrophysics Data System (ADS)

Alsing, Justin; Wandelt, Benjamin

2018-05-01

In this paper, we provide a general procedure for optimally compressing N data down to n summary statistics, where n is equal to the number of parameters of interest. We show that compression to the score function - the gradient of the log-likelihood with respect to the parameters - yields n compressed statistics that are optimal in the sense that they preserve the Fisher information content of the data. Our method generalizes earlier work on linear Karhunen-Loéve compression for Gaussian data whilst recovering both lossless linear compression and quadratic estimation as special cases when they are optimal. We give a unified treatment that also includes the general non-Gaussian case as long as mild regularity conditions are satisfied, producing optimal non-linear summary statistics when appropriate. As a worked example, we derive explicitly the n optimal compressed statistics for Gaussian data in the general case where both the mean and covariance depend on the parameters.

Statistical relations of salt and selenium loads to geospatial characteristics of corresponding subbasins of the Colorado and Gunnison Rivers in Colorado

USGS Publications Warehouse

Leib, Kenneth J.; Linard, Joshua I.; Williams, Cory A.

2012-01-01

Elevated loads of salt and selenium can impair the quality of water for both anthropogenic and natural uses. Understanding the environmental processes controlling how salt and selenium are introduced to streams is critical to managing and mitigating the effects of elevated loads. Dominant relations between salt and selenium loads and environmental characteristics can be established by using geospatial data. The U.S. Geological Survey, in cooperation with the Bureau of Reclamation, investigated statistical relations between seasonal salt or selenium loads emanating from the Upper Colorado River Basin and geospatial data. Salt and selenium loads measured during the irrigation and nonirrigation seasons were related to geospatial variables for 168 subbasins within the Gunnison and Colorado River Basins. These geospatial variables represented subbasin characteristics of the physical environment, precipitation, geology, land use, and the irrigation network. All subbasin variables with units of area had statistically significant relations with load. The few variables that were not in units of area but were statistically significant helped to identify types of geospatial data that might influence salt and selenium loading. Following a stepwise approach, combinations of these statistically significant variables were used to develop multiple linear regression models. The models can be used to help prioritize areas where salt and selenium control projects might be most effective.

Spatial and temporal trends in runoff at long-term streamgages within and near the Chesapeake Bay Watershed

USGS Publications Warehouse

Rice, Karen C.; Hirsch, Robert M.

2012-01-01

Long-term streamflow data within the Chesapeake Bay watershed and surrounding area were analyzed in an attempt to identify trends in streamflow. Data from 30 streamgages near and within the Chesapeake Bay watershed were selected from 1930 through 2010 for analysis. Streamflow data were converted to runoff and trend slopes in percent change per decade were calculated. Trend slopes for three runoff statistics (the 7-day minimum, the mean, and the 1-day maximum) were analyzed annually and seasonally. The slopes also were analyzed both spatially and temporally. The spatial results indicated that trend slopes in the northern half of the watershed were generally greater than those in the southern half. The temporal analysis was done by splitting the 80-year flow record into two subsets; records for 28 streamgages were analyzed for 1930 through 1969 and records for 30 streamgages were analyzed for 1970 through 2010. The mean of the data for all sites for each year were plotted so that the following datasets were analyzed: the 7-day minimum runoff for the north, the 7-day minimum runoff for the south, the mean runoff for the north, the mean runoff for the south, the 1-day maximum runoff for the north, and the 1-day maximum runoff for the south. Results indicated that the period 1930 through 1969 was statistically different from the period 1970 through 2010. For the 7-day minimum runoff and the mean runoff, the latter period had significantly higher streamflow than did the earlier period, although within those two periods no significant linear trends were identified. For the 1-day maximum runoff, no step trend or linear trend could be shown to be statistically significant for the north, although the south showed a mixture of an upward step trend accompanied by linear downtrends within the periods. In no case was a change identified that indicated an increasing rate of change over time, and no general pattern was identified of hydrologic conditions becoming "more extreme" over time.

Solid Cancer Incidence in the Techa River Incidence Cohort: 1956-2007.

PubMed

Davis, F G; Yu, K L; Preston, D; Epifanova, S; Degteva, M; Akleyev, A V

2015-07-01

Previously reported studies of the Techa River Cohort have established associations between radiation dose and the occurrence of solid cancers and leukemia (non-CLL) that appear to be linear in dose response. These analyses include 17,435 cohort members alive and not known to have had cancer prior to January 1, 1956 who lived in areas near the river or Chelyabinsk City at some time between 1956 and the end of 2007, utilized individualized dose estimates computed using the Techa River Dosimetry System 2009 and included five more years of follow-up. The median and mean dose estimates based on these doses are consistently higher than those based on earlier Techa River Dosimetry System 2000 dose estimates. This article includes new site-specific cancer risk estimates and risk estimates adjusted for available information on smoking. There is a statistically significant (P = 0.02) linear trend in the smoking-adjusted all-solid cancer incidence risks with an excess relative risk (ERR) after exposure to 100 mGy of 0.077 with a 95% confidence interval of 0.013-0.15. Examination of site-specific risks revealed statistically significant radiation dose effects only for cancers of the esophagus and uterus with an ERR per 100 mGy estimates in excess of 0.10. Esophageal cancer risk estimates were modified by ethnicity and sex, but not smoking. While the solid cancer rates are attenuated when esophageal cancer is removed (ERR = 0.063 per 100 mGy), a dose-response relationship is present and it remains likely that radiation exposure has increased the risks for most solid cancers in the cohort despite the lack of power to detect statistically significant risks for specific sites.

Radiographic assessment of lower third molar eruption in different anteroposterior skeletal patterns and age-related groups.

PubMed

Jakovljevic, Aleksandar; Lazic, Emira; Soldatovic, Ivan; Nedeljkovic, Nenad; Andric, Miroslav

2015-07-01

To analyze radiographic predictors for lower third molar eruption among subjects with different anteroposterior skeletal relations and of different age groups. In total, 300 lower third molars were recorded on diagnostic digital orthopantomograms (DPTs) and lateral cephalograms (LCs). The radiographs were grouped according to sagittal intermaxillary angle (ANB), subject age, and level of lower third molar eruption. The DPT was used to analyze retromolar space, mesiodistal crown width, space/width ratio, third and second molar angulation (α, γ), third molar inclination (β), and gonion angle. The LC was used to determine ANB, angles of maxillar and mandibular prognathism (SNA, SNB), mandibular plane angle (SN/MP), and mandibular lengths. A logistic regression model was created using the statistically significant predictors. The logistic regression analysis revealed a statistically significant impact of β angle and distance between gonion and gnathion (Go-Gn) on the level of lower third molar eruption (P < .001 and P < .015, respectively). The retromolar space was significantly increased in the adult subgroup for all skeletal classes. The lower third molar impaction rate was significantly higher in the adult subgroup with the Class II (62.3%) compared with Class III subjects (31.7%; P < .013). The most favorable values of linear and angular predictors of mandibular third molar eruption were measured in Class III subjects. For valid estimation of mandibular third molar eruption, certain linear and angular measures (β angle, Go-Gn), as well as the size of the retromolar space, need to be considered.

Correlation between urodynamic function and 3D cat scan anatomy in neobladders: does it exist?

PubMed

Crivellaro, S; Mami, E; Wald, C; Smith, J J; Kocjancic, E; Stoffel, J; Bresette, J; Libertino, J A

2009-01-01

We compared the functional and anatomical differences among three different orthotopic neobladders, utilizing video urodynamics and 3D CT to determine what parameters, if any, correlate to function. Thirty-four patients were able to participate in the evaluation of their neobladder by 3D CT and video urodynamics. Three different orthotopic neobladders were identified (12 ileal, 7 ileocecal, 15 sigmoid). Multiple measurements, observations and functional data have been obtained. Statistical analysis for this study employed a linear regression test and an odds ratio calculation (using StatSoft V. 5.1). In comparing three different neobladders, no significant differences were noted. Looking at the entire population, the following association was statistically significant in linear correlation: the maximal capacity and the neobladder volume; the pressure at the maximal capacity and the distance from the symphysis, the pressure at maximal flow and both the distance from the symphysis and the thickness of the neobladder. The distance from the left femoral head was directly correlated with the post void residual and inversely correlated with the maximal flow. The Odds ratio calculation revealed (with significant P < 0.05) that the further the center of the neobladder is from the right femoral head, the higher risk of incontinence. The study seems to show no significant anatomical or functional difference among the three different types of neobladders. A possible correlation between the position of the neobladder and urinary incontinence is suggested, recognizing further study in a larger population is required.

Landsat analysis for uranium exploration in Northeast Turkey

USGS Publications Warehouse

Lee, Keenan

1983-01-01

No uranium deposits are known in the Trabzon, Turkey region, and consequently, exploration criteria have not been defined. Nonetheless, by analogy with uranium deposits studied elsewhere, exploration guides are suggested to include dense concentrations of linear features, lineaments -- especially with northwest trend, acidic plutonic rocks, and alteration indicated by limonite. A suite of digitally processed images of a single Landsat scene served as the image base for mapping 3,376 linear features. Analysis of the linear feature data yielded two statistically significant trends, which in turn defined two sets of strong lineaments. Color composite images were used to map acidic plutonic rocks and areas of surficial limonitic materials. The Landsat interpretation yielded a map of these exploration guides that may be used to evaluate relative uranium potential. One area in particular shows a high coincidence of favorable indicators.

Predictors of high out-of-pocket healthcare expenditure: an analysis using Bangladesh household income and expenditure survey, 2010.

PubMed

Molla, Azaher Ali; Chi, Chunhuei; Mondaca, Alicia Lorena Núñez

2017-01-31

Predictors of high out-of-pocket household healthcare expenditure are essential for creating effective health system finance policy. In Bangladesh, 63.3% of health expenditure is out-of-pocket and born by households. It is imperative to know what determines household health expenditure. This study aims to investigate the predicting factors of high out-of-pocket household healthcare expenditure targeting to put forward policy recommendations on equity in financial burden. Bangladesh household income and expenditure survey 2010 provides data for this study. Predictors of high out-of-pocket household healthcare expenditure were analyzed using multiple linear regressions. We have modeled non-linear relationship using logarithmic form of linear regression. Heteroscedasticity and multicollinearity were checked using Breusch-Pagan/Cook-Weishberg and VIF tests. Normality of the residuals was checked using Kernel density curve. We applied required adjustment for survey data, so that standard errors and parameters estimation are valid. Presence of chronic disease and household income were found to be the most influential and statistically significant (p < 0.001) predictors of high household healthcare expenditure. Households in rural areas spend 7% less than urban dwellers. The results show that a 100% increase in female members in a family leads to a 2% decrease in household health expenditure. Household income, health shocks in families, and family size are other statistically significant predictors of household healthcare expenditure. Proportion of elderly and under-five members in the family show some positive influence on health expenditure, though statistically nonsignificant. The findings call for emphasizing prevention of chronic diseases, as it is a strong predictor of household health expenditure. Innovative insurance scheme needs to be devised to prevent household from being impoverished due to health shocks in the family. Policy makers are urged to design an alternative source of healthcare financing in Bangladesh to minimize the burden of high OOP healthcare expenditure.

Multivariate mixed linear model analysis of longitudinal data: an information-rich statistical technique for analyzing disease resistance data

USDA-ARS?s Scientific Manuscript database

The mixed linear model (MLM) is currently among the most advanced and flexible statistical modeling techniques and its use in tackling problems in plant pathology has begun surfacing in the literature. The longitudinal MLM is a multivariate extension that handles repeatedly measured data, such as r...

Extra-articular manifestations of seronegative and seropositive rheumatoid arthritis.

PubMed

Sahatciu-Meka, Vjollca; Rexhepi, Sylejman; Manxhuka-Kerliu, Suzana; Rexhepi, Mjellma

2010-02-01

Although considered a "joint disease," rheumatoid arthritis is associated with the involvement of extra-articular manifestations. The aim of the study is the investigation and comparison of frequency and type of extra-articular manifestations in a well defined community based cohort of patients with seropositive and seronegative rheumatoid arthritis. Using the ACR (1987) criteria for rheumatoid arthritis, patients have been classified into the 2nd and 3rd functional class (ARA). The studied group consisted of 125 seronegative patients with titters lower than 1:64 as defined by Rose-Waaler test, whereas the control group consisted of 125 seropositive patients with titters of 1:64 or higher. All patients were between 25-60 years of age (Xb=49,96), with disease duration between 1-27 years (Xb=6,41). In order to present the findings of the study, the structure, prevalence, arithmetic mean (Xb), standard deviation (SB), variation quotient (QV%) and variation interval (Rmax-Rmin) have been used. Probability level has been expressed by p<0,01 and p<0,05. Correlation between the number of extra-articular manifestations and duration of the disease has been calculated by means of Pearson linear correlation. Higher presence of diffuse lung fibrosis, central and peripheral nervous system damages have been confirmed in the seropositive group, and osteoporosis in the seronegative; however, no statistical difference has been found. In extra-articular manifestations, "rheumatoid core" in the seropositive subset (chi2=4,80, p<0,05) presented significant statistical difference. Rheumatoid nodules were more frequent in seropositive subset (12%:16%), in both sexes; however, they were not of significant statistical difference. Neuropathy and lung diseases were also frequently present in seropositive group, but no statistical difference has been found regarding the statistical difference. Longer duration of the disease resulted in an increase of the number of extra-articular manifestations. Calculated linear correlation by Pearson, resulted as positive and high correlation in total (r=0,36, p<0,01), and for groups [(r=0,52, p<0,01) seronegative, (r=0,25, p<0,01) seropositive], nevertheless no significant statistical difference was found regarding the sero-status. In conclusion, extra-articular manifestations are more frequent in the seropositive patients. The longer the duration of the disease the larger the number of extra-articular manifestations. Differences with regard to sero-status and sex, with some exceptions, are not observed.

Estimating PM2.5 Concentrations in Xi'an City Using a Generalized Additive Model with Multi-Source Monitoring Data

PubMed Central

Song, Yong-Ze; Yang, Hong-Lei; Peng, Jun-Huan; Song, Yi-Rong; Sun, Qian; Li, Yuan

2015-01-01

Particulate matter with an aerodynamic diameter <2.5 μm (PM2.5) represents a severe environmental problem and is of negative impact on human health. Xi'an City, with a population of 6.5 million, is among the highest concentrations of PM2.5 in China. In 2013, in total, there were 191 days in Xi’an City on which PM2.5 concentrations were greater than 100 μg/m3. Recently, a few studies have explored the potential causes of high PM2.5 concentration using remote sensing data such as the MODIS aerosol optical thickness (AOT) product. Linear regression is a commonly used method to find statistical relationships among PM2.5 concentrations and other pollutants, including CO, NO2, SO2, and O3, which can be indicative of emission sources. The relationships of these variables, however, are usually complicated and non-linear. Therefore, a generalized additive model (GAM) is used to estimate the statistical relationships between potential variables and PM2.5 concentrations. This model contains linear functions of SO2 and CO, univariate smoothing non-linear functions of NO2, O3, AOT and temperature, and bivariate smoothing non-linear functions of location and wind variables. The model can explain 69.50% of PM2.5 concentrations, with R2 = 0.691, which improves the result of a stepwise linear regression (R2 = 0.582) by 18.73%. The two most significant variables, CO concentration and AOT, represent 20.65% and 19.54% of the deviance, respectively, while the three other gas-phase concentrations, SO2, NO2, and O3 account for 10.88% of the total deviance. These results show that in Xi'an City, the traffic and other industrial emissions are the primary source of PM2.5. Temperature, location, and wind variables also non-linearly related with PM2.5. PMID:26540446

Evaluation of salivary fluoride retention from a new high fluoride mouthrinse.

PubMed

Mason, Stephen C; Shirodaria, Soha; Sufi, Farzana; Rees, Gareth D; Birkhed, Dowen

2010-11-01

To evaluate salivary fluoride retention from a new high fluoride daily use mouthrinse over a 120 min period. Sixteen subjects completed a randomised single-blind, four-treatment cross-over trial. Sensodyne® Pronamel® mouthrinse (A) contained 450 ppm fluoride; reference products were Colgate® Fluorigard® (B), Listerine® Total Care (C) and Listerine Softmint Sensation (D) containing 225, 100 and 0 ppm fluoride respectively. Salivary fluoride retention was monitored ex vivo after a single supervised use of test product (10 mL, 60 s). Samples were collected at 0, 1, 3, 5, 15, 30, 60 and 120 min post-rinse, generating fluoride clearance curves from which the area under the curve (AUC) was calculated. Differences in salivary fluoride concentrations for each product were analysed using ANCOVA at each time point using a 5% significance level, as well as lnAUC for the periods 0-120, 0-1, 1-15, 15-60 and 60-120 min. Pairwise comparisons between all treatment groups were performed. Salivary fluoride levels for A-C peaked immediately following use. Fluoride levels were statistically significantly higher for A versus B-D (p≤ 0.004), linear dose responses were apparent. AUC(0-120) was statistically significantly greater for A than for B (p = 0.035), C (p< 0.0001) and D (p< 0.0001). Post-hoc comparisons of lnAUC for the remaining time domains showed fluoride retention from A was statistically significantly greater versus B-D (p< 0.0001). Single-use treatment with the new mouthrinse containing 450 ppm fluoride resulted in statistically significantly higher salivary fluoride levels throughout the 120 min test period. Total fluoride retention (AUC(0-120)) was also statistically significantly greater versus comparator rinse treatments. Copyright © 2010 Elsevier Ltd. All rights reserved.

A general science-based framework for dynamical spatio-temporal models

USGS Publications Warehouse

Wikle, C.K.; Hooten, M.B.

2010-01-01

Spatio-temporal statistical models are increasingly being used across a wide variety of scientific disciplines to describe and predict spatially-explicit processes that evolve over time. Correspondingly, in recent years there has been a significant amount of research on new statistical methodology for such models. Although descriptive models that approach the problem from the second-order (covariance) perspective are important, and innovative work is being done in this regard, many real-world processes are dynamic, and it can be more efficient in some cases to characterize the associated spatio-temporal dependence by the use of dynamical models. The chief challenge with the specification of such dynamical models has been related to the curse of dimensionality. Even in fairly simple linear, first-order Markovian, Gaussian error settings, statistical models are often over parameterized. Hierarchical models have proven invaluable in their ability to deal to some extent with this issue by allowing dependency among groups of parameters. In addition, this framework has allowed for the specification of science based parameterizations (and associated prior distributions) in which classes of deterministic dynamical models (e. g., partial differential equations (PDEs), integro-difference equations (IDEs), matrix models, and agent-based models) are used to guide specific parameterizations. Most of the focus for the application of such models in statistics has been in the linear case. The problems mentioned above with linear dynamic models are compounded in the case of nonlinear models. In this sense, the need for coherent and sensible model parameterizations is not only helpful, it is essential. Here, we present an overview of a framework for incorporating scientific information to motivate dynamical spatio-temporal models. First, we illustrate the methodology with the linear case. We then develop a general nonlinear spatio-temporal framework that we call general quadratic nonlinearity and demonstrate that it accommodates many different classes of scientific-based parameterizations as special cases. The model is presented in a hierarchical Bayesian framework and is illustrated with examples from ecology and oceanography. ?? 2010 Sociedad de Estad??stica e Investigaci??n Operativa.

Polyethylene wear in Oxford unicompartmental knee replacement: a retrieval study of 47 bearings.

PubMed

Kendrick, B J L; Longino, D; Pandit, H; Svard, U; Gill, H S; Dodd, C A F; Murray, D W; Price, A J

2010-03-01

The Oxford Unicompartmental Knee replacement (UKR) was introduced as a design to reduce polyethylene wear. There has been one previous retrieval study involving this implant, which reported very low rates of wear in some specimens but abnormal patterns of wear in others. There has been no further investigation of these abnormal patterns. The bearings were retrieved from 47 patients who had received a medial Oxford UKR for anteromedial osteoarthritis of the knee. None had been studied previously. The mean time to revision was 8.4 years (sd 4.1), with 20 having been implanted for over ten years. The macroscopic pattern of polyethylene wear and the linear penetration were recorded for each bearing. The mean rate of linear penetration was 0.07 mm/year. The patterns of wear fell into three categories, each with a different rate of linear penetration; 1) no abnormal macroscopic wear and a normal articular surface, n = 16 (linear penetration rate = 0.01 mm/year); 2) abnormal macroscopic wear and normal articular surfaces with extra-articular impingement, n = 16 (linear penetration rate = 0.05 mm/year); 3) abnormal macroscopic wear and abnormal articular surfaces with intra-articular impingement +/- signs of non-congruous articulation, n = 15 (linear penetration rate = 0.12 mm/year). The differences in linear penetration rate were statistically significant (p < 0.001). These results show that very low rates of polyethylene wear are possible if the device functions normally. However, if the bearing displays suboptimal function (extra-articular, intra-articular impingement or incongruous articulation) the rates of wear increase significantly.

Spatially resolved regression analysis of pre-treatment FDG, FLT and Cu-ATSM PET from post-treatment FDG PET: an exploratory study

PubMed Central

Bowen, Stephen R; Chappell, Richard J; Bentzen, Søren M; Deveau, Michael A; Forrest, Lisa J; Jeraj, Robert

2012-01-01

Purpose To quantify associations between pre-radiotherapy and post-radiotherapy PET parameters via spatially resolved regression. Materials and methods Ten canine sinonasal cancer patients underwent PET/CT scans of [18F]FDG (FDGpre), [18F]FLT (FLTpre), and [61Cu]Cu-ATSM (Cu-ATSMpre). Following radiotherapy regimens of 50 Gy in 10 fractions, veterinary patients underwent FDG PET/CT scans at three months (FDGpost). Regression of standardized uptake values in baseline FDGpre, FLTpre and Cu-ATSMpre tumour voxels to those in FDGpost images was performed for linear, log-linear, generalized-linear and mixed-fit linear models. Goodness-of-fit in regression coefficients was assessed by R2. Hypothesis testing of coefficients over the patient population was performed. Results Multivariate linear model fits of FDGpre to FDGpost were significantly positive over the population (FDGpost~0.17 FDGpre, p=0.03), and classified slopes of RECIST non-responders and responders to be different (0.37 vs. 0.07, p=0.01). Generalized-linear model fits related FDGpre to FDGpost by a linear power law (FDGpost~FDGpre0.93, p<0.001). Univariate mixture model fits of FDGpre improved R2 from 0.17 to 0.52. Neither baseline FLT PET nor Cu-ATSM PET uptake contributed statistically significant multivariate regression coefficients. Conclusions Spatially resolved regression analysis indicates that pre-treatment FDG PET uptake is most strongly associated with three-month post-treatment FDG PET uptake in this patient population, though associations are histopathology-dependent. PMID:22682748

Linear Classifier with Reject Option for the Detection of Vocal Fold Paralysis and Vocal Fold Edema

NASA Astrophysics Data System (ADS)

Kotropoulos, Constantine; Arce, Gonzalo R.

2009-12-01

Two distinct two-class pattern recognition problems are studied, namely, the detection of male subjects who are diagnosed with vocal fold paralysis against male subjects who are diagnosed as normal and the detection of female subjects who are suffering from vocal fold edema against female subjects who do not suffer from any voice pathology. To do so, utterances of the sustained vowel "ah" are employed from the Massachusetts Eye and Ear Infirmary database of disordered speech. Linear prediction coefficients extracted from the aforementioned utterances are used as features. The receiver operating characteristic curve of the linear classifier, that stems from the Bayes classifier when Gaussian class conditional probability density functions with equal covariance matrices are assumed, is derived. The optimal operating point of the linear classifier is specified with and without reject option. First results using utterances of the "rainbow passage" are also reported for completeness. The reject option is shown to yield statistically significant improvements in the accuracy of detecting the voice pathologies under study.

Visual Field Outcomes for the Idiopathic Intracranial Hypertension Treatment Trial (IIHTT).

PubMed

Wall, Michael; Johnson, Chris A; Cello, Kimberly E; Zamba, K D; McDermott, Michael P; Keltner, John L

2016-03-01

The Idiopathic Intracranial Hypertension Treatment Trial (IIHTT) showed that acetazolamide provided a modest, significant improvement in mean deviation (MD). Here, we further analyze visual field changes over the 6-month study period. Of 165 subjects with mild visual loss in the IIHTT, 125 had perimetry at baseline and 6 months. We evaluated pointwise linear regression of visual sensitivity versus time to classify test locations in the worst MD (study) eye as improving or not; pointwise changes from baseline to month 6 in decibels; and clinical consensus of change from baseline to 6 months. The average study eye had 36 of 52 test locations with improving sensitivity over 6 months using pointwise linear regression, but differences between the acetazolamide and placebo groups were not significant. Pointwise results mostly improved in both treatment groups with the magnitude of the mean change within groups greatest and statistically significant around the blind spot and the nasal area, especially in the acetazolamide group. The consensus classification of visual field change from baseline to 6 months in the study eye yielded percentages (acetazolamide, placebo) of 7.2% and 17.5% worse, 35.1% and 31.7% with no change, and 56.1% and 50.8% improved; group differences were not statistically significant. In the IIHTT, compared to the placebo group, the acetazolamide group had a significant pointwise improvement in visual field function, particularly in the nasal and pericecal areas; the latter is likely due to reduction in blind spot size related to improvement in papilledema. (ClinicalTrials.gov number, NCT01003639.).

Racial differences in knee osteoarthritis pain: potential contribution of occupational and household tasks.

PubMed

Allen, Kelli D; Chen, Jiu-Chiuan; Callahan, Leigh F; Golightly, Yvonne M; Helmick, Charles G; Renner, Jordan B; Schwartz, Todd A; Jordan, Joanne M

2012-02-01

We examined whether occupational and household tasks contributed to differences in pain between African Americans and whites with radiographic knee osteoarthritis (OA). Participants from the Johnston County Osteoarthritis Project self-reported the frequency (often/always vs never/seldom/sometimes) of performing 9 occupational tasks involving lower extremity joint loading at their longest job (N = 868) and current job (N = 273), as well as 8 household tasks ever performed (N = 811) and currently being performed (N = 767). The associations of the numbers of occupational or household tasks with the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain subscale were first examined in simple linear regression models. If significantly associated with greater pain, each of these was included in adjusted linear regression models to examine whether the association of race with pain remained statistically significant. African Americans reported significantly greater WOMAC pain scores than whites. Exposures to more occupational tasks at the longest job and the current job were associated with greater WOMAC pain scores (p < 0.01). The association of race with greater pain scores remained statistically significant when controlling for occupational tasks at the longest job, but was reduced by 26% and no longer significant when controlling for the number of current occupational tasks. Exposures to an increasing number of household tasks were associated with lower pain scores and were not further analyzed. Current performance of physically demanding occupational tasks contributed to racial differences in pain severity among individuals with knee OA. Better workplace policies to accommodate OA-related limitations may help to reduce racial differences in pain.

Associations between state-level soda taxes and adolescent body mass index.

PubMed

Powell, Lisa M; Chriqui, Jamie; Chaloupka, Frank J

2009-09-01

Soft drink consumption has been linked with higher energy intake, obesity, and poorer health. Fiscal pricing policies such as soda taxes may lower soda consumption and, in turn, reduce weight among U.S. adolescents. This study used multivariate linear regression analyses to examine the associations between state-level grocery store and vending machine soda taxes and adolescent body mass index (BMI). We used repeated cross-sections of individual-level data on adolescents drawn from the Monitoring the Future surveys combined with state-level tax data and local area contextual measures for the years 1997 through 2006. The results showed no statistically significant associations between state-level soda taxes and adolescent BMI. Only a weak economic and statistically significant effect was found between vending machine soda tax rates and BMI among teens at risk for overweight. Current state-level tax rates are not found to be significantly associated with adolescent weight outcomes. It is likely that taxes would need to be raised substantially to detect significant associations between taxes and adolescent weight.

Comparison of disinfectants by immersion and spray atomization techniques on the linear dimensional stability of different interocclusal recording materials: An in vitro study

PubMed Central

Gounder, Revathy; Vikas, B. V. J.

2016-01-01

Objective: To evaluate and compare the effect of 0.5% chlorhexidine gluconate, 1% sodium hypochlorite, and 2% glutaraldehyde by immersion and spray atomization technique on the linear dimensional stability of Jet bite, Aluwax and Ramitec interocclusal recording materials. Materials and Methods: Three representative materials: Jet bite (addition silicone), Aluwax and Ramitec (polyether) were mixed according to manufacturer's instructions and then specimens were prepared according to the specifications of ISO 4823. All the specimens except the control (distilled water) were treated with disinfectant solutions (0.5% chlorhexidine gluconate, 1% sodium hypochlorite, and 2% glutaraldehyde) for 30 and 60 min (n = 10) by spray and immersion technique. Once removed from the solutions, the test samples were washed in water for 15 s, dried and measured after 24 h 3 times using a measuring microscope with an accuracy of 0.0001 mm. Two-way ANOVA and Tukey's test with significance level of 5% were used to assess the statistical data (α = 0.05). Result: All groups showed no significant difference statistically, in linear dimension when disinfected for 30 min by spray or immersion technique. Polyether had significantly higher dimensional variation when immersed in sodium hypochlorite for 60 min. Addition silicone showed the least dimensional change which ranged from 0.024% to 0.05%, followed by polyether from 0.004% to 0.171% and Aluwax from 0.146% to 0.228%. Conclusion: To preserve the dimensions and surface of the recording materials and effective microbial elimination, restrictions should be applied in the method of disinfection and time duration. However, using the disinfectants either by spray or immersion technique, the dimensional change was <0.5% which was not clinically significant according to the American Dental Association specification no. 19 criteria within the first 24 h. PMID:27011733

A note on the correlation between circular and linear variables with an application to wind direction and air temperature data in a Mediterranean climate

NASA Astrophysics Data System (ADS)

Lototzis, M.; Papadopoulos, G. K.; Droulia, F.; Tseliou, A.; Tsiros, I. X.

2018-04-01

There are several cases where a circular variable is associated with a linear one. A typical example is wind direction that is often associated with linear quantities such as air temperature and air humidity. The analysis of a statistical relationship of this kind can be tested by the use of parametric and non-parametric methods, each of which has its own advantages and drawbacks. This work deals with correlation analysis using both the parametric and the non-parametric procedure on a small set of meteorological data of air temperature and wind direction during a summer period in a Mediterranean climate. Correlations were examined between hourly, daily and maximum-prevailing values, under typical and non-typical meteorological conditions. Both tests indicated a strong correlation between mean hourly wind directions and mean hourly air temperature, whereas mean daily wind direction and mean daily air temperature do not seem to be correlated. In some cases, however, the two procedures were found to give quite dissimilar levels of significance on the rejection or not of the null hypothesis of no correlation. The simple statistical analysis presented in this study, appropriately extended in large sets of meteorological data, may be a useful tool for estimating effects of wind on local climate studies.

Linear models: permutation methods

USGS Publications Warehouse

Cade, B.S.; Everitt, B.S.; Howell, D.C.

2005-01-01

Permutation tests (see Permutation Based Inference) for the linear model have applications in behavioral studies when traditional parametric assumptions about the error term in a linear model are not tenable. Improved validity of Type I error rates can be achieved with properly constructed permutation tests. Perhaps more importantly, increased statistical power, improved robustness to effects of outliers, and detection of alternative distributional differences can be achieved by coupling permutation inference with alternative linear model estimators. For example, it is well-known that estimates of the mean in linear model are extremely sensitive to even a single outlying value of the dependent variable compared to estimates of the median [7, 19]. Traditionally, linear modeling focused on estimating changes in the center of distributions (means or medians). However, quantile regression allows distributional changes to be estimated in all or any selected part of a distribution or responses, providing a more complete statistical picture that has relevance to many biological questions [6]...

A Novel Kalman Filter for Human Motion Tracking With an Inertial-Based Dynamic Inclinometer.

PubMed

Ligorio, Gabriele; Sabatini, Angelo M

2015-08-01

Design and development of a linear Kalman filter to create an inertial-based inclinometer targeted to dynamic conditions of motion. The estimation of the body attitude (i.e., the inclination with respect to the vertical) was treated as a source separation problem to discriminate the gravity and the body acceleration from the specific force measured by a triaxial accelerometer. The sensor fusion between triaxial gyroscope and triaxial accelerometer data was performed using a linear Kalman filter. Wrist-worn inertial measurement unit data from ten participants were acquired while performing two dynamic tasks: 60-s sequence of seven manual activities and 90 s of walking at natural speed. Stereophotogrammetric data were used as a reference. A statistical analysis was performed to assess the significance of the accuracy improvement over state-of-the-art approaches. The proposed method achieved, on an average, a root mean square attitude error of 3.6° and 1.8° in manual activities and locomotion tasks (respectively). The statistical analysis showed that, when compared to few competing methods, the proposed method improved the attitude estimation accuracy. A novel Kalman filter for inertial-based attitude estimation was presented in this study. A significant accuracy improvement was achieved over state-of-the-art approaches, due to a filter design that better matched the basic optimality assumptions of Kalman filtering. Human motion tracking is the main application field of the proposed method. Accurately discriminating the two components present in the triaxial accelerometer signal is well suited for studying both the rotational and the linear body kinematics.

Gender differences in knee morphology and the prospects for implant design in total knee replacement.

PubMed

Asseln, Malte; Hänisch, Christoph; Schick, Fabian; Radermacher, Klaus

2018-05-14

Morphological differences between female and male knees have been reported in the literature, which led to the development of so-called gender-specific implants. However, detailed morphological descriptions covering the entire joint are rare and little is known regarding whether gender differences are real sexual dimorphisms or can be explained by overall differences in size. We comprehensively analysed knee morphology using 33 features of the femur and 21 features of the tibia to quantify knee shape. The landmark recognition and feature extraction based on three-dimensional surface data were fully automatically applied to 412 pathological (248 female and 164 male) knees undergoing total knee arthroplasty. Subsequently, an exploratory statistical analysis was performed and linear correlation analysis was used to investigate normalization factors and gender-specific differences. Statistically significant differences between genders were observed. These were pronounced for distance measurements and negligible for angular (relative) measurements. Female knees were significantly narrower at the same depth compared to male knees. The correlation analysis showed that linear correlations were higher for distance measurements defined in the same direction. After normalizing the distance features according to overall dimensions in the direction of their definition, gender-specific differences disappeared or were smaller than the related confidence intervals. Implants should not be linearly scaled according to one dimension. Instead, features in medial/lateral and anterior/posterior directions should be normalized separately (non-isotropic scaling). However, large inter-individual variations of the features remain after normalization, suggesting that patient-specific design solutions are required for an improved implant design, regardless of gender. Copyright © 2018 Elsevier B.V. All rights reserved.

Overcoming bias in estimating the volume-outcome relationship.

PubMed

Tsai, Alexander C; Votruba, Mark; Bridges, John F P; Cebul, Randall D

2006-02-01

To examine the effect of hospital volume on 30-day mortality for patients with congestive heart failure (CHF) using administrative and clinical data in conventional regression and instrumental variables (IV) estimation models. The primary data consisted of longitudinal information on comorbid conditions, vital signs, clinical status, and laboratory test results for 21,555 Medicare-insured patients aged 65 years and older hospitalized for CHF in northeast Ohio in 1991-1997. The patient was the primary unit of analysis. We fit a linear probability model to the data to assess the effects of hospital volume on patient mortality within 30 days of admission. Both administrative and clinical data elements were included for risk adjustment. Linear distances between patients and hospitals were used to construct the instrument, which was then used to assess the endogeneity of hospital volume. When only administrative data elements were included in the risk adjustment model, the estimated volume-outcome effect was statistically significant (p=.029) but small in magnitude. The estimate was markedly attenuated in magnitude and statistical significance when clinical data were added to the model as risk adjusters (p=.39). IV estimation shifted the estimate in a direction consistent with selective referral, but we were unable to reject the consistency of the linear probability estimates. Use of only administrative data for volume-outcomes research may generate spurious findings. The IV analysis further suggests that conventional estimates of the volume-outcome relationship may be contaminated by selective referral effects. Taken together, our results suggest that efforts to concentrate hospital-based CHF care in high-volume hospitals may not reduce mortality among elderly patients.

Adding a Parameter Increases the Variance of an Estimated Regression Function

ERIC Educational Resources Information Center

Withers, Christopher S.; Nadarajah, Saralees

2011-01-01

The linear regression model is one of the most popular models in statistics. It is also one of the simplest models in statistics. It has received applications in almost every area of science, engineering and medicine. In this article, the authors show that adding a predictor to a linear model increases the variance of the estimated regression…

Statistical properties of radiation from VUV and X-ray free electron laser

NASA Astrophysics Data System (ADS)

Saldin, E. L.; Schneidmiller, E. A.; Yurkov, M. V.

1998-03-01

The paper presents a comprehensive analysis of the statistical properties of the radiation from a self-amplified spontaneous emission (SASE) free electron laser operating in linear and nonlinear mode. The investigation has been performed in a one-dimensional approximation assuming the electron pulse length to be much larger than a coherence length of the radiation. The following statistical properties of the SASE FEL radiation have been studied in detail: time and spectral field correlations, distribution of the fluctuations of the instantaneous radiation power, distribution of the energy in the electron bunch, distribution of the radiation energy after the monochromator installed at the FEL amplifier exit and radiation spectrum. The linear high gain limit is studied analytically. It is shown that the radiation from a SASE FEL operating in the linear regime possesses all the features corresponding to completely chaotic polarized radiation. A detailed study of statistical properties of the radiation from a SASE FEL operating in linear and nonlinear regime has been performed by means of time-dependent simulation codes. All numerical results presented in the paper have been calculated for the 70 nm SASE FEL at the TESLA Test Facility being under construction at DESY.

[Correlation between gaseous exchange rate, body temperature, and mitochondrial protein content in the liver of mice].

PubMed

Muradian, Kh K; Utko, N O; Mozzhukhina, T H; Pishel', I M; Litoshenko, O Ia; Bezrukov, V V; Fraĭfel'd, V E

2002-01-01

Correlative and regressive relations between the gaseous exchange, thermoregulation and mitochondrial protein content were analyzed by two- and three-dimensional statistics in mice. It has been shown that the pair wise linear methods of analysis did not reveal any significant correlation between the parameters under exploration. However, it became evident at three-dimensional and non-linear plotting for which the coefficients of multivariable correlation reached and even exceeded 0.7-0.8. The calculations based on partial differentiation of the multivariable regression equations allow to conclude that at certain values of VO2, VCO2 and body temperature negative relations between the systems of gaseous exchange and thermoregulation become dominating.

Evaluation to determine the caries remineralization potential of three dentifrices: An in vitro study

PubMed Central

Balakrishnan, Arun; Jonathan, R; Benin, P; Kuumar, Arvind

2013-01-01

Aim: The aim of this study was to evaluate the remineralizing potential of three different remineralizing agents (GC tooth Mousse, Clinpro tooth crθme and SHY-NM) on demineralized tooth surfaces using micro CT and microhardness. Materials and Methods: Forty five freshly extracted mandibular premolars were collected and enamel specimens were prepared. The samples were assigned to three groups with fifteen specimens in each group. The specimens were then demineralized using McInne's demineralizing solution in two cycles. After that, remineralization was carried out in two cycles for 30 days using Casein phosphopeptide - Amorphous calcium phosphate (CPP - ACP), 0.21% sodium fluoride - Tricalcium phosphate (f-TCP) and Calcium Sodium Phosphosilicate (CSP) containing tooth pastes for groups I, II, III respectively. The specimens were evaluated for Linear attenuation co-efficient using micro CT (Scanco™) and Vicker's Micro Hardness (Schimadzu™) testing at different time periods. The results were tabulated and statistically analysed. Results: It was observed that all the three remineralizing agents used in the study significantly increased the Linear Attenuation Co-efficient and Vicker's hardness number values of the enamel specimens following 15 days and 30 days application. Conclusion: CPP – ACP showed the better remineralizing potential than the other two agents and there was no statistical significant difference between f-TCP and CSP groups. PMID:23956545

Patterns of shading tolerance determined from experimental ...

EPA Pesticide Factsheets

An extensive review of the experimental literature on seagrass shading evaluated the relationship between experimental light reductions, duration of experiment and seagrass response metrics to determine whether there were consistent statistical patterns. There were highly significant linear relationships of both percent biomass and percent shoot density reduction versus percent light reduction (versus controls), although unexplained variation in the data were high. Duration of exposure affected extent of response for both metrics, but was more clearly a factor in biomass response. Both biomass and shoot density showed linear responses to duration of light reduction for treatments 60%. Unexplained variation was again high, and greater for shoot density than biomass. With few exceptions, regressions of both biomass and shoot density on light reduction for individual species and for genera were statistically significant, but also tended to show high degrees of variability in data. Multivariate regressions that included both percent light reduction and duration of reduction as dependent variables increased the percentage of variation explained in almost every case. Analysis of response data by seagrass life history category (Colonizing, Opportunistic, Persistent) did not yield clearly separate response relationships in most cases. Biomass tended to show somewhat less variation in response to light reduction than shoot density, and of the two, may be the prefe

Evaluation of systemic markers of inflammation in atomic-bomb survivors with special reference to radiation and age effects.

PubMed

Hayashi, Tomonori; Morishita, Yukari; Khattree, Ravindra; Misumi, Munechika; Sasaki, Keiko; Hayashi, Ikue; Yoshida, Kengo; Kajimura, Junko; Kyoizumi, Seishi; Imai, Kazue; Kusunoki, Yoichiro; Nakachi, Kei

2012-11-01

Past exposure to atomic bomb (A-bomb) radiation has exerted various long-lasting deleterious effects on the health of survivors. Some of these effects are seen even after >60 yr. In this study, we evaluated the subclinical inflammatory status of 442 A-bomb survivors, in terms of 8 inflammation-related cytokines or markers, comprised of plasma levels of reactive oxygen species (ROS), interleukin (IL)-6, tumor necrosis factor α (TNF-α), C-reactive protein (CRP), IL-4, IL-10, and immunoglobulins, and erythrocyte sedimentation rate (ESR). The effects of past radiation exposure and natural aging on these markers were individually assessed and compared. Next, to assess the biologically significant relationship between inflammation and radiation exposure or aging, which was masked by the interrelationship of those cytokines/markers, we used multivariate statistical analyses and evaluated the systemic markers of inflammation as scores being calculated by linear combinations of selected cytokines and markers. Our results indicate that a linear combination of ROS, IL-6, CRP, and ESR generated a score that was the most indicative of inflammation and revealed clear dependences on radiation dose and aging that were found to be statistically significant. The results suggest that collectively, radiation exposure, in conjunction with natural aging, may enhance the persistent inflammatory status of A-bomb survivors.

Ab initio multiple cloning simulations of pyrrole photodissociation: TKER spectra and velocity map imaging

DOE PAGES

Makhov, Dmitry V.; Saita, Kenichiro; Martinez, Todd J.; ...

2014-12-11

In this study, we report a detailed computational simulation of the photodissociation of pyrrole using the ab initio Multiple Cloning (AIMC) method implemented within MOLPRO. The efficiency of the AIMC implementation, employing train basis sets, linear approximation for matrix elements, and Ehrenfest configuration cloning, allows us to accumulate significant statistics. We calculate and analyze the total kinetic energy release (TKER) spectrum and Velocity Map Imaging (VMI) of pyrrole and compare the results directly with experimental measurements. Both the TKER spectrum and the structure of the velocity map image (VMI) are well reproduced. Previously, it has been assumed that the isotropicmore » component of the VMI arises from long time statistical dissociation. Instead, our simulations suggest that ultrafast dynamics contributes significantly to both low and high energy portions of the TKER spectrum.« less

Ab initio multiple cloning simulations of pyrrole photodissociation: TKER spectra and velocity map imaging

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

Makhov, Dmitry V.; Saita, Kenichiro; Martinez, Todd J.

In this study, we report a detailed computational simulation of the photodissociation of pyrrole using the ab initio Multiple Cloning (AIMC) method implemented within MOLPRO. The efficiency of the AIMC implementation, employing train basis sets, linear approximation for matrix elements, and Ehrenfest configuration cloning, allows us to accumulate significant statistics. We calculate and analyze the total kinetic energy release (TKER) spectrum and Velocity Map Imaging (VMI) of pyrrole and compare the results directly with experimental measurements. Both the TKER spectrum and the structure of the velocity map image (VMI) are well reproduced. Previously, it has been assumed that the isotropicmore » component of the VMI arises from long time statistical dissociation. Instead, our simulations suggest that ultrafast dynamics contributes significantly to both low and high energy portions of the TKER spectrum.« less

The Statistics of Visual Representation

NASA Technical Reports Server (NTRS)

Jobson, Daniel J.; Rahman, Zia-Ur; Woodell, Glenn A.

2002-01-01

The experience of retinex image processing has prompted us to reconsider fundamental aspects of imaging and image processing. Foremost is the idea that a good visual representation requires a non-linear transformation of the recorded (approximately linear) image data. Further, this transformation appears to converge on a specific distribution. Here we investigate the connection between numerical and visual phenomena. Specifically the questions explored are: (1) Is there a well-defined consistent statistical character associated with good visual representations? (2) Does there exist an ideal visual image? And (3) what are its statistical properties?

Random forests in non-invasive sensorimotor rhythm brain-computer interfaces: a practical and convenient non-linear classifier.

PubMed

Steyrl, David; Scherer, Reinhold; Faller, Josef; Müller-Putz, Gernot R

2016-02-01

There is general agreement in the brain-computer interface (BCI) community that although non-linear classifiers can provide better results in some cases, linear classifiers are preferable. Particularly, as non-linear classifiers often involve a number of parameters that must be carefully chosen. However, new non-linear classifiers were developed over the last decade. One of them is the random forest (RF) classifier. Although popular in other fields of science, RFs are not common in BCI research. In this work, we address three open questions regarding RFs in sensorimotor rhythm (SMR) BCIs: parametrization, online applicability, and performance compared to regularized linear discriminant analysis (LDA). We found that the performance of RF is constant over a large range of parameter values. We demonstrate - for the first time - that RFs are applicable online in SMR-BCIs. Further, we show in an offline BCI simulation that RFs statistically significantly outperform regularized LDA by about 3%. These results confirm that RFs are practical and convenient non-linear classifiers for SMR-BCIs. Taking into account further properties of RFs, such as independence from feature distributions, maximum margin behavior, multiclass and advanced data mining capabilities, we argue that RFs should be taken into consideration for future BCIs.

OPR-PPR, a Computer Program for Assessing Data Importance to Model Predictions Using Linear Statistics

USGS Publications Warehouse

Tonkin, Matthew J.; Tiedeman, Claire; Ely, D. Matthew; Hill, Mary C.

2007-01-01

The OPR-PPR program calculates the Observation-Prediction (OPR) and Parameter-Prediction (PPR) statistics that can be used to evaluate the relative importance of various kinds of data to simulated predictions. The data considered fall into three categories: (1) existing observations, (2) potential observations, and (3) potential information about parameters. The first two are addressed by the OPR statistic; the third is addressed by the PPR statistic. The statistics are based on linear theory and measure the leverage of the data, which depends on the location, the type, and possibly the time of the data being considered. For example, in a ground-water system the type of data might be a head measurement at a particular location and time. As a measure of leverage, the statistics do not take into account the value of the measurement. As linear measures, the OPR and PPR statistics require minimal computational effort once sensitivities have been calculated. Sensitivities need to be calculated for only one set of parameter values; commonly these are the values estimated through model calibration. OPR-PPR can calculate the OPR and PPR statistics for any mathematical model that produces the necessary OPR-PPR input files. In this report, OPR-PPR capabilities are presented in the context of using the ground-water model MODFLOW-2000 and the universal inverse program UCODE_2005. The method used to calculate the OPR and PPR statistics is based on the linear equation for prediction standard deviation. Using sensitivities and other information, OPR-PPR calculates (a) the percent increase in the prediction standard deviation that results when one or more existing observations are omitted from the calibration data set; (b) the percent decrease in the prediction standard deviation that results when one or more potential observations are added to the calibration data set; or (c) the percent decrease in the prediction standard deviation that results when potential information on one or more parameters is added.

OPLS statistical model versus linear regression to assess sonographic predictors of stroke prognosis.

PubMed

Vajargah, Kianoush Fathi; Sadeghi-Bazargani, Homayoun; Mehdizadeh-Esfanjani, Robab; Savadi-Oskouei, Daryoush; Farhoudi, Mehdi

2012-01-01

The objective of the present study was to assess the comparable applicability of orthogonal projections to latent structures (OPLS) statistical model vs traditional linear regression in order to investigate the role of trans cranial doppler (TCD) sonography in predicting ischemic stroke prognosis. The study was conducted on 116 ischemic stroke patients admitted to a specialty neurology ward. The Unified Neurological Stroke Scale was used once for clinical evaluation on the first week of admission and again six months later. All data was primarily analyzed using simple linear regression and later considered for multivariate analysis using PLS/OPLS models through the SIMCA P+12 statistical software package. The linear regression analysis results used for the identification of TCD predictors of stroke prognosis were confirmed through the OPLS modeling technique. Moreover, in comparison to linear regression, the OPLS model appeared to have higher sensitivity in detecting the predictors of ischemic stroke prognosis and detected several more predictors. Applying the OPLS model made it possible to use both single TCD measures/indicators and arbitrarily dichotomized measures of TCD single vessel involvement as well as the overall TCD result. In conclusion, the authors recommend PLS/OPLS methods as complementary rather than alternative to the available classical regression models such as linear regression.

Skillful prediction of hot temperature extremes over the source region of ancient Silk Road.

PubMed

Zhang, Jingyong; Yang, Zhanmei; Wu, Lingyun

2018-04-27

The source region of ancient Silk Road (SRASR) in China, a region of around 150 million people, faces a rapidly increased risk of extreme heat in summer. In this study, we develop statistical models to predict summer hot temperature extremes over the SRASR based on a timescale decomposition approach. Results show that after removing the linear trends, the inter-annual components of summer hot days and heatwaves over the SRASR are significantly related with those of spring soil temperature over Central Asia and sea surface temperature over Northwest Atlantic while their inter-decadal components are closely linked to those of spring East Pacific/North Pacific pattern and Atlantic Multidecadal Oscillation for 1979-2016. The physical processes involved are also discussed. Leave-one-out cross-validation for detrended 1979-2016 time series indicates that the statistical models based on identified spring predictors can predict 47% and 57% of the total variances of summer hot days and heatwaves averaged over the SRASR, respectively. When the linear trends are put back, the prediction skills increase substantially to 64% and 70%. Hindcast experiments for 2012-2016 show high skills in predicting spatial patterns of hot temperature extremes over the SRASR. The statistical models proposed herein can be easily applied to operational seasonal forecasting.

Analysis and prediction of flow from local source in a river basin using a Neuro-fuzzy modeling tool.

PubMed

Aqil, Muhammad; Kita, Ichiro; Yano, Akira; Nishiyama, Soichi

2007-10-01

Traditionally, the multiple linear regression technique has been one of the most widely used models in simulating hydrological time series. However, when the nonlinear phenomenon is significant, the multiple linear will fail to develop an appropriate predictive model. Recently, neuro-fuzzy systems have gained much popularity for calibrating the nonlinear relationships. This study evaluated the potential of a neuro-fuzzy system as an alternative to the traditional statistical regression technique for the purpose of predicting flow from a local source in a river basin. The effectiveness of the proposed identification technique was demonstrated through a simulation study of the river flow time series of the Citarum River in Indonesia. Furthermore, in order to provide the uncertainty associated with the estimation of river flow, a Monte Carlo simulation was performed. As a comparison, a multiple linear regression analysis that was being used by the Citarum River Authority was also examined using various statistical indices. The simulation results using 95% confidence intervals indicated that the neuro-fuzzy model consistently underestimated the magnitude of high flow while the low and medium flow magnitudes were estimated closer to the observed data. The comparison of the prediction accuracy of the neuro-fuzzy and linear regression methods indicated that the neuro-fuzzy approach was more accurate in predicting river flow dynamics. The neuro-fuzzy model was able to improve the root mean square error (RMSE) and mean absolute percentage error (MAPE) values of the multiple linear regression forecasts by about 13.52% and 10.73%, respectively. Considering its simplicity and efficiency, the neuro-fuzzy model is recommended as an alternative tool for modeling of flow dynamics in the study area.

Significant Association of Urinary Toxic Metals and Autism-Related Symptoms—A Nonlinear Statistical Analysis with Cross Validation

PubMed Central

Adams, James; Kruger, Uwe; Geis, Elizabeth; Gehn, Eva; Fimbres, Valeria; Pollard, Elena; Mitchell, Jessica; Ingram, Julie; Hellmers, Robert; Quig, David; Hahn, Juergen

2017-01-01

Introduction A number of previous studies examined a possible association of toxic metals and autism, and over half of those studies suggest that toxic metal levels are different in individuals with Autism Spectrum Disorders (ASD). Additionally, several studies found that those levels correlate with the severity of ASD. Methods In order to further investigate these points, this paper performs the most detailed statistical analysis to date of a data set in this field. First morning urine samples were collected from 67 children and adults with ASD and 50 neurotypical controls of similar age and gender. The samples were analyzed to determine the levels of 10 urinary toxic metals (UTM). Autism-related symptoms were assessed with eleven behavioral measures. Statistical analysis was used to distinguish participants on the ASD spectrum and neurotypical participants based upon the UTM data alone. The analysis also included examining the association of autism severity with toxic metal excretion data using linear and nonlinear analysis. “Leave-one-out” cross-validation was used to ensure statistical independence of results. Results and Discussion Average excretion levels of several toxic metals (lead, tin, thallium, antimony) were significantly higher in the ASD group. However, ASD classification using univariate statistics proved difficult due to large variability, but nonlinear multivariate statistical analysis significantly improved ASD classification with Type I/II errors of 15% and 18%, respectively. These results clearly indicate that the urinary toxic metal excretion profiles of participants in the ASD group were significantly different from those of the neurotypical participants. Similarly, nonlinear methods determined a significantly stronger association between the behavioral measures and toxic metal excretion. The association was strongest for the Aberrant Behavior Checklist (including subscales on Irritability, Stereotypy, Hyperactivity, and Inappropriate Speech), but significant associations were found for UTM with all eleven autism-related assessments with cross-validation R2 values ranging from 0.12–0.48. PMID:28068407

Enhancing the Biological Relevance of Secretome-Based Proteomics by Linking Tumor Cell Proliferation and Protein Secretion.

PubMed

Gregori, Josep; Méndez, Olga; Katsila, Theodora; Pujals, Mireia; Salvans, Cándida; Villarreal, Laura; Arribas, Joaquin; Tabernero, Josep; Sánchez, Alex; Villanueva, Josep

2014-07-15

Secretome profiling has become a methodology of choice for the identification of tumor biomarkers. We hypothesized that due to the dynamic nature of secretomes cellular perturbations could affect their composition but also change the global amount of protein secreted per cell. We confirmed our hypothesis by measuring the levels of secreted proteins taking into account the amount of proteome produced per cell. Then, we established a correlation between cell proliferation and protein secretion that explained the observed changes in global protein secretion. Next, we implemented a normalization correcting the statistical results of secretome studies by the global protein secretion of cells into a generalized linear model (GLM). The application of the normalization to two biological perturbations on tumor cells resulted in drastic changes in the list of statistically significant proteins. Furthermore, we found that known epithelial-to-mesenchymal transition (EMT) effectors were only statistically significant when the normalization was applied. Therefore, the normalization proposed here increases the sensitivity of statistical tests by increasing the number of true-positives. From an oncology perspective, the correlation between protein secretion and cellular proliferation suggests that slow-growing tumors could have high-protein secretion rates and consequently contribute strongly to tumor paracrine signaling.

Cognitive predictors of balance in Parkinson's disease.

PubMed

Fernandes, Ângela; Mendes, Andreia; Rocha, Nuno; Tavares, João Manuel R S

2016-06-01

Postural instability is one of the most incapacitating symptoms of Parkinson's disease (PD) and appears to be related to cognitive deficits. This study aims to determine the cognitive factors that can predict deficits in static and dynamic balance in individuals with PD. A sociodemographic questionnaire characterized 52 individuals with PD for this work. The Trail Making Test, Rule Shift Cards Test, and Digit Span Test assessed the executive functions. The static balance was assessed using a plantar pressure platform, and dynamic balance was based on the Timed Up and Go Test. The results were statistically analysed using SPSS Statistics software through linear regression analysis. The results show that a statistically significant model based on cognitive outcomes was able to explain the variance of motor variables. Also, the explanatory value of the model tended to increase with the addition of individual and clinical variables, although the resulting model was not statistically significant The model explained 25-29% of the variability of the Timed Up and Go Test, while for the anteroposterior displacement it was 23-34%, and for the mediolateral displacement it was 24-39%. From the findings, we conclude that the cognitive performance, especially the executive functions, is a predictor of balance deficit in individuals with PD.

The seasonal response of the Held-Suarez climate model to prescribed ocean temperature anomalies. II - Dynamical analysis

NASA Technical Reports Server (NTRS)

Phillips, T. J.

1984-01-01

The heating associated with equatorial, subtropical, and midlatitude ocean temperature anamolies in the Held-Suarez climate model is analyzed. The local and downstream response to the anomalies is analyzed, first by examining the seasonal variation in heating associated with each ocean temperature anomaly, and then by combining knowledge of the heating with linear dynamical theory in order to develop a more comprehensive explanation of the seasonal variation in local and downstream atmospheric response to each anomaly. The extent to which the linear theory of propagating waves can assist the interpretation of the remote cross-latitudinal response of the model to the ocean temperature anomalies is considered. Alternative hypotheses that attempt to avoid the contradictions inherent in a strict application of linear theory are investigated, and the impact of sampling errors on the assessment of statistical significance is also examined.

Analysis of reciprocal creatinine plots by two-phase linear regression.

PubMed

Rowe, P A; Richardson, R E; Burton, P R; Morgan, A G; Burden, R P

1989-01-01

The progression of renal diseases is often monitored by the serial measurement of plasma creatinine. The slope of the linear relation that is frequently found between the reciprocal of creatinine concentration and time delineates the rate of change in renal function. Minor changes in slope, perhaps indicating response to therapeutic intervention, can be difficult to identify and yet be of clinical importance. We describe the application of two-phase linear regression to identify and characterise changes in slope using a microcomputer. The method fits two intersecting lines to the data by computing a least-squares estimate of the position of the slope change and its 95% confidence limits. This avoids the potential bias of fixing the change at a preconceived time corresponding with an alteration in treatment. The program then evaluates the statistical and clinical significance of the slope change and produces a graphical output to aid interpretation.

Relevant reduction effect with a modified thermoplastic mask of rotational error for glottic cancer in IMRT

NASA Astrophysics Data System (ADS)

Jung, Jae Hong; Jung, Joo-Young; Cho, Kwang Hwan; Ryu, Mi Ryeong; Bae, Sun Hyun; Moon, Seong Kwon; Kim, Yong Ho; Choe, Bo-Young; Suh, Tae Suk

2017-02-01

The purpose of this study was to analyze the glottis rotational error (GRE) by using a thermoplastic mask for patients with the glottic cancer undergoing intensity-modulated radiation therapy (IMRT). We selected 20 patients with glottic cancer who had received IMRT by using the tomotherapy. The image modalities with both kilovoltage computed tomography (planning kVCT) and megavoltage CT (daily MVCT) images were used for evaluating the error. Six anatomical landmarks in the image were defined to evaluate a correlation between the absolute GRE (°) and the length of contact with the underlying skin of the patient by the mask (mask, mm). We also statistically analyzed the results by using the Pearson's correlation coefficient and a linear regression analysis ( P <0.05). The mask and the absolute GRE were verified to have a statistical correlation ( P < 0.01). We found a statistical significance for each parameter in the linear regression analysis (mask versus absolute roll: P = 0.004 [ P < 0.05]; mask versus 3D-error: P = 0.000 [ P < 0.05]). The range of the 3D-errors with contact by the mask was from 1.2% - 39.7% between the maximumand no-contact case in this study. A thermoplastic mask with a tight, increased contact area may possibly contribute to the uncertainty of the reproducibility as a variation of the absolute GRE. Thus, we suggest that a modified mask, such as one that covers only the glottis area, can significantly reduce the patients' setup errors during the treatment.

[Application of SAS macro to evaluated multiplicative and additive interaction in logistic and Cox regression in clinical practices].

PubMed

Nie, Z Q; Ou, Y Q; Zhuang, J; Qu, Y J; Mai, J Z; Chen, J M; Liu, X Q

2016-05-01

Conditional logistic regression analysis and unconditional logistic regression analysis are commonly used in case control study, but Cox proportional hazard model is often used in survival data analysis. Most literature only refer to main effect model, however, generalized linear model differs from general linear model, and the interaction was composed of multiplicative interaction and additive interaction. The former is only statistical significant, but the latter has biological significance. In this paper, macros was written by using SAS 9.4 and the contrast ratio, attributable proportion due to interaction and synergy index were calculated while calculating the items of logistic and Cox regression interactions, and the confidence intervals of Wald, delta and profile likelihood were used to evaluate additive interaction for the reference in big data analysis in clinical epidemiology and in analysis of genetic multiplicative and additive interactions.

Comparison between Linear and Nonlinear Regression in a Laboratory Heat Transfer Experiment

ERIC Educational Resources Information Center

Gonçalves, Carine Messias; Schwaab, Marcio; Pinto, José Carlos

2013-01-01

In order to interpret laboratory experimental data, undergraduate students are used to perform linear regression through linearized versions of nonlinear models. However, the use of linearized models can lead to statistically biased parameter estimates. Even so, it is not an easy task to introduce nonlinear regression and show for the students…

Introducing Linear Functions: An Alternative Statistical Approach

ERIC Educational Resources Information Center

Nolan, Caroline; Herbert, Sandra

2015-01-01

The introduction of linear functions is the turning point where many students decide if mathematics is useful or not. This means the role of parameters and variables in linear functions could be considered to be "threshold concepts". There is recognition that linear functions can be taught in context through the exploration of linear…

Surface Ozone Variability and Trends over the South African Highveld from 1990 to 2007

NASA Technical Reports Server (NTRS)

Balashov, Nikolay V.; Thompson, Anne M.; Piketh, Stuart J.; Langerman, Kristy E.

2014-01-01

Surface ozone is a secondary air pollutant formed from reactions between nitrogen oxides (NOx = NO + NO2) and volatile organic compounds in the presence of sunlight. In this work we examine effects of the climate pattern known as the El Niño-Southern Oscillation (ENSO) and NOx variability on surface ozone from 1990 to 2007 over the South African Highveld, a heavily populated region in South Africa with numerous industrial facilities. Over summer and autumn (December-May) on the Highveld, El Niño, as signified by positive sea surface temperature (SST) anomalies over the central Pacific Ocean, is typically associated with drier and warmer than normal conditions favoring ozone formation. Conversely, La Niña, or negative SST anomalies over the central Pacific Ocean, is typically associated with cloudier and above normal rainfall conditions, hindering ozone production. We use a generalized regression model to identify any linear dependence that the Highveld ozone, measured at five air quality monitoring stations, may have on ENSO and NOx. Our results indicate that four out of the five stations exhibit a statistically significant sensitivity to ENSO at some point over the December-May period where El Niño amplifies ozone formation and La Niña reduces ozone formation. Three out of the five stations reveal statistically significant sensitivity to NOx variability, primarily in winter and spring. Accounting for ENSO and NOx effects throughout the study period of 18 years, two stations exhibit statistically significant negative ozone trends in spring, one station displays a statistically significant positive trend in August, and two stations show no statistically significant change in surface ozone.

Statistical Signal Models and Algorithms for Image Analysis

DTIC Science & Technology

1984-10-25

In this report, two-dimensional stochastic linear models are used in developing algorithms for image analysis such as classification, segmentation, and object detection in images characterized by textured backgrounds. These models generate two-dimensional random processes as outputs to which statistical inference procedures can naturally be applied. A common thread throughout our algorithms is the interpretation of the inference procedures in terms of linear prediction

Sequential CFAR detectors using a dead-zone limiter

NASA Astrophysics Data System (ADS)

Tantaratana, Sawasd

1990-09-01

The performances of some proposed sequential constant-false-alarm-rate (CFAR) detectors are evaluated. The observations are passed through a dead-zone limiter, the output of which is -1, 0, or +1, depending on whether the input is less than -c, between -c and c, or greater than c, where c is a constant. The test statistic is the sum of the outputs. The test is performed on a reduced set of data (those with absolute value larger than c), with the test statistic being the sum of the signs of the reduced set of data. Both constant and linear boundaries are considered. Numerical results show a significant reduction of the average number of observations needed to achieve the same false alarm and detection probabilities as a fixed-sample-size CFAR detector using the same kind of test statistic.

Quantitatively measured tremor in hand-arm vibration-exposed workers.

PubMed

Edlund, Maria; Burström, Lage; Hagberg, Mats; Lundström, Ronnie; Nilsson, Tohr; Sandén, Helena; Wastensson, Gunilla

2015-04-01

The aim of the present study was to investigate the possible increase in hand tremor in relation to hand-arm vibration (HAV) exposure in a cohort of exposed and unexposed workers. Participants were 178 male workers with or without exposure to HAV. The study is cross-sectional regarding the outcome of tremor and has a longitudinal design with respect to exposure. The dose of HAV exposure was collected via questionnaires and measurements at several follow-ups. The CATSYS Tremor Pen(®) was used for measuring postural tremor. Multiple linear regression methods were used to analyze associations between different tremor variables and HAV exposure, along with predictor variables with biological relevance. There were no statistically significant associations between the different tremor variables and cumulative HAV or current exposure. Age was a statistically significant predictor of variation in tremor outcomes for three of the four tremor variables, whereas nicotine use was a statistically significant predictor of either left or right hand or both hands for all four tremor variables. In the present study, there was no evidence of an exposure-response association between HAV exposure and measured postural tremor. Increase in age and nicotine use appeared to be the strongest predictors of tremor.

A methodology for design of a linear referencing system for surface transportation

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

Vonderohe, A.; Hepworth, T.

1997-06-01

The transportation community has recently placed significant emphasis on development of data models, procedural standards, and policies for management of linearly-referenced data. There is an Intelligent Transportation Systems initiative underway to create a spatial datum for location referencing in one, two, and three dimensions. Most recently, a call was made for development of a unified linear reference system to support public, private, and military surface transportation needs. A methodology for design of the linear referencing system was developed from geodetic engineering principles and techniques used for designing geodetic control networks. The method is founded upon the law of propagation ofmore » random error and the statistical analysis of systems of redundant measurements, used to produce best estimates for unknown parameters. A complete mathematical development is provided. Example adjustments of linear distance measurement systems are included. The classical orders of design are discussed with regard to the linear referencing system. A simple design example is provided. A linear referencing system designed and analyzed with this method will not only be assured of meeting the accuracy requirements of users, it will have the potential for supporting delivery of error estimates along with the results of spatial analytical queries. Modeling considerations, alternative measurement methods, implementation strategies, maintenance issues, and further research needs are discussed. Recommendations are made for further advancement of the unified linear referencing system concept.« less

The effect of pre-cure bracket movement on shear bond strength during placement of orthodontic brackets, an in vitro study.

PubMed

Tam, Byron; Bollu, Prashanti; Chaudhry, Kishore; Subramani, Karthikeyan

2017-10-01

The purpose of this study was to determine the influence of linear and rotational pre-cure bracket displacement during the bonding procedure on shear bond strength (SBS) of orthodontic brackets. Stainless steel orthodontic premolar brackets were bonded to the buccal surfaces of 50 human pre-molars with a conventional two-step bonding protocol. Extracted human pre-molars were divided into 5 groups (n=10/group). In the Control Group, the brackets were bonded with no pre-cure bracket displacement or rotation. The Rotation Group was bonded with 45 degrees of pre-cure rotation. The Displacement Group was bonded with 2mm pre-cure linear displacement. The Rotation-Displacement Group was bonded with pre-cure movements of 45º counter-clockwise rotation and 2mm displacement. The Slippage Group was bonded with 2mm each of mesial and distal pre-cure linear displacement. Photo-activation was carried out on the lateral sides of the bracket. Shear debonding force was measured, 24 hours after initial bonding, with an Instron universal testing machine using a knife-edged chisel. Data was analyzed using one-way ANOVA test. Adhesive Remnant Index (ARI) was scored under 15x magnification. The ARI data was analyzed using the Chi-square test ( p -value < 0.05). No statistically significant differences were detected among the control and experimental groups ( p = 0.331). The rotation and displacement group showed the highest mean SBS than all other groups. Mean SBS for all groups were above the clinically acceptable range. No statistically significant differences were detected in ARI scores among groups ( p = 0.071). Linear and rotational pre-cure bracket displacements do not appear to effect the shear bond strength of orthodontic brackets. Key words: Shear bond strength, orthodontic bracket, displacement, rotation, adhesive remnant index, pre-cure movement.

Advanced Statistical Analyses to Reduce Inconsistency of Bond Strength Data.

PubMed

Minamino, T; Mine, A; Shintani, A; Higashi, M; Kawaguchi-Uemura, A; Kabetani, T; Hagino, R; Imai, D; Tajiri, Y; Matsumoto, M; Yatani, H

2017-11-01

This study was designed to clarify the interrelationship of factors that affect the value of microtensile bond strength (µTBS), focusing on nondestructive testing by which information of the specimens can be stored and quantified. µTBS test specimens were prepared from 10 noncarious human molars. Six factors of µTBS test specimens were evaluated: presence of voids at the interface, X-ray absorption coefficient of resin, X-ray absorption coefficient of dentin, length of dentin part, size of adhesion area, and individual differences of teeth. All specimens were observed nondestructively by optical coherence tomography and micro-computed tomography before µTBS testing. After µTBS testing, the effect of these factors on µTBS data was analyzed by the general linear model, linear mixed effects regression model, and nonlinear regression model with 95% confidence intervals. By the general linear model, a significant difference in individual differences of teeth was observed ( P < 0.001). A significantly positive correlation was shown between µTBS and length of dentin part ( P < 0.001); however, there was no significant nonlinearity ( P = 0.157). Moreover, a significantly negative correlation was observed between µTBS and size of adhesion area ( P = 0.001), with significant nonlinearity ( P = 0.014). No correlation was observed between µTBS and X-ray absorption coefficient of resin ( P = 0.147), and there was no significant nonlinearity ( P = 0.089). Additionally, a significantly positive correlation was observed between µTBS and X-ray absorption coefficient of dentin ( P = 0.022), with significant nonlinearity ( P = 0.036). A significant difference was also observed between the presence and absence of voids by linear mixed effects regression analysis. Our results showed correlations between various parameters of tooth specimens and µTBS data. To evaluate the performance of the adhesive more precisely, the effect of tooth variability and a method to reduce variation in bond strength values should also be considered.

Reanalysis of cancer mortality in Japanese A-bomb survivors exposed to low doses of radiation: bootstrap and simulation methods

PubMed Central

2009-01-01

Background The International Commission on Radiological Protection (ICRP) recommended annual occupational dose limit is 20 mSv. Cancer mortality in Japanese A-bomb survivors exposed to less than 20 mSv external radiation in 1945 was analysed previously, using a latency model with non-linear dose response. Questions were raised regarding statistical inference with this model. Methods Cancers with over 100 deaths in the 0 - 20 mSv subcohort of the 1950-1990 Life Span Study are analysed with Poisson regression models incorporating latency, allowing linear and non-linear dose response. Bootstrap percentile and Bias-corrected accelerated (BCa) methods and simulation of the Likelihood Ratio Test lead to Confidence Intervals for Excess Relative Risk (ERR) and tests against the linear model. Results The linear model shows significant large, positive values of ERR for liver and urinary cancers at latencies from 37 - 43 years. Dose response below 20 mSv is strongly non-linear at the optimal latencies for the stomach (11.89 years), liver (36.9), lung (13.6), leukaemia (23.66), and pancreas (11.86) and across broad latency ranges. Confidence Intervals for ERR are comparable using Bootstrap and Likelihood Ratio Test methods and BCa 95% Confidence Intervals are strictly positive across latency ranges for all 5 cancers. Similar risk estimates for 10 mSv (lagged dose) are obtained from the 0 - 20 mSv and 5 - 500 mSv data for the stomach, liver, lung and leukaemia. Dose response for the latter 3 cancers is significantly non-linear in the 5 - 500 mSv range. Conclusion Liver and urinary cancer mortality risk is significantly raised using a latency model with linear dose response. A non-linear model is strongly superior for the stomach, liver, lung, pancreas and leukaemia. Bootstrap and Likelihood-based confidence intervals are broadly comparable and ERR is strictly positive by bootstrap methods for all 5 cancers. Except for the pancreas, similar estimates of latency and risk from 10 mSv are obtained from the 0 - 20 mSv and 5 - 500 mSv subcohorts. Large and significant cancer risks for Japanese survivors exposed to less than 20 mSv external radiation from the atomic bombs in 1945 cast doubt on the ICRP recommended annual occupational dose limit. PMID:20003238

An Investigation of Lower Urinary Tract Symptoms in Women Aged 40 and Over.

PubMed

Sever, Neziha; Oskay, Umran

2017-01-01

The objective of this study was to determine lower urinary tract symptoms (LUTS) and associated risk factors in women aged 40 years and over. The study was carried out with a total of 312 women. The data were collected between 1 January 2009 and 30 July 2010. As research instruments, an interview form of 19 questions that questioned personal characteristics and was developed by researchers, and the Bristol Female Lower Urinary Tract Symptoms (BFLUTS) Questionnaire evaluating lower urinary tract symptoms were used. Linear regression analysis was used to detect associated risk factors. The rates of urgency, urinary incontinence, nocturia, and frequency symptoms were 61.5, 52.2, 18.9, and 25%, respectively. BFLUTS total scores increased with age, but the present study has detected no statistically significant differences (P > 0.05). BFLUTS scores of the women demonstrated statistically significant differences according to several risk factors including menopause status (P = 0.03), presence of chronic illness (P = 0.000), medicine use (P = 0.000), recurrent urinary tract infections (P = 0.000), body mass index (BMI) (P = 0.004), delivery number (P = 0.005) and chronic constipation (P = 0.002). Multiple linear regression analysis determined that frequent urinary tract infections, presence of chronic illness, chronic constipation, BMI and number of deliveries were significantly related to LUTS development. The most common LUTS was urgency in women aged 40 years and older. Recurrent urinary tract infection was determined as the most significant risk factor for LUTS, followed by chronic illness, chronic constipation, higher BMI and parity. © 2015 Wiley Publishing Asia Pty Ltd.

The effect of teaching medical ethics on medical students' moral reasoning.

PubMed

Self, D J; Wolinsky, F D; Baldwin, D C

1989-12-01

A study assessed the effect of incorporating medical ethics into the medical curriculum and the relative effects of two methods of implementing that curriculum, namely, lecture and case-study discussions. Results indicate a statistically significant increase (p less than or equal to .0001) in the level of moral reasoning of students exposed to the medical ethics course, regardless of format. Moreover, the unadjusted posttest scores indicated that the case-study method was significantly (p less than or equal to .03) more effective than the lecture method in increasing students' level of moral reasoning. When adjustment were made for the pretest scores, however, this difference was not statistically significant (p less than or equal to .18). Regression analysis by linear panel techniques revealed that age, gender, undergraduate grade-point average, and scores on the Medical College Admission Test were not related to the changes in moral-reasoning scores. All of the variance that could be explained was due to the students' being in one of the two experimental groups. In comparison with the control group, the change associated with each experimental format was statistically significant (lecture, p less than or equal to .004; case study, p less than or equal to .0001). Various explanations for these findings and their implications are given.

Sex differences in thickness, and folding developments throughout the cortex.

PubMed

Mutlu, A Kadir; Schneider, Maude; Debbané, Martin; Badoud, Deborah; Eliez, Stephan; Schaer, Marie

2013-11-15

While significant differences in male and female brain structures have commonly been reported, only a few studies have focused on the sex differences in the way the cortex matures over time. Here, we investigated cortical thickness maturation between the age of 6 to 30 years, using 209 longitudinally-acquired brain MRI scans. Significant sex differences in the trajectories of cortical thickness change with age were evidenced using non-linear mixed effects models. Similar statistical analyses were computed to quantify the differences between cortical gyrification changes with age in males and females. During adolescence, we observed a statistically significant higher rate of cortical thinning in females compared to males in the right temporal regions, the left temporoparietal junction and the left orbitofrontal cortex. This finding is interpreted as a faster maturation of the social brain areas in females. Concomitantly, statistically significant sex differences in cortical folding changes with age were observed only in one cluster of the right prefrontal regions, suggesting that the mechanisms underlying cortical thickness and gyrification changes with age are quite distinct. Sexual dimorphism in the developmental course of the cortical maturation may be associated with the different age of onset and clinical presentation of many psychiatric disorders between males and females. Copyright © 2013 Elsevier Inc. All rights reserved.

Image-analysis library

NASA Technical Reports Server (NTRS)

1980-01-01

MATHPAC image-analysis library is collection of general-purpose mathematical and statistical routines and special-purpose data-analysis and pattern-recognition routines for image analysis. MATHPAC library consists of Linear Algebra, Optimization, Statistical-Summary, Densities and Distribution, Regression, and Statistical-Test packages.

Binary recursive partitioning: background, methods, and application to psychology.

PubMed

Merkle, Edgar C; Shaffer, Victoria A

2011-02-01

Binary recursive partitioning (BRP) is a computationally intensive statistical method that can be used in situations where linear models are often used. Instead of imposing many assumptions to arrive at a tractable statistical model, BRP simply seeks to accurately predict a response variable based on values of predictor variables. The method outputs a decision tree depicting the predictor variables that were related to the response variable, along with the nature of the variables' relationships. No significance tests are involved, and the tree's 'goodness' is judged based on its predictive accuracy. In this paper, we describe BRP methods in a detailed manner and illustrate their use in psychological research. We also provide R code for carrying out the methods.

Radon balneotherapy and physical activity for osteoporosis prevention: a randomized, placebo-controlled intervention study.

PubMed

Winklmayr, Martina; Kluge, Christian; Winklmayr, Wolfgang; Küchenhoff, Helmut; Steiner, Martina; Ritter, Markus; Hartl, Arnulf

2015-03-01

Low-dose radon hyperthermia balneo treatment (LDRnHBT) is applied as a traditional measure in the non-pharmacological treatment of rheumatic diseases in Europe. During the last decades, the main approach of LDRnHBT was focused on the treatment of musculoskeletal disorders, but scientific evidence for the biological background of LDRnHBT is weak. Recently, evidence emerged that LDRnHBT influences bone metabolism. We investigated, whether combined LDRnHBT and exercise treatment has an impact on bone metabolism and quality of life in a study population in an age group at risk for developing osteoporosis. This randomized, double-blind, placebo-controlled trial comprised guided hiking tours and hyperthermia treatment in either radon thermal water (LDRnHBT) or radon-free thermal water (PlaceboHBT). Markers of bone metabolism, quality of life and somatic complaints were evaluated. Statistics was performed by linear regression and a linear mixed model analysis. Significant changes over time were observed for most analytes investigated as well as an improvement in self-assessed health in both groups. No significant impact from the LDRnHBT could be observed. After 6 months, the LDRnHBT group showed a slightly stronger reduction of the osteoclast stimulating protein receptor activator of nuclear kB-ligand compared to the PlaceboHBT group, indicating a possible trend. A combined hyperthermia balneo and exercise treatment has significant immediate and long-term effects on regulators of bone metabolism as well as somatic complaints. LDRnHBT and placeboHBT yielded statistically equal outcomes.

Estimating the impact of mineral aerosols on crop yields in food insecure regions using statistical crop models

NASA Astrophysics Data System (ADS)

Hoffman, A.; Forest, C. E.; Kemanian, A.

2016-12-01

A significant number of food-insecure nations exist in regions of the world where dust plays a large role in the climate system. While the impacts of common climate variables (e.g. temperature, precipitation, ozone, and carbon dioxide) on crop yields are relatively well understood, the impact of mineral aerosols on yields have not yet been thoroughly investigated. This research aims to develop the data and tools to progress our understanding of mineral aerosol impacts on crop yields. Suspended dust affects crop yields by altering the amount and type of radiation reaching the plant, modifying local temperature and precipitation. While dust events (i.e. dust storms) affect crop yields by depleting the soil of nutrients or by defoliation via particle abrasion. The impact of dust on yields is modeled statistically because we are uncertain which impacts will dominate the response on national and regional scales considered in this study. Multiple linear regression is used in a number of large-scale statistical crop modeling studies to estimate yield responses to various climate variables. In alignment with previous work, we develop linear crop models, but build upon this simple method of regression with machine-learning techniques (e.g. random forests) to identify important statistical predictors and isolate how dust affects yields on the scales of interest. To perform this analysis, we develop a crop-climate dataset for maize, soybean, groundnut, sorghum, rice, and wheat for the regions of West Africa, East Africa, South Africa, and the Sahel. Random forest regression models consistently model historic crop yields better than the linear models. In several instances, the random forest models accurately capture the temperature and precipitation threshold behavior in crops. Additionally, improving agricultural technology has caused a well-documented positive trend that dominates time series of global and regional yields. This trend is often removed before regression with traditional crop models, but likely at the cost of removing climate information. Our random forest models consistently discover the positive trend without removing any additional data. The application of random forests as a statistical crop model provides insight into understanding the impact of dust on yields in marginal food producing regions.

Assessing risk factors for periodontitis using regression

NASA Astrophysics Data System (ADS)

Lobo Pereira, J. A.; Ferreira, Maria Cristina; Oliveira, Teresa

2013-10-01

Multivariate statistical analysis is indispensable to assess the associations and interactions between different factors and the risk of periodontitis. Among others, regression analysis is a statistical technique widely used in healthcare to investigate and model the relationship between variables. In our work we study the impact of socio-demographic, medical and behavioral factors on periodontal health. Using regression, linear and logistic models, we can assess the relevance, as risk factors for periodontitis disease, of the following independent variables (IVs): Age, Gender, Diabetic Status, Education, Smoking status and Plaque Index. The multiple linear regression analysis model was built to evaluate the influence of IVs on mean Attachment Loss (AL). Thus, the regression coefficients along with respective p-values will be obtained as well as the respective p-values from the significance tests. The classification of a case (individual) adopted in the logistic model was the extent of the destruction of periodontal tissues defined by an Attachment Loss greater than or equal to 4 mm in 25% (AL≥4mm/≥25%) of sites surveyed. The association measures include the Odds Ratios together with the correspondent 95% confidence intervals.

Normalization Approaches for Removing Systematic Biases Associated with Mass Spectrometry and Label-Free Proteomics

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

Callister, Stephen J.; Barry, Richard C.; Adkins, Joshua N.

2006-02-01

Central tendency, linear regression, locally weighted regression, and quantile techniques were investigated for normalization of peptide abundance measurements obtained from high-throughput liquid chromatography-Fourier transform ion cyclotron resonance mass spectrometry (LC-FTICR MS). Arbitrary abundances of peptides were obtained from three sample sets, including a standard protein sample, two Deinococcus radiodurans samples taken from different growth phases, and two mouse striatum samples from control and methamphetamine-stressed mice (strain C57BL/6). The selected normalization techniques were evaluated in both the absence and presence of biological variability by estimating extraneous variability prior to and following normalization. Prior to normalization, replicate runs from each sample setmore » were observed to be statistically different, while following normalization replicate runs were no longer statistically different. Although all techniques reduced systematic bias, assigned ranks among the techniques revealed significant trends. For most LC-FTICR MS analyses, linear regression normalization ranked either first or second among the four techniques, suggesting that this technique was more generally suitable for reducing systematic biases.« less

Development of statistical linear regression model for metals from transportation land uses.

PubMed

Maniquiz, Marla C; Lee, Soyoung; Lee, Eunju; Kim, Lee-Hyung

2009-01-01

The transportation landuses possessing impervious surfaces such as highways, parking lots, roads, and bridges were recognized as the highly polluted non-point sources (NPSs) in the urban areas. Lots of pollutants from urban transportation are accumulating on the paved surfaces during dry periods and are washed-off during a storm. In Korea, the identification and monitoring of NPSs still represent a great challenge. Since 2004, the Ministry of Environment (MOE) has been engaged in several researches and monitoring to develop stormwater management policies and treatment systems for future implementation. The data over 131 storm events during May 2004 to September 2008 at eleven sites were analyzed to identify correlation relationships between particulates and metals, and to develop simple linear regression (SLR) model to estimate event mean concentration (EMC). Results indicate that there was no significant relationship between metals and TSS EMC. However, the SLR estimation models although not providing useful results are valuable indicators of high uncertainties that NPS pollution possess. Therefore, long term monitoring employing proper methods and precise statistical analysis of the data should be undertaken to eliminate these uncertainties.

[Visual field progression in glaucoma: cluster analysis].

PubMed

Bresson-Dumont, H; Hatton, J; Foucher, J; Fonteneau, M

2012-11-01

Visual field progression analysis is one of the key points in glaucoma monitoring, but distinction between true progression and random fluctuation is sometimes difficult. There are several different algorithms but no real consensus for detecting visual field progression. The trend analysis of global indices (MD, sLV) may miss localized deficits or be affected by media opacities. Conversely, point-by-point analysis makes progression difficult to differentiate from physiological variability, particularly when the sensitivity of a point is already low. The goal of our study was to analyse visual field progression with the EyeSuite™ Octopus Perimetry Clusters algorithm in patients with no significant changes in global indices or worsening of the analysis of pointwise linear regression. We analyzed the visual fields of 162 eyes (100 patients - 58 women, 42 men, average age 66.8 ± 10.91) with ocular hypertension or glaucoma. For inclusion, at least six reliable visual fields per eye were required, and the trend analysis (EyeSuite™ Perimetry) of visual field global indices (MD and SLV), could show no significant progression. The analysis of changes in cluster mode was then performed. In a second step, eyes with statistically significant worsening of at least one of their clusters were analyzed point-by-point with the Octopus Field Analysis (OFA). Fifty four eyes (33.33%) had a significant worsening in some clusters, while their global indices remained stable over time. In this group of patients, more advanced glaucoma was present than in stable group (MD 6.41 dB vs. 2.87); 64.82% (35/54) of those eyes in which the clusters progressed, however, had no statistically significant change in the trend analysis by pointwise linear regression. Most software algorithms for analyzing visual field progression are essentially trend analyses of global indices, or point-by-point linear regression. This study shows the potential role of analysis by clusters trend. However, for best results, it is preferable to compare the analyses of several tests in combination with morphologic exam. Copyright © 2012 Elsevier Masson SAS. All rights reserved.

Development of parallel line analysis criteria for recombinant adenovirus potency assay and definition of a unit of potency.

PubMed

Ogawa, Yasushi; Fawaz, Farah; Reyes, Candice; Lai, Julie; Pungor, Erno

2007-01-01

Parameter settings of a parallel line analysis procedure were defined by applying statistical analysis procedures to the absorbance data from a cell-based potency bioassay for a recombinant adenovirus, Adenovirus 5 Fibroblast Growth Factor-4 (Ad5FGF-4). The parallel line analysis was performed with a commercially available software, PLA 1.2. The software performs Dixon outlier test on replicates of the absorbance data, performs linear regression analysis to define linear region of the absorbance data, and tests parallelism between the linear regions of standard and sample. Width of Fiducial limit, expressed as a percent of the measured potency, was developed as a criterion for rejection of the assay data and to significantly improve the reliability of the assay results. With the linear range-finding criteria of the software set to a minimum of 5 consecutive dilutions and best statistical outcome, and in combination with the Fiducial limit width acceptance criterion of <135%, 13% of the assay results were rejected. With these criteria applied, the assay was found to be linear over the range of 0.25 to 4 relative potency units, defined as the potency of the sample normalized to the potency of Ad5FGF-4 standard containing 6 x 10(6) adenovirus particles/mL. The overall precision of the assay was estimated to be 52%. Without the application of Fiducial limit width criterion, the assay results were not linear over the range, and an overall precision of 76% was calculated from the data. An absolute unit of potency for the assay was defined by using the parallel line analysis procedure as the amount of Ad5FGF-4 that results in an absorbance value that is 121% of the average absorbance readings of the wells containing cells not infected with the adenovirus.

Arctic Sea Ice Variability and Trends, 1979-2006

NASA Technical Reports Server (NTRS)

Parkinson, Claire L.; Cavalieri, Donald J.

2008-01-01

Analysis of Arctic sea ice extents derived from satellite passive-microwave data for the 28 years, 1979-2006 yields an overall negative trend of -45,100 +/- 4,600 km2/yr (-3.7 +/- 0.4%/decade) in the yearly averages, with negative ice-extent trends also occurring for each of the four seasons and each of the 12 months. For the yearly averages the largest decreases occur in the Kara and Barents Seas and the Arctic Ocean, with linear least squares slopes of -10,600 +/- 2,800 km2/yr (-7.4 +/- 2.0%/decade) and -10,100 +/- 2,200 km2/yr (-1.5 +/- 0.3%/decade), respectively, followed by Baffin Bay/Labrador Sea, with a slope of -8,000 +/- 2,000 km2/yr) -9.0 +/- 2.3%/decade), the Greenland Sea, with a slope of -7,000 +/- 1,400 km2/yr (-9.3 +/- 1.9%/decade), and Hudson Bay, with a slope of -4,500 +/- 900 km2/yr (-5.3 +/- 1.1%/decade). These are all statistically significant decreases at a 99% confidence level. The Seas of Okhotsk and Japan also have a statistically significant ice decrease, although at a 95% confidence level, and the three remaining regions, the Bering Sea, Canadian Archipelago, and Gulf of St. Lawrence, have negative slopes that are not statistically significant. The 28-year trends in ice areas for the Northern Hemisphere total are also statistically significant and negative in each season, each month, and for the yearly averages.

Effects of selective serotonin reuptake inhibitors on thought-action fusion, metacognitions, and thought suppression in obsessive-compulsive disorder.

PubMed

Besiroglu, Lutfullah; Çetinkaya, Nuralay; Selvi, Yavuz; Atli, Abdullah

2011-01-01

We aimed to assess whether cognitive processes change over time in patients with obsessive-compulsive disorder (OCD) receiving selective serotonin reuptake inhibitors without cognitive behavioral therapy and to investigate the factors associated with probable cognitive changes. During the 16 weeks of the study, 55 patients who met the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, criteria for OCD received open-label treatment with sertraline (100-200 mg/d) or fluoxetine (40-80 mg/d) and were assessed using the Yale-Brown Obsessive-Compulsive Scale, Beck Depression Inventory (BDI), Thought-Action Fusion Scale (TAFS), Metacognitions Questionnaire (MCQ-30), and White Bear Suppression Inventory (WBSI). The Yale-Brown Obsessive-Compulsive Scale (P < .001), BDI (P < .001), TAFS morality (P < .005), MCQ-30 (P < .01), and WBSI (P < .005) scores at follow-up were significantly lower than baseline scores. When we excluded OCD patients with depressive disorder (n = 12), statistical significance in paired comparisons for MCQ and WBSI disappeared. Similarly, when OCD patients with religious obsessions (n = 16) were excluded, paired comparisons for MCQ and TAF morality were not statistically significant. Changes in BDI, TAFS morality, MCQ-30, and WBSI (P < .005) were significantly correlated with changes in severity of obsessions, but not that of compulsions. After controlling for the change in depression severity, significant correlations between changes in obsessive and cognitive scales did not continue to have statistical significance. The BDI changes (P < .05) significantly explained the changes in symptom severity in a linear regression model. Our findings suggest that selective serotonin reuptake inhibitors can change appraisals of obsessive intrusions via their effects on negative emotions. Copyright © 2011 Elsevier Inc. All rights reserved.

New Optical Transforms For Statistical Image Recognition

NASA Astrophysics Data System (ADS)

Lee, Sing H.

1983-12-01

In optical implementation of statistical image recognition, new optical transforms on large images for real-time recognition are of special interest. Several important linear transformations frequently used in statistical pattern recognition have now been optically implemented, including the Karhunen-Loeve transform (KLT), the Fukunaga-Koontz transform (FKT) and the least-squares linear mapping technique (LSLMT).1-3 The KLT performs principle components analysis on one class of patterns for feature extraction. The FKT performs feature extraction for separating two classes of patterns. The LSLMT separates multiple classes of patterns by maximizing the interclass differences and minimizing the intraclass variations.

A lower-extremities kinematic comparison of deep-water running styles and treadmill running.

PubMed

Killgore, Garry L; Wilcox, Anthony R; Caster, Brian L; Wood, Terry M

2006-11-01

The purpose of this investigation was to identify a deep-water running (DWR) style that most closely approximates terrestrial running, particularly relative to the lower extremities. Twenty intercollegiate distance runners (women, N = 12; men, N = 8) were videotaped from the right sagittal view while running on a treadmill (TR) and in deep water at 55-60% of their TR VO(2)max using 2 DWR styles: cross-country (CC) and high-knee (HK). Variables of interest were horizontal (X) and vertical (Y) displacement of the knee and ankle, stride rate (SR), VO(2), heart rate (HR), and rating of perceived exertion (RPE). Multivariate omnibus tests revealed statistically significant differences for RPE (p < 0.001). The post hoc pairwise comparisons revealed significant differences between TR and both DWR styles (p < 0.001). The kinematic variables multivariate omnibus tests were found to be statistically significant (p < 0.001 to p < 0.019). The post hoc pairwise comparisons revealed significant differences in SR (p < 0.001) between TR (1.25 +/- 0.08 Hz) and both DWR styles and also between the CC (0.81 +/- 0.08 Hz) and HK (1.14 +/- 0.10 Hz) styles of DWR. The CC style of DWR was found to be similar to TR with respect to linear ankle displacement, whereas the HK style was significantly different from TR in all comparisons made for ankle and knee displacement. The CC style of DWR is recommended as an adjunct to distance running training if the goal is to mimic the specificity of the ankle linear horizontal displacement of land-based running, but the SR will be slower at a comparable percentage of VO(2)max.

A statistical assessment of seismic models of the U.S. continental crust using Bayesian inversion of ambient noise surface wave dispersion data

NASA Astrophysics Data System (ADS)

Olugboji, T. M.; Lekic, V.; McDonough, W.

2017-07-01

We present a new approach for evaluating existing crustal models using ambient noise data sets and its associated uncertainties. We use a transdimensional hierarchical Bayesian inversion approach to invert ambient noise surface wave phase dispersion maps for Love and Rayleigh waves using measurements obtained from Ekström (2014). Spatiospectral analysis shows that our results are comparable to a linear least squares inverse approach (except at higher harmonic degrees), but the procedure has additional advantages: (1) it yields an autoadaptive parameterization that follows Earth structure without making restricting assumptions on model resolution (regularization or damping) and data errors; (2) it can recover non-Gaussian phase velocity probability distributions while quantifying the sources of uncertainties in the data measurements and modeling procedure; and (3) it enables statistical assessments of different crustal models (e.g., CRUST1.0, LITHO1.0, and NACr14) using variable resolution residual and standard deviation maps estimated from the ensemble. These assessments show that in the stable old crust of the Archean, the misfits are statistically negligible, requiring no significant update to crustal models from the ambient noise data set. In other regions of the U.S., significant updates to regionalization and crustal structure are expected especially in the shallow sedimentary basins and the tectonically active regions, where the differences between model predictions and data are statistically significant.

Relationship of milking rate to somatic cell count.

PubMed

Brown, C A; Rischette, S J; Schultz, L H

1986-03-01

Information on milking rate, monthly bucket somatic cell counts, mastitis treatment, and milk production was obtained from 284 lactations of Holstein cows separated into three lactation groups. Significant correlations between somatic cell count (linear score) and other parameters included production in lactation 1 (-.185), production in lactation 2 (-.267), and percent 2-min milk in lactation 2 (.251). Somatic cell count tended to increase with maximum milking rate in all lactations, but correlations were not statistically significant. Twenty-nine percent of cows with milking rate measurements were treated for clinical mastitis. Treated cows in each lactation group produced less milk than untreated cows. In the second and third lactation groups, treated cows had a shorter total milking time and a higher percent 2-min milk than untreated cows, but differences were not statistically significant. Overall, the data support the concept that faster milking cows tend to have higher cell counts and more mastitis treatments, particularly beyond first lactation. However, the magnitude of the relationship was small.

Strengthen forensic entomology in court--the need for data exploration and the validation of a generalised additive mixed model.

PubMed

Baqué, Michèle; Amendt, Jens

2013-01-01

Developmental data of juvenile blow flies (Diptera: Calliphoridae) are typically used to calculate the age of immature stages found on or around a corpse and thus to estimate a minimum post-mortem interval (PMI(min)). However, many of those data sets don't take into account that immature blow flies grow in a non-linear fashion. Linear models do not supply a sufficient reliability on age estimates and may even lead to an erroneous determination of the PMI(min). According to the Daubert standard and the need for improvements in forensic science, new statistic tools like smoothing methods and mixed models allow the modelling of non-linear relationships and expand the field of statistical analyses. The present study introduces into the background and application of these statistical techniques by analysing a model which describes the development of the forensically important blow fly Calliphora vicina at different temperatures. The comparison of three statistical methods (linear regression, generalised additive modelling and generalised additive mixed modelling) clearly demonstrates that only the latter provided regression parameters that reflect the data adequately. We focus explicitly on both the exploration of the data--to assure their quality and to show the importance of checking it carefully prior to conducting the statistical tests--and the validation of the resulting models. Hence, we present a common method for evaluating and testing forensic entomological data sets by using for the first time generalised additive mixed models.

Photometric analysis of esthetically pleasant and unpleasant facial profile

PubMed Central

Fortes, Helena Nunes da Rocha; Guimarães, Thamirys Correia; Belo, Ivana Mara Lira; da Matta, Edgard Norões Rodrigues

2014-01-01

Objective To identify which linear, angular and proportionality measures could influence a profile to be considered esthetically pleasant or unpleasant, and to assess sexual dimorphism. Methods 150 standardized facial profile photographs of dental students of both sexes were obtained and printed on photographic paper. Ten plastic surgeons, ten orthodontists and ten layperson answered a questionnaire characterizing each profile as pleasant, acceptable or unpleasant. With the use of a score system, the 15 most pleasant and unpleasant profiles of each sex were selected. The photographs were scanned into AutoCAD computer software. Linear, angular and proportion measurements were obtained using the software tools. The average values between groups were compared by the Student's t-test and the Mann-Whitney test at 5%. Results The linear measures LL-S, LL-H, LL-E, LL-B and Pn-H showed statistically significant differences (p < 0.05). Statistical differences were also found in the angular measures G'.Pn.Pg', G'.Sn.Pg' and Sn.Me'.C and in the proportions G'-Sn:Sn-Me' and Sn-Gn':Gn'-C (p < 0.05). Differences between sexes were found for the linear measure Ala-Pn, angles G'-Pg'.N-Pn, Sn.Me'.C, and proportions Gn'-Sn:Sn-Me' and Ala-Pn:N'-Sn. (p < 0.05). Conclusion The anteroposterior position of the lower lip, the amount of nose that influences the profile, facial convexity, total vertical proportion and lip-chin proportion appear to influence pleasantness of facial profile. Sexual dimorphism was identified in nasal length, nasofacial and lower third of the face angles, total vertical and nasal height/length proportions. PMID:24945516

Cross-conditional entropy and coherence analysis of pharmaco-EEG changes induced by alprazolam.

PubMed

Alonso, J F; Mañanas, M A; Romero, S; Rojas-Martínez, M; Riba, J

2012-06-01

Quantitative analysis of electroencephalographic signals (EEG) and their interpretation constitute a helpful tool in the assessment of the bioavailability of psychoactive drugs in the brain. Furthermore, psychotropic drug groups have typical signatures which relate biochemical mechanisms with specific EEG changes. To analyze the pharmacological effect of a dose of alprazolam on the connectivity of the brain during wakefulness by means of linear and nonlinear approaches. EEG signals were recorded after alprazolam administration in a placebo-controlled crossover clinical trial. Nonlinear couplings assessed by means of corrected cross-conditional entropy were compared to linear couplings measured with the classical magnitude squared coherence. Linear variables evidenced a statistically significant drug-induced decrease, whereas nonlinear variables showed significant increases. All changes were highly correlated to drug plasma concentrations. The spatial distribution of the observed connectivity changes clearly differed from a previous study: changes before and after the maximum drug effect were mainly observed over the anterior half of the scalp. Additionally, a new variable with very low computational cost was defined to evaluate nonlinear coupling. This is particularly interesting when all pairs of EEG channels are assessed as in this study. Results showed that alprazolam induced changes in terms of uncoupling between regions of the scalp, with opposite trends depending on the variables: decrease in linear ones and increase in nonlinear features. Maps provided consistent information about the way brain changed in terms of connectivity being definitely necessary to evaluate separately linear and nonlinear interactions.

Determination of statistics for any rotation of axes of a bivariate normal elliptical distribution. [of wind vector components

NASA Technical Reports Server (NTRS)

Falls, L. W.; Crutcher, H. L.

1976-01-01

Transformation of statistics from a dimensional set to another dimensional set involves linear functions of the original set of statistics. Similarly, linear functions will transform statistics within a dimensional set such that the new statistics are relevant to a new set of coordinate axes. A restricted case of the latter is the rotation of axes in a coordinate system involving any two correlated random variables. A special case is the transformation for horizontal wind distributions. Wind statistics are usually provided in terms of wind speed and direction (measured clockwise from north) or in east-west and north-south components. A direct application of this technique allows the determination of appropriate wind statistics parallel and normal to any preselected flight path of a space vehicle. Among the constraints for launching space vehicles are critical values selected from the distribution of the expected winds parallel to and normal to the flight path. These procedures are applied to space vehicle launches at Cape Kennedy, Florida.

Classification of emotional states from electrocardiogram signals: a non-linear approach based on hurst

PubMed Central

2013-01-01

Background Identifying the emotional state is helpful in applications involving patients with autism and other intellectual disabilities; computer-based training, human computer interaction etc. Electrocardiogram (ECG) signals, being an activity of the autonomous nervous system (ANS), reflect the underlying true emotional state of a person. However, the performance of various methods developed so far lacks accuracy, and more robust methods need to be developed to identify the emotional pattern associated with ECG signals. Methods Emotional ECG data was obtained from sixty participants by inducing the six basic emotional states (happiness, sadness, fear, disgust, surprise and neutral) using audio-visual stimuli. The non-linear feature ‘Hurst’ was computed using Rescaled Range Statistics (RRS) and Finite Variance Scaling (FVS) methods. New Hurst features were proposed by combining the existing RRS and FVS methods with Higher Order Statistics (HOS). The features were then classified using four classifiers – Bayesian Classifier, Regression Tree, K- nearest neighbor and Fuzzy K-nearest neighbor. Seventy percent of the features were used for training and thirty percent for testing the algorithm. Results Analysis of Variance (ANOVA) conveyed that Hurst and the proposed features were statistically significant (p < 0.001). Hurst computed using RRS and FVS methods showed similar classification accuracy. The features obtained by combining FVS and HOS performed better with a maximum accuracy of 92.87% and 76.45% for classifying the six emotional states using random and subject independent validation respectively. Conclusions The results indicate that the combination of non-linear analysis and HOS tend to capture the finer emotional changes that can be seen in healthy ECG data. This work can be further fine tuned to develop a real time system. PMID:23680041

2,4,6-Trinitrotoluene (TNT) air concentrations, hemoglobin changes, and anemia cases in respirator protected TNT munitions demilitarization workers.

PubMed

Bradley, Melville D

2011-03-01

2,4,6-Trinitrotoluene (TNT) is an explosive used in munitions production that is known to cause both aplastic and hemolytic anemia in exposed workers. Anemia in a TNT worker is considered a sentinel health event (occupational) (SHE(O)) in the United States (US). Deaths have been reported secondary to aplastic anemia. Studies have shown that TNT systemic absorption is significant by both the respiratory and dermal routes. No studies encountered looked at hemoglobin change or anemia cases in respiratory protected workers. It is hypothesized that respiratory protection is insufficient to protect TNT workers from the risk of anemia development and hemoglobin concentration drop. A records review of eight groups of respiratory protected TNT workers' pre-exposure hemoglobin levels were compared with their during-exposure hemoglobin levels for statistically significant (alpha level 0.05) hemoglobin level changes, and anemia cases were recorded. A curve estimation analysis was performed between mean TNT air concentrations and mean hemoglobin change values. Statistically significant hemoglobin level drops and anemia cases were apparent at TNT air concentrations about the REL and PEL in respiratory protected workers. There were no anemia cases or statistically significant hemoglobin level drops at concentrations about the TLV, however. A statistically significant inverse non-linear regression model was found to be the best fit for regressing hemoglobin change on TNT air concentration. Respiratory protection may be inadequate to prevent workers who are at risk for TNT skin absorption from developing anemia. This study contributes evidence that the TLV should be considered for adoption as the new PEL.

Chromosome aberration analysis in peripheral lymphocytes of Gulf War and Balkans War veterans.

PubMed

Schröder, H; Heimers, A; Frentzel-Beyme, R; Schott, A; Hoffmann, W

2003-01-01

Chromosome aberrations and sister chromatid exchanges (SCEs) were determined in standard peripheral lymphocyte metaphase preparations of 13 British Gulf War veterans, two veterans of the recent war in the Balkans and one veteran of both wars. All 16 volunteers suspect exposures to depleted uranium (DU) while deployed at the two different theatres of war in 1990 and later on. The Bremen laboratory control served as a reference in this study. Compared with this control there was a statistically significant increase in the frequency of dicentric chromosomes (dic) and centric ring chromosomes (cR) in the veterans' group. indicating a previous exposure to ionising radiation. The statistically significant overdispersion of die and cR indicates non-uniform irradiation as would be expected after non-uniform exposure and/or exposure to radiation with a high linear energy transfer (LET). The frequency of SCEs was decreased when compared with the laboratory control.

Association Between Medicare Summary Star Ratings for Patient Experience and Clinical Outcomes in US Hospitals.

PubMed

Trzeciak, Stephen; Gaughan, John P; Bosire, Joshua; Mazzarelli, Anthony J

2016-03-01

In 2015, the Centers for Medicare and Medicaid Services (CMS) released new summary star ratings for US hospitals based on patient experience. We aimed to test the association between CMS patient experience star ratings and clinical outcomes. We analyzed risk-adjusted data for more than 3000 US hospitals from CMS Hospital Compare using linear regression. We found that better patient experience was associated with favorable clinical outcomes. Specifically, a higher number of stars for patient experience had a statistically significant association with lower rates of many in-hospital complications. A higher patient experience star rating also had a statistically significant association with lower rates of unplanned readmissions to the hospital within 30 days. Better patient experience according to the CMS star ratings is associated with favorable clinical outcomes. These results support the inclusion of patient experience data in the framework of how hospitals are paid for services.

Improving DHH students' grammar through an individualized software program.

PubMed

Cannon, Joanna E; Easterbrooks, Susan R; Gagné, Phill; Beal-Alvarez, Jennifer

2011-01-01

The purpose of this study was to determine if the frequent use of a targeted, computer software grammar instruction program, used as an individualized classroom activity, would influence the comprehension of morphosyntax structures (determiners, tense, and complementizers) in deaf/hard-of-hearing (DHH) participants who use American Sign Language (ASL). Twenty-six students from an urban day school for the deaf participated in this study. Two hierarchical linear modeling growth curve analyses showed that the influence of LanguageLinks: Syntax Assessment and Intervention (LL) resulted in statistically significant gains in participants' comprehension of morphosyntax structures. Two dependent t tests revealed statistically significant results between the pre- and postintervention assessments on the Diagnostic Evaluation of Language Variation-Norm Referenced. The daily use of LL increased the morphosyntax comprehension of the participants in this study and may be a promising practice for DHH students who use ASL.

Septic tank additive impacts on microbial populations.

PubMed

Pradhan, S; Hoover, M T; Clark, G H; Gumpertz, M; Wollum, A G; Cobb, C; Strock, J

2008-01-01

Environmental health specialists, other onsite wastewater professionals, scientists, and homeowners have questioned the effectiveness of septic tank additives. This paper describes an independent, third-party, field scale, research study of the effects of three liquid bacterial septic tank additives and a control (no additive) on septic tank microbial populations. Microbial populations were measured quarterly in a field study for 12 months in 48 full-size, functioning septic tanks. Bacterial populations in the 48 septic tanks were statistically analyzed with a mixed linear model. Additive effects were assessed for three septic tank maintenance levels (low, intermediate, and high). Dunnett's t-test for tank bacteria (alpha = .05) indicated that none of the treatments were significantly different, overall, from the control at the statistical level tested. In addition, the additives had no significant effects on septic tank bacterial populations at any of the septic tank maintenance levels. Additional controlled, field-based research iswarranted, however, to address additional additives and experimental conditions.

Response to Comment on "Does the Earth Have an Adaptive Infrared IRIS?"

NASA Technical Reports Server (NTRS)

Bell, Thomas L.; Chou, Ming-Dah; Lindzen, Richard S.; Hou, Arthur Y.

2001-01-01

Harrison's (2001) Comment on the Methodology in Lindzen et al (2001) has prompted re-examination of several aspects of study. Probably the most significant disagreement in our conclusions is due to our different approaches to minimizing the influence of long-time-scale variations in the variables A and T on the results. Given the strength of the annual cycle and the 20-month period covered by the data, we believe that removing monthly means is a better approach to minimizing the long-time-scale behavior of the data than removal of the linear trend, which might actually add spurious long- time- scale variability into the modified data. We have also indicated how our statistical methods of establishing statistical significance differ. More definitive conclusions may only possible after more data have been analyzed, but we feel that our results are robust enough to encourage further study of this phenomenon.

Mass detection, localization and estimation for wind turbine blades based on statistical pattern recognition

NASA Astrophysics Data System (ADS)

Colone, L.; Hovgaard, M. K.; Glavind, L.; Brincker, R.

2018-07-01

A method for mass change detection on wind turbine blades using natural frequencies is presented. The approach is based on two statistical tests. The first test decides if there is a significant mass change and the second test is a statistical group classification based on Linear Discriminant Analysis. The frequencies are identified by means of Operational Modal Analysis using natural excitation. Based on the assumption of Gaussianity of the frequencies, a multi-class statistical model is developed by combining finite element model sensitivities in 10 classes of change location on the blade, the smallest area being 1/5 of the span. The method is experimentally validated for a full scale wind turbine blade in a test setup and loaded by natural wind. Mass change from natural causes was imitated with sand bags and the algorithm was observed to perform well with an experimental detection rate of 1, localization rate of 0.88 and mass estimation rate of 0.72.

Humidity-corrected Arrhenius equation: The reference condition approach.

PubMed

Naveršnik, Klemen; Jurečič, Rok

2016-03-16

Accelerated and stress stability data is often used to predict shelf life of pharmaceuticals. Temperature, combined with humidity accelerates chemical decomposition and the Arrhenius equation is used to extrapolate accelerated stability results to long-term stability. Statistical estimation of the humidity-corrected Arrhenius equation is not straightforward due to its non-linearity. A two stage nonlinear fitting approach is used in practice, followed by a prediction stage. We developed a single-stage statistical procedure, called the reference condition approach, which has better statistical properties (less collinearity, direct estimation of uncertainty, narrower prediction interval) and is significantly easier to use, compared to the existing approaches. Our statistical model was populated with data from a 35-day stress stability study on a laboratory batch of vitamin tablets and required mere 30 laboratory assay determinations. The stability prediction agreed well with the actual 24-month long term stability of the product. The approach has high potential to assist product formulation, specification setting and stability statements. Copyright © 2016 Elsevier B.V. All rights reserved.

Functional linear models to test for differences in prairie wetland hydraulic gradients

USGS Publications Warehouse

Greenwood, Mark C.; Sojda, Richard S.; Preston, Todd M.; Swayne, David A.; Yang, Wanhong; Voinov, A.A.; Rizzoli, A.; Filatova, T.

2010-01-01

Functional data analysis provides a framework for analyzing multiple time series measured frequently in time, treating each series as a continuous function of time. Functional linear models are used to test for effects on hydraulic gradient functional responses collected from three types of land use in Northeastern Montana at fourteen locations. Penalized regression-splines are used to estimate the underlying continuous functions based on the discretely recorded (over time) gradient measurements. Permutation methods are used to assess the statistical significance of effects. A method for accommodating missing observations in each time series is described. Hydraulic gradients may be an initial and fundamental ecosystem process that responds to climate change. We suggest other potential uses of these methods for detecting evidence of climate change.

Diurnal fluctuations in brain volume: Statistical analyses of MRI from large populations.

PubMed

Nakamura, Kunio; Brown, Robert A; Narayanan, Sridar; Collins, D Louis; Arnold, Douglas L

2015-09-01

We investigated fluctuations in brain volume throughout the day using statistical modeling of magnetic resonance imaging (MRI) from large populations. We applied fully automated image analysis software to measure the brain parenchymal fraction (BPF), defined as the ratio of the brain parenchymal volume and intracranial volume, thus accounting for variations in head size. The MRI data came from serial scans of multiple sclerosis (MS) patients in clinical trials (n=755, 3269 scans) and from subjects participating in the Alzheimer's Disease Neuroimaging Initiative (ADNI, n=834, 6114 scans). The percent change in BPF was modeled with a linear mixed effect (LME) model, and the model was applied separately to the MS and ADNI datasets. The LME model for the MS datasets included random subject effects (intercept and slope over time) and fixed effects for the time-of-day, time from the baseline scan, and trial, which accounted for trial-related effects (for example, different inclusion criteria and imaging protocol). The model for ADNI additionally included the demographics (baseline age, sex, subject type [normal, mild cognitive impairment, or Alzheimer's disease], and interaction between subject type and time from baseline). There was a statistically significant effect of time-of-day on the BPF change in MS clinical trial datasets (-0.180 per day, that is, 0.180% of intracranial volume, p=0.019) as well as the ADNI dataset (-0.438 per day, that is, 0.438% of intracranial volume, p<0.0001), showing that the brain volume is greater in the morning. Linearly correcting the BPF values with the time-of-day reduced the required sample size to detect a 25% treatment effect (80% power and 0.05 significance level) on change in brain volume from 2 time-points over a period of 1year by 2.6%. Our results have significant implications for future brain volumetric studies, suggesting that there is a potential acquisition time bias that should be randomized or statistically controlled to account for the day-to-day brain volume fluctuations. Copyright © 2015 Elsevier Inc. All rights reserved.

Assessment of geometrical characteristics of dental endodontic micro-instruments utilizing X-ray micro computed tomography

PubMed Central

Al JABBARI, Youssef S.; TSAKIRIDIS, Peter; ELIADES, George; AL-HADLAQ, Solaiman M.; ZINELIS, Spiros

2012-01-01

Objective The aim of this study was to quantify the surface area, volume and specific surface area of endodontic files employing quantitative X-ray micro computed tomography (mXCT). Material and Methods Three sets (six files each) of the Flex-Master Ni-Ti system (Nº 20, 25 and 30, taper .04) were utilized in this study. The files were scanned by mXCT. The surface area and volume of all files were determined from the cutting tip up to 16 mm. The data from the surface area, volume and specific area were statistically evaluated using the one-way ANOVA and SNK multiple comparison tests at α=0.05, employing the file size as a discriminating variable. The correlation between the surface area and volume with nominal ISO sizes were tested employing linear regression analysis. Results The surface area and volume of Nº 30 files showed the highest value followed by Nº 25 and Nº 20 and the differences were statistically significant. The Nº 20 files showed a significantly higher specific surface area compared to Nº 25 and Nº 30. The increase in surface and volume towards higher file sizes follows a linear relationship with the nominal ISO sizes (r2=0.930 for surface area and r2=0.974 for volume respectively). Results indicated that the surface area and volume demonstrated an almost linear increase while the specific surface area exhibited an abrupt decrease towards higher sizes. Conclusions This study demonstrates that mXCT can be effectively applied to discriminate very small differences in the geometrical features of endodontic micro-instruments, while providing quantitative information for their geometrical properties. PMID:23329248

A model for predicting sulcus-to-sulcus diameter in posterior chamber phakic intraocular lens candidates: correlation between ocular biometric parameters.

PubMed

Ghoreishi, Mohammad; Abdi-Shahshahani, Mehdi; Peyman, Alireza; Pourazizi, Mohsen

2018-02-21

The aim of this study was to determine the correlation between ocular biometric parameters and sulcus-to-sulcus (STS) diameter. This was a cross-sectional study of preoperative ocular biometry data of patients who were candidates for phakic intraocular lens (IOL) surgery. Subjects underwent ocular biometry analysis, including refraction error evaluation using an autorefractor and Orbscan topography for white-to-white (WTW) corneal diameter and measurement. Pentacam was used to perform WTW corneal diameter and measurements of minimum and maximum keratometry (K). Measurements of STS and angle-to-angle (ATA) were obtained using a 50-MHz B-mode ultrasound device. Anterior optical coherence tomography was performed for anterior chamber depth measurement. Pearson's correlation test and stepwise linear regression analysis were used to find a model to predict STS. Fifty-eight eyes of 58 patients were enrolled. Mean age ± standard deviation of sample was 28.95 ± 6.04 years. The Pearson's correlation coefficient between STS with WTW, ATA, mean K was 0.383, 0.492, and - 0.353, respectively, which was statistically significant (all P < 0.001). Using stepwise linear regression analysis, there is a statistically significant association between STS with WTW (P = 0.011) and mean K (P = 0.025). The standardized coefficient was 0.323 and - 0.284 for WTW and mean K, respectively. The stepwise linear regression analysis equation was: (STS = 9.549 + 0.518 WTW - 0.083 mean K). Based on our result, given the correlation of STS with WTW and mean K and potential of direct and essay measurement of WTW and mean K, it seems that current IOL sizing protocols could be estimating with WTW and mean K.

A theory of fine structure image models with an application to detection and classification of dementia.

PubMed

O'Neill, William; Penn, Richard; Werner, Michael; Thomas, Justin

2015-06-01

Estimation of stochastic process models from data is a common application of time series analysis methods. Such system identification processes are often cast as hypothesis testing exercises whose intent is to estimate model parameters and test them for statistical significance. Ordinary least squares (OLS) regression and the Levenberg-Marquardt algorithm (LMA) have proven invaluable computational tools for models being described by non-homogeneous, linear, stationary, ordinary differential equations. In this paper we extend stochastic model identification to linear, stationary, partial differential equations in two independent variables (2D) and show that OLS and LMA apply equally well to these systems. The method employs an original nonparametric statistic as a test for the significance of estimated parameters. We show gray scale and color images are special cases of 2D systems satisfying a particular autoregressive partial difference equation which estimates an analogous partial differential equation. Several applications to medical image modeling and classification illustrate the method by correctly classifying demented and normal OLS models of axial magnetic resonance brain scans according to subject Mini Mental State Exam (MMSE) scores. Comparison with 13 image classifiers from the literature indicates our classifier is at least 14 times faster than any of them and has a classification accuracy better than all but one. Our modeling method applies to any linear, stationary, partial differential equation and the method is readily extended to 3D whole-organ systems. Further, in addition to being a robust image classifier, estimated image models offer insights into which parameters carry the most diagnostic image information and thereby suggest finer divisions could be made within a class. Image models can be estimated in milliseconds which translate to whole-organ models in seconds; such runtimes could make real-time medicine and surgery modeling possible.

Perturbative Gaussianizing transforms for cosmological fields

NASA Astrophysics Data System (ADS)

Hall, Alex; Mead, Alexander

2018-01-01

Constraints on cosmological parameters from large-scale structure have traditionally been obtained from two-point statistics. However, non-linear structure formation renders these statistics insufficient in capturing the full information content available, necessitating the measurement of higher order moments to recover information which would otherwise be lost. We construct quantities based on non-linear and non-local transformations of weakly non-Gaussian fields that Gaussianize the full multivariate distribution at a given order in perturbation theory. Our approach does not require a model of the fields themselves and takes as input only the first few polyspectra, which could be modelled or measured from simulations or data, making our method particularly suited to observables lacking a robust perturbative description such as the weak-lensing shear. We apply our method to simulated density fields, finding a significantly reduced bispectrum and an enhanced correlation with the initial field. We demonstrate that our method reconstructs a large proportion of the linear baryon acoustic oscillations, improving the information content over the raw field by 35 per cent. We apply the transform to toy 21 cm intensity maps, showing that our method still performs well in the presence of complications such as redshift-space distortions, beam smoothing, pixel noise and foreground subtraction. We discuss how this method might provide a route to constructing a perturbative model of the fully non-Gaussian multivariate likelihood function.

An analysis of a large dataset on immigrant integration in Spain. The Statistical Mechanics perspective on Social Action

NASA Astrophysics Data System (ADS)

Barra, Adriano; Contucci, Pierluigi; Sandell, Rickard; Vernia, Cecilia

2014-02-01

How does immigrant integration in a country change with immigration density? Guided by a statistical mechanics perspective we propose a novel approach to this problem. The analysis focuses on classical integration quantifiers such as the percentage of jobs (temporary and permanent) given to immigrants, mixed marriages, and newborns with parents of mixed origin. We find that the average values of different quantifiers may exhibit either linear or non-linear growth on immigrant density and we suggest that social action, a concept identified by Max Weber, causes the observed non-linearity. Using the statistical mechanics notion of interaction to quantitatively emulate social action, a unified mathematical model for integration is proposed and it is shown to explain both growth behaviors observed. The linear theory instead, ignoring the possibility of interaction effects would underestimate the quantifiers up to 30% when immigrant densities are low, and overestimate them as much when densities are high. The capacity to quantitatively isolate different types of integration mechanisms makes our framework a suitable tool in the quest for more efficient integration policies.

Low-complexity stochastic modeling of wall-bounded shear flows

NASA Astrophysics Data System (ADS)

Zare, Armin

Turbulent flows are ubiquitous in nature and they appear in many engineering applications. Transition to turbulence, in general, increases skin-friction drag in air/water vehicles compromising their fuel-efficiency and reduces the efficiency and longevity of wind turbines. While traditional flow control techniques combine physical intuition with costly experiments, their effectiveness can be significantly enhanced by control design based on low-complexity models and optimization. In this dissertation, we develop a theoretical and computational framework for the low-complexity stochastic modeling of wall-bounded shear flows. Part I of the dissertation is devoted to the development of a modeling framework which incorporates data-driven techniques to refine physics-based models. We consider the problem of completing partially known sample statistics in a way that is consistent with underlying stochastically driven linear dynamics. Neither the statistics nor the dynamics are precisely known. Thus, our objective is to reconcile the two in a parsimonious manner. To this end, we formulate optimization problems to identify the dynamics and directionality of input excitation in order to explain and complete available covariance data. For problem sizes that general-purpose solvers cannot handle, we develop customized optimization algorithms based on alternating direction methods. The solution to the optimization problem provides information about critical directions that have maximal effect in bringing model and statistics in agreement. In Part II, we employ our modeling framework to account for statistical signatures of turbulent channel flow using low-complexity stochastic dynamical models. We demonstrate that white-in-time stochastic forcing is not sufficient to explain turbulent flow statistics and develop models for colored-in-time forcing of the linearized Navier-Stokes equations. We also examine the efficacy of stochastically forced linearized NS equations and their parabolized equivalents in the receptivity analysis of velocity fluctuations to external sources of excitation as well as capturing the effect of the slowly-varying base flow on streamwise streaks and Tollmien-Schlichting waves. In Part III, we develop a model-based approach to design surface actuation of turbulent channel flow in the form of streamwise traveling waves. This approach is capable of identifying the drag reducing trends of traveling waves in a simulation-free manner. We also use the stochastically forced linearized NS equations to examine the Reynolds number independent effects of spanwise wall oscillations on drag reduction in turbulent channel flows. This allows us to extend the predictive capability of our simulation-free approach to high Reynolds numbers.

A Statistical Analysis of Brain Morphology Using Wild Bootstrapping

PubMed Central

Ibrahim, Joseph G.; Tang, Niansheng; Rowe, Daniel B.; Hao, Xuejun; Bansal, Ravi; Peterson, Bradley S.

2008-01-01

Methods for the analysis of brain morphology, including voxel-based morphology and surface-based morphometries, have been used to detect associations between brain structure and covariates of interest, such as diagnosis, severity of disease, age, IQ, and genotype. The statistical analysis of morphometric measures usually involves two statistical procedures: 1) invoking a statistical model at each voxel (or point) on the surface of the brain or brain subregion, followed by mapping test statistics (e.g., t test) or their associated p values at each of those voxels; 2) correction for the multiple statistical tests conducted across all voxels on the surface of the brain region under investigation. We propose the use of new statistical methods for each of these procedures. We first use a heteroscedastic linear model to test the associations between the morphological measures at each voxel on the surface of the specified subregion (e.g., cortical or subcortical surfaces) and the covariates of interest. Moreover, we develop a robust test procedure that is based on a resampling method, called wild bootstrapping. This procedure assesses the statistical significance of the associations between a measure of given brain structure and the covariates of interest. The value of this robust test procedure lies in its computationally simplicity and in its applicability to a wide range of imaging data, including data from both anatomical and functional magnetic resonance imaging (fMRI). Simulation studies demonstrate that this robust test procedure can accurately control the family-wise error rate. We demonstrate the application of this robust test procedure to the detection of statistically significant differences in the morphology of the hippocampus over time across gender groups in a large sample of healthy subjects. PMID:17649909

Physical activity, sedentary behavior, and vitamin D metabolites.

PubMed

Hibler, Elizabeth A; Sardo Molmenti, Christine L; Dai, Qi; Kohler, Lindsay N; Warren Anderson, Shaneda; Jurutka, Peter W; Jacobs, Elizabeth T

2016-02-01

Physical activity is associated with circulating 25-hydroxyvitamin D (25(OH)D). However, the influence of activity and/or sedentary behavior on the biologically active, seco-steroid hormone 1α,25-dihydroxyvitamin D (1,25(OH)2D) is unknown. We conducted a cross-sectional analysis among ursodeoxycholic acid (UDCA) randomized trial participants (n=876) to evaluate associations between physical activity, sedentary behavior, and circulating vitamin D metabolite concentrations. Continuous vitamin D metabolite measurements and clinical thresholds were evaluated using multiple linear and logistic regression models, mutually adjusted for either 1,25(OH)2D or 25(OH)D and additional confounding factors. A statistically significant linear association between 1,25(OH)2D and moderate-vigorous physical activity per week was strongest among women (β (95% CI): 3.10 (1.51-6.35)) versus men (β (95% CI): 1.35 (0.79-2.29)) in the highest tertile of activity compared to the lowest (p-interaction=0.003). Furthermore, 25(OH)D was 1.54ng/ml (95% CI 1.09-1.98) higher per hour increase in moderate-vigorous activity (p=0.001) and odds of sufficient 25(OH)D status was higher among physically active participants (p=0.001). Sedentary behavior was not significantly associated with either metabolite in linear regression models, nor was a statistically significant interaction by sex identified. The current study identified novel associations between physical activity and serum 1,25(OH)2D levels, adjusted for 25(OH)D concentrations. These results identify the biologically active form of vitamin D as a potential physiologic mechanism related to observed population-level associations between moderate-vigorous physical activity with bone health and chronic disease risk. However, future longitudinal studies are needed to further evaluate the role of physical activity and vitamin D metabolites in chronic disease prevention. Copyright © 2015 Elsevier Inc. All rights reserved.

Comparing The Effectiveness of a90/95 Calculations (Preprint)

DTIC Science & Technology

2006-09-01

Nachtsheim, John Neter, William Li, Applied Linear Statistical Models , 5th ed., McGraw-Hill/Irwin, 2005 5. Mood, Graybill and Boes, Introduction...curves is based on methods that are only valid for ordinary linear regression. Requirements for a valid Ordinary Least-Squares Regression Model There... linear . For example is a linear model ; is not. 2. Uniform variance (homoscedasticity

Association between blood cholesterol and sodium intake in hypertensive women with excess weight.

PubMed

Padilha, Bruna Merten; Ferreira, Raphaela Costa; Bueno, Nassib Bezerra; Tassitano, Rafael Miranda; Holanda, Lidiana de Souza; Vasconcelos, Sandra Mary Lima; Cabral, Poliana Coelho

2018-04-01

Restricted sodium intake has been recommended for more than 1 century for the treatment of hypertension. However, restriction seems to increase blood cholesterol. In women with excess weight, blood cholesterol may increase even more because of insulin resistance and the high lipolytic activity of adipose tissue.The aim of this study was to assess the association between blood cholesterol and sodium intake in hypertensive women with and without excess weight.This was a cross-sectional study with hypertensive and nondiabetic women aged 20 to 59 years, recruited at the primary healthcare units of Maceio, Alagoas, Brazilian Northeast. Excess weight was defined as body mass index (BMI) ≥25.0 kg/m. Sodium intake was estimated by the 24-hour urinary excretion of sodium. Blood cholesterol was the primary outcome investigated by this study, and its relationship with sodium intake and other variables was assessed by Pearson correlation and multivariate linear regression using a significance level of 5%.This study included 165 hypertensive women. Of these, 135 (81.8%) were with excess weight. The mean sodium intake was 3.7 g (±1.9) and 3.4 g (±2.4) in hypertensive women with and without excess weight, respectively. The multiple normal linear regression models fitted to the "blood cholesterol" in the 2 groups reveal that for the group of hypertensive women without excess weight only 1 independent variable "age" is statistically significant to explain the variability of the blood cholesterol levels. However, for the group of hypertensive women with excess weight, 2 independent variables, age and sodium intake, can statistically explain variations of the blood cholesterol levels.Blood cholesterol is statistically inversely related to sodium intake for hypertensive women with excess weight, but it is not statistically related to sodium intake for hypertensive women without excess weight.

Statistical treatment for the wet bias in tree-ring chronologies: A case study from the InteriorWest, USA

Treesearch

Yan Sun; Matthew F. Bekker; R. Justin DeRose; Roger Kjelgren; S. -Y. Simon Wang

2017-01-01

Dendroclimatic research has long assumed a linear relationship between tree-ring increment and climate variables. However, ring width frequently underestimates extremely wet years, a phenomenon we refer to as ‘wet bias’. In this paper, we present statistical evidence for wet bias that is obscured by the assumption of linearity. To improve tree-ring-climate modeling, we...

Incorporating signal-dependent noise for hyperspectral target detection

NASA Astrophysics Data System (ADS)

Morman, Christopher J.; Meola, Joseph

2015-05-01

The majority of hyperspectral target detection algorithms are developed from statistical data models employing stationary background statistics or white Gaussian noise models. Stationary background models are inaccurate as a result of two separate physical processes. First, varying background classes often exist in the imagery that possess different clutter statistics. Many algorithms can account for this variability through the use of subspaces or clustering techniques. The second physical process, which is often ignored, is a signal-dependent sensor noise term. For photon counting sensors that are often used in hyperspectral imaging systems, sensor noise increases as the measured signal level increases as a result of Poisson random processes. This work investigates the impact of this sensor noise on target detection performance. A linear noise model is developed describing sensor noise variance as a linear function of signal level. The linear noise model is then incorporated for detection of targets using data collected at Wright Patterson Air Force Base.

Employing the Gini coefficient to measure participation inequality in treatment-focused Digital Health Social Networks.

PubMed

van Mierlo, Trevor; Hyatt, Douglas; Ching, Andrew T

2016-01-01

Digital Health Social Networks (DHSNs) are common; however, there are few metrics that can be used to identify participation inequality. The objective of this study was to investigate whether the Gini coefficient, an economic measure of statistical dispersion traditionally used to measure income inequality, could be employed to measure DHSN inequality. Quarterly Gini coefficients were derived from four long-standing DHSNs. The combined data set included 625,736 posts that were generated from 15,181 actors over 18,671 days. The range of actors (8-2323), posts (29-28,684), and Gini coefficients (0.15-0.37) varied. Pearson correlations indicated statistically significant associations between number of actors and number of posts (0.527-0.835, p  < .001), and Gini coefficients and number of posts (0.342-0.725, p  < .001). However, the association between Gini coefficient and number of actors was only statistically significant for the addiction networks (0.619 and 0.276, p  < .036). Linear regression models had positive but mixed R 2 results (0.333-0.527). In all four regression models, the association between Gini coefficient and posts was statistically significant ( t  = 3.346-7.381, p  < .002). However, unlike the Pearson correlations, the association between Gini coefficient and number of actors was only statistically significant in the two mental health networks ( t  = -4.305 and -5.934, p  < .000). The Gini coefficient is helpful in measuring shifts in DHSN inequality. However, as a standalone metric, the Gini coefficient does not indicate optimal numbers or ratios of actors to posts, or effective network engagement. Further, mixed-methods research investigating quantitative performance metrics is required.

Impact of work environment and work-related stress on turnover intention in physical therapists.

PubMed

Lee, Byoung-Kwon; Seo, Dong-Kwon; Lee, Jang-Tae; Lee, A-Ram; Jeon, Ha-Neul; Han, Dong-Uk

2016-08-01

[Purpose] This study was conducted to provide basic data for solutions to reduce the turnover rate of physical therapists. It should help create efficient personnel and organization management by exploring the impact of the work environment and work-related stress on turnover intention and analyzing the correlation between them. [Subjects and Methods] A survey was conducted with 236 physical therapists working at medical institutions in the Daejeon and Chungcheong areas. For the analysis on the collected data, correlational and linear regression analyses were conducted using the SPSS 18.0 program and Cronbach's alpha coefficient. [Results] The results showed a statistically significant positive correlation between turnover intention and work-related stress but a statistically significant negative correlation respectively between turnover intention and work environment. Work-related stress (β=0.415) had a significant positive impact on turnover intention and work environment (β=-0.387) had a significant negative impact on turnover intention. [Conclusion] To increase satisfaction level with the profession as well as the workplace for physical therapists, improvement of the work environment was the most necessary primary improvement.

Impact of work environment and work-related stress on turnover intention in physical therapists

PubMed Central

Lee, Byoung-kwon; Seo, Dong-kwon; Lee, Jang-Tae; Lee, A-Ram; Jeon, Ha-Neul; Han, Dong-Uk

2016-01-01

[Purpose] This study was conducted to provide basic data for solutions to reduce the turnover rate of physical therapists. It should help create efficient personnel and organization management by exploring the impact of the work environment and work-related stress on turnover intention and analyzing the correlation between them. [Subjects and Methods] A survey was conducted with 236 physical therapists working at medical institutions in the Daejeon and Chungcheong areas. For the analysis on the collected data, correlational and linear regression analyses were conducted using the SPSS 18.0 program and Cronbach’s alpha coefficient. [Results] The results showed a statistically significant positive correlation between turnover intention and work-related stress but a statistically significant negative correlation respectively between turnover intention and work environment. Work-related stress (β=0.415) had a significant positive impact on turnover intention and work environment (β=−0.387) had a significant negative impact on turnover intention. [Conclusion] To increase satisfaction level with the profession as well as the workplace for physical therapists, improvement of the work environment was the most necessary primary improvement. PMID:27630432

Technician Consistency in Specular Microscopy Measurements: A "Real-World" Retrospective Analysis of a United States Eye Bank.

PubMed

Rand, Gabriel M; Kwon, Ji Won; Gore, Patrick K; McCartney, Mitchell D; Chuck, Roy S

2017-10-01

To quantify consistency of endothelial cell density (ECD) measurements among technicians in a single US eye bank operating under typical operating conditions. In this retrospective analysis of 51 microscopy technicians using a semiautomated counting method on 35,067 eyes from July 2007 to May 2015, technician- and date-related marginal ECD effects were calculated using linear regression models. ECD variance was correlated with the number of specular microscopy technicians. Technician mean ECDs ranged from 2386 ± 431 to 3005 ± 560 cells/mm. Nine technicians had statistically and clinically significant marginal effects. Annual mean ECDs adjusted for changes in technicians ranged from 2422 ± 433 to 2644 ± 430 cells/mm. The period of 2007 to 2009 had statistically and clinically significant marginal effects. There was a nonstatistically significant association between the number of technicians and ECD standard deviation. There was significant ECD variability associated with specular microscopy technicians and with the date of measurement. We recommend that eye banks collect data related to laboratory factors that have been shown to influence ECD variability.

Impact of poverty, not seeking medical care, unemployment, inflation, self-reported illness, and health insurance on mortality in Jamaica.

PubMed

Bourne, Paul Andrew

2009-08-01

An extensive review of the literature revealed that no study exists that has examined poverty, not seeking medical care, inflation, self-reported illness, and mortality in Jamaica. The current study will bridge the gap by providing an investigation of poverty; not seeking medical care; illness; health insurance coverage; inflation and mortality in Jamaica. Using two decades (1988-2007), the current study used three sets of secondary data published by the (1) Planning Institute of Jamaica and the Statistical Institute of Jamaica (Jamaica Survey of Living Conditions) (2) the Statistical Institute of Jamaica (Demographic Statistics) and (3) the Bank of Jamaica (Economic Report). Scatter diagrams were used to examine correlations between the particular dependent and independent variables. For the current study, a number of hypotheses were tested to provide explanation morality in Jamaica. The average percent of Jamaicans not seeking medical care over the last 2 decades was 41.9%; and the figure has been steadily declining over the last 5 years. In 1990, the most Jamaicans who did not seek medical care were 61.4% and this fell to 52.3% in 1991; 49.1% in 1992 and 48.2% the proceeding year. Based on the percentages, in the early 1990s (1990-1994), the percent of Jamaicans not seeking medical care was close to 50% and in the latter part of the decade, the figure was in the region of 30% and the low as 31.6% in 1999. In 2006, the percent of Jamaicans not seeking medical care despite being ill was 30% and this increased by 4% the following year. Concomitantly, poverty fell by 3.1 times over the 2 decades to 9.9% in 2007, while inflation increased by 1.9 times, self-reported illness was 15.5% in 2007 with mortality averaging 15,776 year of the 2 decades. There is a significant statistical correlation between not seeking medical-care and prevalence of poverty (r = 0.759, p< 0.05). There is a statistical correlation between not seeking medical care and unemployment; but the association is a non-linear one. The relationship between mortality and unemployment was an unsure one, with there being no clear linear or non-linear correlation. The findings revealed that there is a strong direct association between not seeking medical care and inflation rate (r = 0.752). A strong negative statistical correlation was found between mortality and prevalence of poverty (r=0.717). There is a non-linear statistical association between not seeking medical care and illness/injury. Not seeking medical care is not a good indicator of premature mortality; but that this percentage must be excess of 55%. While this study cannot confirm a clear rate of premature mortality, there are some indications that this occurs beyond a certain level of not seeking care for illness.

Impact of poverty, not seeking medical care, unemployment, inflation, self-reported illness, and health insurance on mortality in Jamaica

PubMed Central

Bourne, Paul Andrew

2009-01-01

Background: An extensive review of the literature revealed that no study exists that has examined poverty, not seeking medical care, inflation, self-reported illness, and mortality in Jamaica. The current study will bridge the gap by providing an investigation of poverty; not seeking medical care; illness; health insurance coverage; inflation and mortality in Jamaica. Materials and Method: Using two decades (1988-2007), the current study used three sets of secondary data published by the (1) Planning Institute of Jamaica and the Statistical Institute of Jamaica (Jamaica Survey of Living Conditions) (2) the Statistical Institute of Jamaica (Demographic Statistics) and (3) the Bank of Jamaica (Economic Report). Scatter diagrams were used to examine correlations between the particular dependent and independent variables. For the current study, a number of hypotheses were tested to provide explanation morality in Jamaica. Results: The average percent of Jamaicans not seeking medical care over the last 2 decades was 41.9%; and the figure has been steadily declining over the last 5 years. In 1990, the most Jamaicans who did not seek medical care were 61.4% and this fell to 52.3% in 1991; 49.1% in 1992 and 48.2% the proceeding year. Based on the percentages, in the early 1990s (1990-1994), the percent of Jamaicans not seeking medical care was close to 50% and in the latter part of the decade, the figure was in the region of 30% and the low as 31.6% in 1999. In 2006, the percent of Jamaicans not seeking medical care despite being ill was 30% and this increased by 4% the following year. Concomitantly, poverty fell by 3.1 times over the 2 decades to 9.9% in 2007, while inflation increased by 1.9 times, self-reported illness was 15.5% in 2007 with mortality averaging 15,776 year of the 2 decades. There is a significant statistical correlation between not seeking medical-care and prevalence of poverty (r = 0.759, p< 0.05). There is a statistical correlation between not seeking medical care and unemployment; but the association is a non-linear one. The relationship between mortality and unemployment was an unsure one, with there being no clear linear or non-linear correlation. The findings revealed that there is a strong direct association between not seeking medical care and inflation rate (r = 0.752). A strong negative statistical correlation was found between mortality and prevalence of poverty (r=0.717). There is a non-linear statistical association between not seeking medical care and illness/injury. Conclusions: Not seeking medical care is not a good indicator of premature mortality; but that this percentage must be excess of 55%. While this study cannot confirm a clear rate of premature mortality, there are some indications that this occurs beyond a certain level of not seeking care for illness. PMID:22666679

Rank-based testing of equal survivorship based on cross-sectional survival data with or without prospective follow-up.

PubMed

Chan, Kwun Chuen Gary; Qin, Jing

2015-10-01

Existing linear rank statistics cannot be applied to cross-sectional survival data without follow-up since all subjects are essentially censored. However, partial survival information are available from backward recurrence times and are frequently collected from health surveys without prospective follow-up. Under length-biased sampling, a class of linear rank statistics is proposed based only on backward recurrence times without any prospective follow-up. When follow-up data are available, the proposed rank statistic and a conventional rank statistic that utilizes follow-up information from the same sample are shown to be asymptotically independent. We discuss four ways to combine these two statistics when follow-up is present. Simulations show that all combined statistics have substantially improved power compared with conventional rank statistics, and a Mantel-Haenszel test performed the best among the proposal statistics. The method is applied to a cross-sectional health survey without follow-up and a study of Alzheimer's disease with prospective follow-up. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Compositional Solution Space Quantification for Probabilistic Software Analysis

NASA Technical Reports Server (NTRS)

Borges, Mateus; Pasareanu, Corina S.; Filieri, Antonio; d'Amorim, Marcelo; Visser, Willem

2014-01-01

Probabilistic software analysis aims at quantifying how likely a target event is to occur during program execution. Current approaches rely on symbolic execution to identify the conditions to reach the target event and try to quantify the fraction of the input domain satisfying these conditions. Precise quantification is usually limited to linear constraints, while only approximate solutions can be provided in general through statistical approaches. However, statistical approaches may fail to converge to an acceptable accuracy within a reasonable time. We present a compositional statistical approach for the efficient quantification of solution spaces for arbitrarily complex constraints over bounded floating-point domains. The approach leverages interval constraint propagation to improve the accuracy of the estimation by focusing the sampling on the regions of the input domain containing the sought solutions. Preliminary experiments show significant improvement on previous approaches both in results accuracy and analysis time.

Jackknife Variance Estimator for Two Sample Linear Rank Statistics

DTIC Science & Technology

1988-11-01

Accesion For - - ,NTIS GPA&I "TIC TAB Unann c, nc .. [d Keywords: strong consistency; linear rank test’ influence function . i , at L By S- )Distribut...reverse if necessary and identify by block number) FIELD IGROUP SUB-GROUP Strong consistency; linear rank test; influence function . 19. ABSTRACT

A Constrained Linear Estimator for Multiple Regression

ERIC Educational Resources Information Center

Davis-Stober, Clintin P.; Dana, Jason; Budescu, David V.

2010-01-01

"Improper linear models" (see Dawes, Am. Psychol. 34:571-582, "1979"), such as equal weighting, have garnered interest as alternatives to standard regression models. We analyze the general circumstances under which these models perform well by recasting a class of "improper" linear models as "proper" statistical models with a single predictor. We…

On spurious detection of linear response and misuse of the fluctuation-dissipation theorem in finite time series

NASA Astrophysics Data System (ADS)

Gottwald, Georg A.; Wormell, J. P.; Wouters, Jeroen

2016-09-01

Using a sensitive statistical test we determine whether or not one can detect the breakdown of linear response given observations of deterministic dynamical systems. A goodness-of-fit statistics is developed for a linear statistical model of the observations, based on results for central limit theorems for deterministic dynamical systems, and used to detect linear response breakdown. We apply the method to discrete maps which do not obey linear response and show that the successful detection of breakdown depends on the length of the time series, the magnitude of the perturbation and on the choice of the observable. We find that in order to reliably reject the assumption of linear response for typical observables sufficiently large data sets are needed. Even for simple systems such as the logistic map, one needs of the order of 106 observations to reliably detect the breakdown with a confidence level of 95 %; if less observations are available one may be falsely led to conclude that linear response theory is valid. The amount of data required is larger the smaller the applied perturbation. For judiciously chosen observables the necessary amount of data can be drastically reduced, but requires detailed a priori knowledge about the invariant measure which is typically not available for complex dynamical systems. Furthermore we explore the use of the fluctuation-dissipation theorem (FDT) in cases with limited data length or coarse-graining of observations. The FDT, if applied naively to a system without linear response, is shown to be very sensitive to the details of the sampling method, resulting in erroneous predictions of the response.

Coronal temperatures of selected active cool stars as derived from low resolution Einstein observations

NASA Technical Reports Server (NTRS)

Vilhu, Osmi; Linsky, Jeffrey L.

1990-01-01

Mean coronal temperatures of some active G-K stars were derived from Rev1-processed Einstein-observatory's IPC-spectra. The combined X-ray and transition region emission line data are in rough agreement with static coronal loop models. Although the sample is too small to derive any statistically significant conclusions, it suggests that the mean coronal temperature depends linearly on the inverse Rossby-number, with saturation at short rotation periods.

Bone mineral density and correlation factor analysis in normal Taiwanese children.

PubMed

Shu, San-Ging

2007-01-01

Our aim was to establish reference data and linear regression equations for lumbar bone mineral density (BMD) in normal Taiwanese children. Several influencing factors of lumbar BMD were investigated. Two hundred fifty-seven healthy children were recruited from schools, 136 boys and 121 girls, aged 4-18 years were enrolled on a voluntary basis with written consent. Their height, weight, blood pressure, puberty stage, bone age and lumbar BMD (L2-4) by dual energy x-ray absorptiometry (DEXA) were measured. Data were analyzed using Pearson correlation and stepwise regression tests. All measurements increased with age. Prior to age 8, there was no gender difference. Parameters such as height, weight, and bone age (BA) in girls surpassed boys between ages 8-13 without statistical significance (p> or =0.05). This was reversed subsequently after age 14 in height (p<0.05). BMD difference had the same trend but was not statistically significant either. The influencing power of puberty stage and bone age over BMD was almost equal to or higher than that of height and weight. All the other factors correlated with BMD to variable powers. Multiple linear regression equations for boys and girls were formulated. BMD reference data is provided and can be used to monitor childhood pathological conditions. However, BMD in those with abnormal bone age or pubertal development could need modifications to ensure accuracy.

Antral follicle counts are strongly associated with live-birth rates after assisted reproduction, with superior treatment outcome in women with polycystic ovaries.

PubMed

Holte, Jan; Brodin, Thomas; Berglund, Lars; Hadziosmanovic, Nermin; Olovsson, Matts; Bergh, Torbjörn

2011-09-01

To evaluate the association of antral follicle count (AFC) with in vitro fertilization/intracytoplasmic sperm injection (IVF-ICSI) outcome in a large unselected cohort of patients covering the entire range of AFC. Prospective observational study. University-affiliated private infertility center. 2,092 women undergoing 4,308 IVF-ICSI cycles. AFC analyzed for associations with treatment outcome and statistically adjusted for repeated treatments and age. Pregnancy rate, live-birth rate, and stimulation outcome parameters. The AFC was log-normally distributed. Pregnancy rates and live-birth rates were positively associated with AFC in a log-linear way, leveling out above AFC ∼30. Treatment outcome was superior among women with polycystic ovaries, independent from ovulatory status. The findings were significant also after adjustment for age and number of oocytes retrieved. Pregnancy and live-birth rates are log-linearly related to AFC. Polycystic ovaries, most often excluded from studies on ovarian reserve, fit as one extreme in the spectrum of AFC; a low count constitutes the other extreme, with the lowest ovarian reserve and poor treatment outcome. The findings remained statistically significant also after adjustment for the number of oocytes retrieved, suggesting this measure of ovarian reserve comprises information on oocyte quality and not only quantity. Copyright © 2011 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Tower of London test: a comparison between conventional statistic approach and modelling based on artificial neural network in differentiating fronto-temporal dementia from Alzheimer's disease.

PubMed

Franceschi, Massimo; Caffarra, Paolo; Savarè, Rita; Cerutti, Renata; Grossi, Enzo

2011-01-01

The early differentiation of Alzheimer's disease (AD) from frontotemporal dementia (FTD) may be difficult. The Tower of London (ToL), thought to assess executive functions such as planning and visuo-spatial working memory, could help in this purpose. Twentytwo Dementia Centers consecutively recruited patients with early FTD or AD. ToL performances of these groups were analyzed using both the conventional statistical approaches and the Artificial Neural Networks (ANNs) modelling. Ninety-four non aphasic FTD and 160 AD patients were recruited. ToL Accuracy Score (AS) significantly (p < 0.05) differentiated FTD from AD patients. However, the discriminant validity of AS checked by ROC curve analysis, yielded no significant results in terms of sensitivity and specificity (AUC 0.63). The performances of the 12 Success Subscores (SS) together with age, gender and schooling years were entered into advanced ANNs developed by Semeion Institute. The best ANNs were selected and submitted to ROC curves. The non-linear model was able to discriminate FTD from AD with an average AUC for 7 independent trials of 0.82. The use of hidden information contained in the different items of ToL and the non linear processing of the data through ANNs allows a high discrimination between FTD and AD in individual patients.

Associations between maternal antioxidant intakes in pregnancy and infant allergic outcomes.

PubMed

West, Christina E; Dunstan, Janet; McCarthy, Suzi; Metcalfe, Jessica; D'Vaz, Nina; Meldrum, Suzanne; Oddy, Wendy H; Tulic, Meri K; Prescott, Susan L

2012-11-14

Antioxidant intakes in pregnancy may influence fetal immune programming and the risk of allergic disease. We investigated associations between maternal intakes of β-carotene, vitamin C, vitamin E, copper and zinc, and infant allergic outcomes. Antioxidant intakes of pregnant women (n = 420) assessed prospectively by a food frequency questionnaire, were examined in relation to allergic outcomes at 1 year of age (n = 300). The main relationships with allergic outcomes were seen with dietary vitamin C and copper. Specifically, higher maternal dietary vitamin C intake was associated with a reduced risk of any diagnosed infant allergic disease and wheeze. After adjustment for potential confounders the relationship with wheeze remained statistically significant. There was also an inverse linear relationship between vitamin C and food allergy. Higher dietary copper intake was associated with reduced risk of eczema, wheeze and any allergic disease. The relationship with wheeze and any allergic disease remained statistically significant in multivariate analysis, and there was also an inverse linear relationship between copper and food allergy. However, these relationships were only seen for nutrients present in food. There were no relationships between β-carotene, vitamin E or zinc and any allergic outcomes. In summary, this study suggests that maternal diet of fresh foods rich in vitamin C is associated with reduced risk of infant wheeze, and that copper intake is associated with reduced risk of several allergic outcomes.

A genome-wide association study suggests new candidate genes for milk production traits in Chinese Holstein cattle.

PubMed

Yue, S J; Zhao, Y Q; Gu, X R; Yin, B; Jiang, Y L; Wang, Z H; Shi, K R

2017-12-01

A genome-wide association study (GWAS) was conducted on 15 milk production traits in Chinese Holstein. The experimental population consisted of 445 cattle, each genotyped by the GGP (GeneSeek genomic profiling)-BovineLD V3 SNP chip, which had 26 151 public SNPs in its manifest file. After data cleaning, 20 326 SNPs were retained for the GWAS. The phenotypes were estimated breeding values of traits, provided by a public dairy herd improvement program center that had been collected once a month for 3 years. Two statistical models, a fixed-effect linear regression model and a mixed-effect linear model, were used to estimate the association effects of SNPs on each of the phenotypes. Genome-wide significant and suggestive thresholds were set at 2.46E-06 and 4.95E-05 respectively. The two statistical models concurrently identified two genome-wide significant (P < 0.05) SNPs on milk production traits in this Chinese Holstein population. The positional candidate genes, which were the ones closest to these two identified SNPs, were EEF2K (eukaryotic elongation factor 2 kinase) and KLHL1 (kelch like family member 1). These two genes could serve as new candidate genes for milk yield and lactation persistence, yet their roles need to be verified in further function studies. © 2017 Stichting International Foundation for Animal Genetics.

Time-frequency Features for Impedance Cardiography Signals During Anesthesia Using Different Distribution Kernels.

PubMed

Muñoz, Jesús Escrivá; Gambús, Pedro; Jensen, Erik W; Vallverdú, Montserrat

2018-01-01

This works investigates the time-frequency content of impedance cardiography signals during a propofol-remifentanil anesthesia. In the last years, impedance cardiography (ICG) is a technique which has gained much attention. However, ICG signals need further investigation. Time-Frequency Distributions (TFDs) with 5 different kernels are used in order to analyze impedance cardiography signals (ICG) before the start of the anesthesia and after the loss of consciousness. In total, ICG signals from one hundred and thirty-one consecutive patients undergoing major surgery under general anesthesia were analyzed. Several features were extracted from the calculated TFDs in order to characterize the time-frequency content of the ICG signals. Differences between those features before and after the loss of consciousness were studied. The Extended Modified Beta Distribution (EMBD) was the kernel for which most features shows statistically significant changes between before and after the loss of consciousness. Among all analyzed features, those based on entropy showed a sensibility, specificity and area under the curve of the receiver operating characteristic above 60%. The anesthetic state of the patient is reflected on linear and non-linear features extracted from the TFDs of the ICG signals. Especially, the EMBD is a suitable kernel for the analysis of ICG signals and offers a great range of features which change according to the patient's anesthesia state in a statistically significant way. Schattauer GmbH.

An empirical evaluation of genetic distance statistics using microsatellite data from bear (Ursidae) populations.

PubMed

Paetkau, D; Waits, L P; Clarkson, P L; Craighead, L; Strobeck, C

1997-12-01

A large microsatellite data set from three species of bear (Ursidae) was used to empirically test the performance of six genetic distance measures in resolving relationships at a variety of scales ranging from adjacent areas in a continuous distribution to species that diverged several million years ago. At the finest scale, while some distance measures performed extremely well, statistics developed specifically to accommodate the mutational processes of microsatellites performed relatively poorly, presumably because of the relatively higher variance of these statistics. At the other extreme, no statistic was able to resolve the close sister relationship of polar bears and brown bears from more distantly related pairs of species. This failure is most likely due to constraints on allele distributions at microsatellite loci. At intermediate scales, both within continuous distributions and in comparisons to insular populations of late Pleistocene origin, it was not possible to define the point where linearity was lost for each of the statistics, except that it is clearly lost after relatively short periods of independent evolution. All of the statistics were affected by the amount of genetic diversity within the populations being compared, significantly complicating the interpretation of genetic distance data.

An Empirical Evaluation of Genetic Distance Statistics Using Microsatellite Data from Bear (Ursidae) Populations

PubMed Central

Paetkau, D.; Waits, L. P.; Clarkson, P. L.; Craighead, L.; Strobeck, C.

1997-01-01

A large microsatellite data set from three species of bear (Ursidae) was used to empirically test the performance of six genetic distance measures in resolving relationships at a variety of scales ranging from adjacent areas in a continuous distribution to species that diverged several million years ago. At the finest scale, while some distance measures performed extremely well, statistics developed specifically to accommodate the mutational processes of microsatellites performed relatively poorly, presumably because of the relatively higher variance of these statistics. At the other extreme, no statistic was able to resolve the close sister relationship of polar bears and brown bears from more distantly related pairs of species. This failure is most likely due to constraints on allele distributions at microsatellite loci. At intermediate scales, both within continuous distributions and in comparisons to insular populations of late Pleistocene origin, it was not possible to define the point where linearity was lost for each of the statistics, except that it is clearly lost after relatively short periods of independent evolution. All of the statistics were affected by the amount of genetic diversity within the populations being compared, significantly complicating the interpretation of genetic distance data. PMID:9409849

Statistical analysis of aerosol species, trace gasses, and meteorology in Chicago.

PubMed

Binaku, Katrina; O'Brien, Timothy; Schmeling, Martina; Fosco, Tinamarie

2013-09-01

Both canonical correlation analysis (CCA) and principal component analysis (PCA) were applied to atmospheric aerosol and trace gas concentrations and meteorological data collected in Chicago during the summer months of 2002, 2003, and 2004. Concentrations of ammonium, calcium, nitrate, sulfate, and oxalate particulate matter, as well as, meteorological parameters temperature, wind speed, wind direction, and humidity were subjected to CCA and PCA. Ozone and nitrogen oxide mixing ratios were also included in the data set. The purpose of statistical analysis was to determine the extent of existing linear relationship(s), or lack thereof, between meteorological parameters and pollutant concentrations in addition to reducing dimensionality of the original data to determine sources of pollutants. In CCA, the first three canonical variate pairs derived were statistically significant at the 0.05 level. Canonical correlation between the first canonical variate pair was 0.821, while correlations of the second and third canonical variate pairs were 0.562 and 0.461, respectively. The first canonical variate pair indicated that increasing temperatures resulted in high ozone mixing ratios, while the second canonical variate pair showed wind speed and humidity's influence on local ammonium concentrations. No new information was uncovered in the third variate pair. Canonical loadings were also interpreted for information regarding relationships between data sets. Four principal components (PCs), expressing 77.0 % of original data variance, were derived in PCA. Interpretation of PCs suggested significant production and/or transport of secondary aerosols in the region (PC1). Furthermore, photochemical production of ozone and wind speed's influence on pollutants were expressed (PC2) along with overall measure of local meteorology (PC3). In summary, CCA and PCA results combined were successful in uncovering linear relationships between meteorology and air pollutants in Chicago and aided in determining possible pollutant sources.

Assessing exotic plant species invasions and associated soil characteristics: A case study in eastern Rocky Mountain National Park, Colorado, USA, using the pixel nested plot design

USGS Publications Warehouse

Kalkhan, M.A.; Stafford, E.J.; Woodly, P.J.; Stohlgren, T.J.

2007-01-01

Rocky Mountain National Park (RMNP), Colorado, USA, contains a diversity of plant species. However, many exotic plant species have become established, potentially impacting the structure and function of native plant communities. Our goal was to quantify patterns of exotic plant species in relation to native plant species, soil characteristics, and other abiotic factors that may indicate or predict their establishment and success. Our research approach for field data collection was based on a field plot design called the pixel nested plot. The pixel nested plot provides a link to multi-phase and multi-scale spatial modeling-mapping techniques that can be used to estimate total species richness and patterns of plant diversity at finer landscape scales. Within the eastern region of RMNP, in an area of approximately 35,000 ha, we established a total of 60 pixel nested plots in 9 vegetation types. We used canonical correspondence analysis (CCA) and multiple linear regressions to quantify relationships between soil characteristics and native and exotic plant species richness and cover. We also used linear correlation, spatial autocorrelation and cross correlation statistics to test for the spatial patterns of variables of interest. CCA showed that exotic species were significantly (P < 0.05) associated with photosynthetically active radiation (r = 0.55), soil nitrogen (r = 0.58) and bare ground (r = -0.66). Pearson's correlation statistic showed significant linear relationships between exotic species, organic carbon, soil nitrogen, and bare ground. While spatial autocorrelations indicated that our 60 pixel nested plots were spatially independent, the cross correlation statistics indicated that exotic plant species were spatially associated with bare ground, in general, exotic plant species were most abundant in areas of high native species richness. This indicates that resource managers should focus on the protection of relatively rare native rich sites with little canopy cover, and fertile soils. Using the pixel nested plot approach for data collection can facilitate the ecological monitoring of these vulnerable areas at the landscape scale in a time- and cost-effective manner. ?? 2006 Elsevier B.V. All rights reserved.

Depression and Anxiety in Greek Male Veterans After Retirement.

PubMed

Kypraiou, Aspa; Sarafis, Pavlos; Tsounis, Andreas; Bitsi, Georgia; Andreanides, Elias; Constantinidis, Theodoros; Kotrotsiou, Evaggelia; Malliarou, Maria

2017-03-01

Retirement is a turning point in human life, resulting in changes to physical and mental health status. The aim of this study was to examine the factors that are related with depression and anxiety symptoms in Greek male veterans after retirement. A total of 502 veterans participated in a cross-sectional study. Beck Depression Inventory for depression assessment and Spielberger Trait Anxiety Inventory for anxiety assessment were used. The Ethics Committee of the Technological Educational Institution of Thessaly granted permission for conducting the research, and informed consent was obtained from all the participants. Questionnaires were filled in electronically using a platform that was made for the specific research. Mean values, standard deviations, Student t test, nonparametric cluster analysis of variance, Pearson's and Spearman's coefficients, and linear regression were conducted, using the Statistical Program for Social Services version 19.0. Severe depression was found in 3.8% of veterans with a mean score of 6.78, whereas 23.2% displayed mild-to-moderate symptoms of depression. Mean score of state anxiety was found to be 36.55 and of trait anxiety 33.60. Veterans who were discharged because of stressful working conditions, those who have a high body mass index, consume regularly alcohol, smoke and were not satisfied by changes in their everyday life after retirement had significantly more symptoms of depression and anxiety, although those who retired because of family problems had significantly more symptoms of depression. Multivariate linear regression analyses indicated that dissatisfaction related to lifestyle changes had statistically significant effect on symptoms of depression and anxiety, and stressful working conditions as a leading cause for retirement had statistically significant effect on depression. Finally, according to linear regression analyses results, those who were satisfied with their professional evolution had 1.80 times lower score in depression scale. The sense of satisfaction derived from fulfilling work-related expectations when finishing a career, with changes in everyday life, and smoking and alcohol reduction, may contribute to a better adjustment during the retirement period. To our knowledge, this was the first study examining depression and anxiety levels in Greek veterans, and the sample size was large, covering a randomly chosen veteran population. On the other, it was a convenient sample, although the study results could not focus on direct-term effects of retirement (up to 3 years of retirement from active service). Primitive data may be used for research directions in the future. Reprint & Copyright © 2017 Association of Military Surgeons of the U.S.

Do US metropolitan core counties have lower scope 1 and 2 CO2 emissions than less urbanized counties?

NASA Astrophysics Data System (ADS)

Tamayao, M. M.; Blackhurst, M. F.; Matthews, H. S.

2014-10-01

Recent sustainability research has focused on urban systems given their high share of environmental impacts and potential for centralized impact mitigation. Recent research emphasizes descriptive statistics from place-based case studies to argue for policy action. This limits the potential for general insights and decision support. Here, we implement generalized linear and multiple linear regression analyses to obtain more robust insights on the relationship between urbanization and greenhouse gas (GHG) emissions in the US We used consistently derived county-level scope 1 and scope 2 GHG inventories for our response variable while predictor variables included dummy-coded variables for county geographic type (central, outlying, and nonmetropolitan), median household income, population density, and climate indices (heating degree days (HDD) and cooling degree days (CDD)). We find that there is not enough statistical evidence indicating per capita scope 1 and 2 emissions differ by geographic type, ceteris paribus. These results are robust for different assumed electricity emissions factors. We do find statistically significant differences in per capita emissions by sector for different county types, with transportation and residential emissions highest in nonmetropolitan (rural) counties, transportation emissions lowest in central counties, and commercial sector emissions highest in central counties. These results indicate the importance of regional land use and transportation dynamics when planning local emissions mitigation measures.

Linear regression analysis of Hospital Episode Statistics predicts a large increase in demand for elective hand surgery in England.

PubMed

Bebbington, Emily; Furniss, Dominic

2015-02-01

We integrated two factors, demographic population shifts and changes in prevalence of disease, to predict future trends in demand for hand surgery in England, to facilitate workforce planning. We analysed Hospital Episode Statistics data for Dupuytren's disease, carpal tunnel syndrome, cubital tunnel syndrome, and trigger finger from 1998 to 2011. Using linear regression, we estimated trends in both diagnosis and surgery until 2030. We integrated this regression with age specific population data from the Office for National Statistics in order to estimate how this will contribute to a change in workload over time. There has been a significant increase in both absolute numbers of diagnoses and surgery for all four conditions. Combined with future population data, we calculate that the total operative burden for these four conditions will increase from 87,582 in 2011 to 170,166 (95% confidence interval 144,517-195,353) in 2030. The prevalence of these diseases in the ageing population, and increasing prevalence of predisposing factors such as obesity and diabetes, may account for the predicted increase in workload. The most cost effective treatments must be sought, which requires high quality clinical trials. Our methodology can be applied to other sub-specialties to help anticipate the need for future service provision. Copyright © 2014 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

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.

The VIMOS Public Extragalactic Redshift Survey (VIPERS). Measuring non-linear galaxy bias at z ~ 0.8

NASA Astrophysics Data System (ADS)

Di Porto, C.; Branchini, E.; Bel, J.; Marulli, F.; Bolzonella, M.; Cucciati, O.; de la Torre, S.; Granett, B. R.; Guzzo, L.; Marinoni, C.; Moscardini, L.; Abbas, U.; Adami, C.; Arnouts, S.; Bottini, D.; Cappi, A.; Coupon, J.; Davidzon, I.; De Lucia, G.; Fritz, A.; Franzetti, P.; Fumana, M.; Garilli, B.; Ilbert, O.; Iovino, A.; Krywult, J.; Le Brun, V.; Le Fèvre, O.; Maccagni, D.; Małek, K.; McCracken, H. J.; Paioro, L.; Polletta, M.; Pollo, A.; Scodeggio, M.; Tasca, L. A. M.; Tojeiro, R.; Vergani, D.; Zanichelli, A.; Burden, A.; Marchetti, A.; Martizzi, D.; Mellier, Y.; Nichol, R. C.; Peacock, J. A.; Percival, W. J.; Viel, M.; Wolk, M.; Zamorani, G.

2016-10-01

Aims: We use the first release of the VImos Public Extragalactic Redshift Survey of galaxies (VIPERS) of ~50 000 objects to measure the biasing relation between galaxies and mass in the redshift range z = [ 0.5,1.1 ]. Methods: We estimate the 1-point distribution function [PDF] of VIPERS galaxies from counts in cells and, assuming a model for the mass PDF, we infer their mean bias relation. The reconstruction of the bias relation is performed through a novel method that accounts for Poisson noise, redshift distortions, inhomogeneous sky coverage. and other selection effects. With this procedure we constrain galaxy bias and its deviations from linearity down to scales as small as 4 h-1 Mpc and out to z = 1.1. Results: We detect small (up to 2%) but statistically significant (up to 3σ) deviations from linear bias. The mean biasing function is close to linear in regions above the mean density. The mean slope of the biasing relation is a proxy to the linear bias parameter. This slope increases with luminosity, which is in agreement with results of previous analyses. We detect a strong bias evolution only for z> 0.9, which is in agreement with some, but not all, previous studies. We also detect a significant increase of the bias with the scale, from 4 to 8 h-1 Mpc , now seen for the first time out to z = 1. The amplitude of non-linearity depends on redshift, luminosity, and scale, but no clear trend is detected. Owing to the large cosmic volume probed by VIPERS, we find that the mismatch between the previous estimates of bias at z ~ 1 from zCOSMOS and VVDS-Deep galaxy samples is fully accounted for by cosmic variance. Conclusions: The results of our work confirm the importance of going beyond the over-simplistic linear bias hypothesis showing that non-linearities can be accurately measured through the applications of the appropriate statistical tools to existing datasets like VIPERS. Based on observations collected at the European Southern Observatory, Paranal, Chile, under programmes 182.A-0886 (LP) at the Very Large Telescope, and also based on observations obtained with MegaPrime/MegaCam, a joint project of CFHT and CEA/DAPNIA, at the Canada-France-Hawaii Telescope (CFHT), which is operated by the National Research Council (NRC) of Canada, the Institut National des Science de l'Univers of the Centre National de la Recherche Scientifique (CNRS) of France, and the University of Hawaii. This work is based in part on data products produced at TERAPIX and the Canadian Astronomy Data Centre as part of the Canada-France-Hawaii Telescope Legacy Survey, a collaborative project of NRC and CNRS. The VIPERS web site is http://vipers.inaf.it/

Exploring the efficacy of replacing linear paper-based patient cases in problem-based learning with dynamic Web-based virtual patients: randomized controlled trial.

PubMed

Poulton, Terry; Ellaway, Rachel H; Round, Jonathan; Jivram, Trupti; Kavia, Sheetal; Hilton, Sean

2014-11-05

Problem-based learning (PBL) is well established in medical education and beyond, and continues to be developed and explored. Challenges include how to connect the somewhat abstract nature of classroom-based PBL with clinical practice and how to maintain learner engagement in the process of PBL over time. A study was conducted to investigate the efficacy of decision-PBL (D-PBL), a variant form of PBL that replaces linear PBL cases with virtual patients. These Web-based interactive cases provided learners with a series of patient management pathways. Learners were encouraged to consider and discuss courses of action, take their chosen management pathway, and experience the consequences of their decisions. A Web-based application was essential to allow scenarios to respond dynamically to learners' decisions, to deliver the scenarios to multiple PBL classrooms in the same timeframe, and to record centrally the paths taken by the PBL groups. A randomized controlled trial in crossover design was run involving all learners (N=81) in the second year of the graduate entry stream for the undergraduate medicine program at St George's University of London. Learners were randomized to study groups; half engaged in a D-PBL activity whereas the other half had a traditional linear PBL activity on the same subject material. Groups alternated D-PBL and linear PBL over the semester. The measure was mean cohort performance on specific face-to-face exam questions at the end of the semester. D-PBL groups performed better than linear PBL groups on questions related to D-PBL with the difference being statistically significant for all questions. Differences between the exam performances of the 2 groups were not statistically significant for the questions not related to D-PBL. The effect sizes for D-PBL-related questions were large and positive (>0.6) except for 1 question that showed a medium positive effect size. The effect sizes for questions not related to D-PBL were all small (≤0.3) with a mix of positive and negative values. The efficacy of D-PBL was indicated by improved exam performance for learners who had D-PBL compared to those who had linear PBL. This suggests that the use of D-PBL leads to better midterm learning outcomes than linear PBL, at least for learners with prior experience with linear PBL. On the basis of tutor and student feedback, St George's University of London and the University of Nicosia, Cyprus have replaced paper PBL cases for midstage undergraduate teaching with D-PBL virtual patients, and 6 more institutions in the ePBLnet partnership will be implementing D-PBL in Autumn 2015.

A novel predictive pharmacokinetic/pharmacodynamic model of repolarization prolongation derived from the effects of terfenadine, cisapride and E-4031 in the conscious chronic av node--ablated, His bundle-paced dog.

PubMed

Nolan, Emily R; Feng, Meihua Rose; Koup, Jeffrey R; Liu, Jing; Turluck, Daniel; Zhang, Yiqun; Paulissen, Jerome B; Olivier, N Bari; Miller, Teresa; Bailie, Marc B

2006-01-01

Terfenadine, cisapride, and E-4031, three drugs that prolong ventricular repolarization, were selected to evaluate the sensitivity of the conscious chronic atrioventricular node--ablated, His bundle-paced Dog for defining drug induced cardiac repolarization prolongation. A novel predictive pharmacokinetic/pharmacodynamic model of repolarization prolongation was generated from these data. Three male beagle dogs underwent radiofrequency AV nodal ablation, and placement of a His bundle-pacing lead and programmable pacemaker under anesthesia. Each dog was restrained in a sling for a series of increasing dose infusions of each drug while maintained at a constant heart rate of 80 beats/min. RT interval, a surrogate for QT interval in His bundle-paced dogs, was recorded throughout the experiment. E-4031 induced a statistically significant RT prolongation at the highest three doses. Cisapride resulted in a dose-dependent increase in RT interval, which was statistically significant at the two highest doses. Terfenadine induced a dose-dependent RT interval prolongation with a statistically significant change occurring only at the highest dose. The relationship between drug concentration and RT interval change was described by a sigmoid E(max) model with an effect site. Maximum RT change (E(max)), free drug concentration at half of the maximum effect (EC(50)), and free drug concentration associated with a 10 ms RT prolongation (EC(10 ms)) were estimated. A linear correlation between EC(10 ms) and HERG IC(50) values was identified. The conscious dog with His bundle-pacing detects delayed cardiac repolarization related to I(Kr) inhibition, and detects repolarization change induced by drugs with activity at multiple ion channels. A clinically relevant sensitivity and a linear correlation with in vitro HERG data make the conscious His bundle-paced dog a valuable tool for detecting repolarization effect of new chemical entities.

Influence of Cobb Angle and ISIS2 Surface Topography Volumetric Asymmetry on Scoliosis Research Society-22 Outcome Scores in Scoliosis.

PubMed

Brewer, Paul; Berryman, Fiona; Baker, De; Pynsent, Paul; Gardner, Adrian

2013-11-01

Retrospective sequential patient series. To establish the relationship between the magnitude of the deformity in scoliosis and patients' perception of their condition, as measured with Scoliosis Research Society-22 scores. A total of 93 untreated patients with adolescent idiopathic scoliosis were included retrospectively. The Cobb angle was measured from a plain radiograph, and volumetric asymmetry was measured by ISIS2 surface topography. The association between Scoliosis Research Society scores for function, pain, self-image, and mental health against Cobb angle and volumetric asymmetry was investigated using the Pearson correlation coefficient. Correlation of both Cobb angle and volumetric asymmetry with function and pain was weak (all < .23); these correlation values were not statistically significant. Correlation of Cobb angle and volumetric asymmetry with self-image, was higher, although still moderate (-.37 for Cobb angle and -.44 for volumetric asymmetry). Both were statistically significant (Cobb angle, p = .0002; volumetric asymmetry; p = .00001). Cobb angle contributed 13.8% to the linear relationship with self-image, whereas volumetric asymmetry contributed 19.3%. For mental health, correlation was statistically significant with Cobb angle (p = .011) and volumetric asymmetry (p = .0005), but the correlation was low to moderate (-.26 and -.35, respectively). Cobb angle contributed 6.9% to the linear relationship with mental health, whereas volumetric asymmetry contributed 12.4%. Volumetric asymmetry correlates better with both mental health and self-image compared with Cobb angle, but the correlation was only moderate. This study suggests that a patient's own perception of self-image and mental health is multifactorial and not completely explained through present objective measurements of the size of the deformity. This helps to explain the difficulties in any objective analysis of a problem with multifactorial perception issues. Further study is required to investigate other physical aspects of the deformity that may have a role in how patients view themselves. Copyright © 2013 Scoliosis Research Society. Published by Elsevier Inc. All rights reserved.

Work as a street vendor, associated traffic-related air pollution exposures and risk of adverse pregnancy outcomes in Accra, Ghana.

PubMed

Amegah, Adeladza Kofi; Jaakkola, Jouni J K

2014-03-01

Street vending, a dominant occupation in urban areas of developing countries exposes the vendors to several environmental pollutants. We investigated whether work as street vendor impairs foetal growth and shortens gestational duration, and evaluated to what extent exposure to traffic-related air pollution is responsible for these adverse effects. A cross-sectional study was conducted among mothers and their newborns accessing postnatal services at the Korle Bu Teaching Hospital in Accra, Ghana in 2010, focusing on 105 street vendors and a reference group of 281 mothers. We categorized exposure to traffic-related air pollution on the basis of street vending activity patterns and traffic density in the working area. Multivariate linear regression analysis adjusting for age, social class, marital status and gravidity of mothers, sex of neonate, and indoor air pollution, indicated a 177 g (95% CI: 324, 31) reduction in birth weight among street vendors. Sensitivity analysis performed by restricting the analysis to term births showed further reductions in birth weight. Generalized linear models adjusting for confounders indicated a 35% (risk ratio (RR)=1.35; 95% CI: 0.87, 2.12) increased risk of LBW, albeit statistically not significant. LBW risk increased in the sensitivity analysis but was also not statistically significant. The risk of PTB was not associated with street vending (RR=1.03; 95% CI: 0.67, 1.58). The exposure-response relations observed were not consistent. Moderate activity patterns and high traffic density jointly was associated with a statistically significant 84% (RR=1.84; 95% CI: 1.05, 3.24) increased risk of LBW. Street vending during pregnancy is a determinant of average foetal growth and risk of LBW. More research is required to further quantify their effects on pregnancy outcomes and safeguard maternal and perinatal health in developing countries. Copyright © 2013 Elsevier GmbH. All rights reserved.

Evaluation of pharyngeal space and its correlation with mandible and hyoid bone in patients with different skeletal classes and facial types.

PubMed

Nejaim, Yuri; Aps, Johan K M; Groppo, Francisco Carlos; Haiter Neto, Francisco

2018-06-01

The purpose of this article was to evaluate the pharyngeal space volume, and the size and shape of the mandible and the hyoid bone, as well as their relationships, in patients with different facial types and skeletal classes. Furthermore, we estimated the volume of the pharyngeal space with a formula using only linear measurements. A total of 161 i-CAT Next Generation (Imaging Sciences International, Hatfield, Pa) cone-beam computed tomography images (80 men, 81 women; ages, 21-58 years; mean age, 27 years) were retrospectively studied. Skeletal class and facial type were determined for each patient from multiplanar reconstructions using the NemoCeph software (Nemotec, Madrid, Spain). Linear and angular measurements were performed using 3D imaging software (version 3.4.3; Carestream Health, Rochester, NY), and volumetric analysis of the pharyngeal space was carried out with ITK-SNAP (version 2.4.0; Cognitica, Philadelphia, Pa) segmentation software. For the statistics, analysis of variance and the Tukey test with a significance level of 0.05, Pearson correlation, and linear regression were used. The pharyngeal space volume, when correlated with mandible and hyoid bone linear and angular measurements, showed significant correlations with skeletal class or facial type. The linear regression performed to estimate the volume of the pharyngeal space showed an R of 0.92 and an adjusted R 2 of 0.8362. There were significant correlations between pharyngeal space volume, and the mandible and hyoid bone measurements, suggesting that the stomatognathic system should be evaluated in an integral and nonindividualized way. Furthermore, it was possible to develop a linear regression model, resulting in a useful formula for estimating the volume of the pharyngeal space. Copyright © 2018 American Association of Orthodontists. Published by Elsevier Inc. All rights reserved.

Boxing and mixed martial arts: preliminary traumatic neuromechanical injury risk analyses from laboratory impact dosage data.

PubMed

Bartsch, Adam J; Benzel, Edward C; Miele, Vincent J; Morr, Douglas R; Prakash, Vikas

2012-05-01

In spite of ample literature pointing to rotational and combined impact dosage being key contributors to head and neck injury, boxing and mixed martial arts (MMA) padding is still designed to primarily reduce cranium linear acceleration. The objects of this study were to quantify preliminary linear and rotational head impact dosage for selected boxing and MMA padding in response to hook punches; compute theoretical skull, brain, and neck injury risk metrics; and statistically compare the protective effect of various glove and head padding conditions. An instrumented Hybrid III 50th percentile anthropomorphic test device (ATD) was struck in 54 pendulum impacts replicating hook punches at low (27-29 J) and high (54-58 J) energy. Five padding combinations were examined: unpadded (control), MMA glove-unpadded head, boxing glove-unpadded head, unpadded pendulum-boxing headgear, and boxing glove-boxing headgear. A total of 17 injury risk parameters were measured or calculated. All padding conditions reduced linear impact dosage. Other parameters significantly decreased, significantly increased, or were unaffected depending on padding condition. Of real-world conditions (MMA glove-bare head, boxing glove-bare head, and boxing glove-headgear), the boxing glove-headgear condition showed the most meaningful reduction in most of the parameters. In equivalent impacts, the MMA glove-bare head condition induced higher rotational dosage than the boxing glove-bare head condition. Finite element analysis indicated a risk of brain strain injury in spite of significant reduction of linear impact dosage. In the replicated hook punch impacts, all padding conditions reduced linear but not rotational impact dosage. Head and neck dosage theoretically accumulates fastest in MMA and boxing bouts without use of protective headgear. The boxing glove-headgear condition provided the best overall reduction in impact dosage. More work is needed to develop improved protective padding to minimize linear and rotational impact dosage and develop next-generation standards for head and neck injury risk.

Statistical assessment of bi-exponential diffusion weighted imaging signal characteristics induced by intravoxel incoherent motion in malignant breast tumors

PubMed Central

Wong, Oi Lei; Lo, Gladys G.; Chan, Helen H. L.; Wong, Ting Ting; Cheung, Polly S. Y.

2016-01-01

Background The purpose of this study is to statistically assess whether bi-exponential intravoxel incoherent motion (IVIM) model better characterizes diffusion weighted imaging (DWI) signal of malignant breast tumor than mono-exponential Gaussian diffusion model. Methods 3 T DWI data of 29 malignant breast tumors were retrospectively included. Linear least-square mono-exponential fitting and segmented least-square bi-exponential fitting were used for apparent diffusion coefficient (ADC) and IVIM parameter quantification, respectively. F-test and Akaike Information Criterion (AIC) were used to statistically assess the preference of mono-exponential and bi-exponential model using region-of-interests (ROI)-averaged and voxel-wise analysis. Results For ROI-averaged analysis, 15 tumors were significantly better fitted by bi-exponential function and 14 tumors exhibited mono-exponential behavior. The calculated ADC, D (true diffusion coefficient) and f (pseudo-diffusion fraction) showed no significant differences between mono-exponential and bi-exponential preferable tumors. Voxel-wise analysis revealed that 27 tumors contained more voxels exhibiting mono-exponential DWI decay while only 2 tumors presented more bi-exponential decay voxels. ADC was consistently and significantly larger than D for both ROI-averaged and voxel-wise analysis. Conclusions Although the presence of IVIM effect in malignant breast tumors could be suggested, statistical assessment shows that bi-exponential fitting does not necessarily better represent the DWI signal decay in breast cancer under clinically typical acquisition protocol and signal-to-noise ratio (SNR). Our study indicates the importance to statistically examine the breast cancer DWI signal characteristics in practice. PMID:27709078

The impact of mother's literacy on child dental caries: Individual data or aggregate data analysis?

PubMed

Haghdoost, Ali-Akbar; Hessari, Hossein; Baneshi, Mohammad Reza; Rad, Maryam; Shahravan, Arash

2017-01-01

To evaluate the impact of mother's literacy on child dental caries based on a national oral health survey in Iran and to investigate the possibility of ecological fallacy in aggregate data analysis. Existing data were from second national oral health survey that was carried out in 2004, which including 8725 6 years old participants. The association of mother's literacy with caries occurrence (DMF (Decayed, Missing, Filling) total score >0) of her child was assessed using individual data by logistic regression model. Then the association of the percentages of mother's literacy and the percentages of decayed teeth in each 30 provinces of Iran was assessed using aggregated data retrieved from the data of second national oral health survey of Iran and alternatively from census of "Statistical Center of Iran" using linear regression model. The significance level was set at 0.05 for all analysis. Individual data analysis showed a statistically significant association between mother's literacy and decayed teeth of children ( P = 0.02, odds ratio = 0.83). There were not statistical significant association between mother's literacy and child dental caries in aggregate data analysis of oral health survey ( P = 0.79, B = 0.03) and census of "Statistical Center of Statistics" ( P = 0.60, B = 0.14). Literate mothers have a preventive effect on occurring dental caries of children. According to the high percentage of illiterate parents in Iran, it's logical to consider suitable methods of oral health education which do not need reading or writing. Aggregate data analysis and individual data analysis had completely different results in this study.

Robust Combining of Disparate Classifiers Through Order Statistics

NASA Technical Reports Server (NTRS)

Tumer, Kagan; Ghosh, Joydeep

2001-01-01

Integrating the outputs of multiple classifiers via combiners or meta-learners has led to substantial improvements in several difficult pattern recognition problems. In this article we investigate a family of combiners based on order statistics, for robust handling of situations where there are large discrepancies in performance of individual classifiers. Based on a mathematical modeling of how the decision boundaries are affected by order statistic combiners, we derive expressions for the reductions in error expected when simple output combination methods based on the the median, the maximum and in general, the ith order statistic, are used. Furthermore, we analyze the trim and spread combiners, both based on linear combinations of the ordered classifier outputs, and show that in the presence of uneven classifier performance, they often provide substantial gains over both linear and simple order statistics combiners. Experimental results on both real world data and standard public domain data sets corroborate these findings.

Tentative explanatory variable of lung dust concentration in gold miners exposed to crystalline silica.

PubMed

Dufresne, A; Loosereewanich, P; Bégin, R; Dion, C; Ecobichon, D; Muir, D C; Ritchie, A C; Perrault, G

1998-01-01

The first objective of the study was to investigate the relationships between quantitative lung mineral dust burdens, dust exposure history, and pathological fibrosis grading in silicotic workers. The second objective was to evaluate the association between particle size parameters, concentration of retained silica particles and the severity of the silicosis. Sixty-seven paraffin-embedded lung tissue samples of silicotic patients were analyzed. The cases of silicosis included 39 non-lung cancer patients and 28 patients with lung cancer. All of the cases were gold miners in the Province of Ontario, Canada. Particles, both angular and fibrous, were extracted from lung parenchyma by a bleach digestion method, mounted on copper microscopic grids by a carbon replica technique, and analyzed by transmission electron microscopy (TEM) and energy dispersive spectroscopy (EDS). Quartz concentration was also determined by X-ray diffraction (XRD) on a silver membrane filter after the extraction from the lung parenchyma. Total particles, silica, clay, and quartz also increase in concentration with increased age at death, although the trends are not statistically significant. Quartz concentration has a statistically significant correlation with the silicosis severity score (r = +0.45, p < 0.001), with the geometric mean concentration increasing from 2.24 micrograms/mg in the group having silicosis severity score less than 1 to 4.80 micrograms/mg in group with highest score. Quartz concentration is the only significant explanatory variable of the silicosis severity with a regression coefficient of +0.41 (p < 0.001). Among several dust exposure variables extracted from the work history of the miners, the calendar year of first exposure was the primary significant determinant of lung retained total particles, silica, and clay minerals, except for quartz. A statistically significant linear relationship between lung quartz concentration and silicosis severity in the gold miners was observed (p < 0.001). Among the several types of lung particles detected, quartz was the only significant determinant of the silicosis severity in the gold miners in this study and vice versa, although it explained only 20% of the variation in the severity. This study suggested no significant linear relationship between the duration of dust exposure and the lung burden of any particle types in the gold miners.

A Clinical Comparative Study of 3-Dimensional Accuracy between Digital and Conventional Implant Impression Techniques.

PubMed

Alsharbaty, Mohammed Hussein M; Alikhasi, Marzieh; Zarrati, Simindokht; Shamshiri, Ahmed Reza

2018-02-09

To evaluate the accuracy of a digital implant impression technique using a TRIOS 3Shape intraoral scanner (IOS) compared to conventional implant impression techniques (pick-up and transfer) in clinical situations. Thirty-six patients who had two implants (Implantium, internal connection) ranging in diameter between 3.8 and 4.8 mm in posterior regions participated in this study after signing a consent form. Thirty-six reference models (RM) were fabricated by attaching two impression copings intraorally, splinted with autopolymerizing acrylic resin, verified by sectioning through the middle of the index, and rejoined again with freshly mixed autopolymerizing acrylic resin pattern (Pattern Resin) with the brush bead method. After that, the splinted assemblies were attached to implant analogs (DANSE) and impressed with type III dental stone (Gypsum Microstone) in standard plastic die lock trays. Thirty-six working casts were fabricated for each conventional impression technique (i.e., pick-up and transfer). Thirty-six digital impressions were made with a TRIOS 3Shape IOS. Eight of the digitally scanned files were damaged; 28 digital scan files were retrieved to STL format. A coordinate-measuring machine (CMM) was used to record linear displacement measurements (x, y, and z-coordinates), interimplant distances, and angular displacements for the RMs and conventionally fabricated working casts. CATIA 3D evaluation software was used to assess the digital STL files for the same variables as the CMM measurements. CMM measurements made on the RMs and conventionally fabricated working casts were compared with 3D software measurements made on the digitally scanned files. Data were statistically analyzed using the generalized estimating equation (GEE) with an exchangeable correlation matrix and linear method, followed by the Bonferroni method for pairwise comparisons (α = 0.05). The results showed significant differences between the pick-up and digital groups in all of the measured variables (p < 0.001). Concerning the transfer and digital groups, the results were statistically significant in angular displacement (p < 0.001), distance measurements (p = 0.01), and linear displacement (p = 0.03); however, between the pick-up and transfer groups, there was no statistical significance in all of the measured variables (interimplant distance deviation, linear displacement, and angular displacement deviations). According to the results of this study, the digital implant impression technique had the least accuracy. Based on the study outcomes, distance and angulation errors associated with the intraoral digital implant impressions were too large to fabricate well-fitting restorations for partially edentulous patients. The pick-up implant impression technique was the most accurate, and the transfer technique revealed comparable accuracy to it. © 2018 by the American College of Prosthodontists.

Examining the predictive accuracy of the novel 3D N-linear algebraic molecular codifications on benchmark datasets.

PubMed

García-Jacas, César R; Contreras-Torres, Ernesto; Marrero-Ponce, Yovani; Pupo-Meriño, Mario; Barigye, Stephen J; Cabrera-Leyva, Lisset

2016-01-01

Recently, novel 3D alignment-free molecular descriptors (also known as QuBiLS-MIDAS) based on two-linear, three-linear and four-linear algebraic forms have been introduced. These descriptors codify chemical information for relations between two, three and four atoms by using several (dis-)similarity metrics and multi-metrics. Several studies aimed at assessing the quality of these novel descriptors have been performed. However, a deeper analysis of their performance is necessary. Therefore, in the present manuscript an assessment and statistical validation of the performance of these novel descriptors in QSAR studies is performed. To this end, eight molecular datasets (angiotensin converting enzyme, acetylcholinesterase inhibitors, benzodiazepine receptor, cyclooxygenase-2 inhibitors, dihydrofolate reductase inhibitors, glycogen phosphorylase b, thermolysin inhibitors, thrombin inhibitors) widely used as benchmarks in the evaluation of several procedures are utilized. Three to nine variable QSAR models based on Multiple Linear Regression are built for each chemical dataset according to the original division into training/test sets. Comparisons with respect to leave-one-out cross-validation correlation coefficients[Formula: see text] reveal that the models based on QuBiLS-MIDAS indices possess superior predictive ability in 7 of the 8 datasets analyzed, outperforming methodologies based on similar or more complex techniques such as: Partial Least Square, Neural Networks, Support Vector Machine and others. On the other hand, superior external correlation coefficients[Formula: see text] are attained in 6 of the 8 test sets considered, confirming the good predictive power of the obtained models. For the [Formula: see text] values non-parametric statistic tests were performed, which demonstrated that the models based on QuBiLS-MIDAS indices have the best global performance and yield significantly better predictions in 11 of the 12 QSAR procedures used in the comparison. Lastly, a study concerning to the performance of the indices according to several conformer generation methods was performed. This demonstrated that the quality of predictions of the QSAR models based on QuBiLS-MIDAS indices depend on 3D structure generation method considered, although in this preliminary study the results achieved do not present significant statistical differences among them. As conclusions it can be stated that the QuBiLS-MIDAS indices are suitable for extracting structural information of the molecules and thus, constitute a promissory alternative to build models that contribute to the prediction of pharmacokinetic, pharmacodynamics and toxicological properties on novel compounds.Graphical abstractComparative graphical representation of the performance of the novel QuBiLS-MIDAS 3D-MDs with respect to other methodologies in QSAR modeling of eight chemical datasets.

Linear and Order Statistics Combiners for Pattern Classification

NASA Technical Reports Server (NTRS)

Tumer, Kagan; Ghosh, Joydeep; Lau, Sonie (Technical Monitor)

2001-01-01

Several researchers have experimentally shown that substantial improvements can be obtained in difficult pattern recognition problems by combining or integrating the outputs of multiple classifiers. This chapter provides an analytical framework to quantify the improvements in classification results due to combining. The results apply to both linear combiners and order statistics combiners. We first show that to a first order approximation, the error rate obtained over and above the Bayes error rate, is directly proportional to the variance of the actual decision boundaries around the Bayes optimum boundary. Combining classifiers in output space reduces this variance, and hence reduces the 'added' error. If N unbiased classifiers are combined by simple averaging. the added error rate can be reduced by a factor of N if the individual errors in approximating the decision boundaries are uncorrelated. Expressions are then derived for linear combiners which are biased or correlated, and the effect of output correlations on ensemble performance is quantified. For order statistics based non-linear combiners, we derive expressions that indicate how much the median, the maximum and in general the i-th order statistic can improve classifier performance. The analysis presented here facilitates the understanding of the relationships among error rates, classifier boundary distributions, and combining in output space. Experimental results on several public domain data sets are provided to illustrate the benefits of combining and to support the analytical results.

Statistics of galaxy orientations - Morphology and large-scale structure

NASA Technical Reports Server (NTRS)

Lambas, Diego G.; Groth, Edward J.; Peebles, P. J. E.

1988-01-01

Using the Uppsala General Catalog of bright galaxies and the northern and southern maps of the Lick counts of galaxies, statistical evidence of a morphology-orientation effect is found. Major axes of elliptical galaxies are preferentially oriented along the large-scale features of the Lick maps. However, the orientations of the major axes of spiral and lenticular galaxies show no clear signs of significant nonrandom behavior at a level of less than about one-fifth of the effect seen for ellipticals. The angular scale of the detected alignment effect for Uppsala ellipticals extends to at least theta of about 2 deg, which at a redshift of z of about 0.02 corresponds to a linear scale of about 2/h Mpc.

QSAR study of curcumine derivatives as HIV-1 integrase inhibitors.

PubMed

Gupta, Pawan; Sharma, Anju; Garg, Prabha; Roy, Nilanjan

2013-03-01

A QSAR study was performed on curcumine derivatives as HIV-1 integrase inhibitors using multiple linear regression. The statistically significant model was developed with squared correlation coefficients (r(2)) 0.891 and cross validated r(2) (r(2) cv) 0.825. The developed model revealed that electronic, shape, size, geometry, substitution's information and hydrophilicity were important atomic properties for determining the inhibitory activity of these molecules. The model was also tested successfully for external validation (r(2) pred = 0.849) as well as Tropsha's test for model predictability. Furthermore, the domain analysis was carried out to evaluate the prediction reliability of external set molecules. The model was statistically robust and had good predictive power which can be successfully utilized for screening of new molecules.

Neck-focused panic attacks among Cambodian refugees; a logistic and linear regression analysis.

PubMed

Hinton, Devon E; Chhean, Dara; Pich, Vuth; Um, Khin; Fama, Jeanne M; Pollack, Mark H

2006-01-01

Consecutive Cambodian refugees attending a psychiatric clinic were assessed for the presence and severity of current--i.e., at least one episode in the last month--neck-focused panic. Among the whole sample (N=130), in a logistic regression analysis, the Anxiety Sensitivity Index (ASI; odds ratio=3.70) and the Clinician-Administered PTSD Scale (CAPS; odds ratio=2.61) significantly predicted the presence of current neck panic (NP). Among the neck panic patients (N=60), in the linear regression analysis, NP severity was significantly predicted by NP-associated flashbacks (beta=.42), NP-associated catastrophic cognitions (beta=.22), and CAPS score (beta=.28). Further analysis revealed the effect of the CAPS score to be significantly mediated (Sobel test [Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173-1182]) by both NP-associated flashbacks and catastrophic cognitions. In the care of traumatized Cambodian refugees, NP severity, as well as NP-associated flashbacks and catastrophic cognitions, should be specifically assessed and treated.

Statistical analysis and interpretation of prenatal diagnostic imaging studies, Part 2: descriptive and inferential statistical methods.

PubMed

Tuuli, Methodius G; Odibo, Anthony O

2011-08-01

The objective of this article is to discuss the rationale for common statistical tests used for the analysis and interpretation of prenatal diagnostic imaging studies. Examples from the literature are used to illustrate descriptive and inferential statistics. The uses and limitations of linear and logistic regression analyses are discussed in detail.

Grip Strength Is Associated With Cognitive Performance in Schizophrenia and the General Population: A UK Biobank Study of 476559 Participants.

PubMed

Firth, Joseph; Stubbs, Brendon; Vancampfort, Davy; Firth, Josh A; Large, Matthew; Rosenbaum, Simon; Hallgren, Mats; Ward, Philip B; Sarris, Jerome; Yung, Alison R

2018-06-06

Handgrip strength may provide an easily-administered marker of cognitive functional status. However, further population-scale research examining relationships between grip strength and cognitive performance across multiple domains is needed. Additionally, relationships between grip strength and cognitive functioning in people with schizophrenia, who frequently experience cognitive deficits, has yet to be explored. Baseline data from the UK Biobank (2007-2010) was analyzed; including 475397 individuals from the general population, and 1162 individuals with schizophrenia. Linear mixed models and generalized linear mixed models were used to assess the relationship between grip strength and 5 cognitive domains (visual memory, reaction time, reasoning, prospective memory, and number memory), controlling for age, gender, bodyweight, education, and geographical region. In the general population, maximal grip strength was positively and significantly related to visual memory (coefficient [coeff] = -0.1601, standard error [SE] = 0.003), reaction time (coeff = -0.0346, SE = 0.0004), reasoning (coeff = 0.2304, SE = 0.0079), number memory (coeff = 0.1616, SE = 0.0092), and prospective memory (coeff = 0.3486, SE = 0.0092: all P < .001). In the schizophrenia sample, grip strength was strongly related to visual memory (coeff = -0.155, SE = 0.042, P < .001) and reaction time (coeff = -0.049, SE = 0.009, P < .001), while prospective memory approached statistical significance (coeff = 0.233, SE = 0.132, P = .078), and no statistically significant association was found with number memory and reasoning (P > .1). Grip strength is significantly associated with cognitive functioning in the general population and individuals with schizophrenia, particularly for working memory and processing speed. Future research should establish directionality, examine if grip strength also predicts functional and physical health outcomes in schizophrenia, and determine whether interventions which improve muscular strength impact on cognitive and real-world functioning.

Combining ultrasonography and noncontrast helical computerized tomography to evaluate Holmium laser lithotripsy

PubMed Central

Mi, Jia; Li, Jie; Zhang, Qinglu; Wang, Xing; Liu, Hongyu; Cao, Yanlu; Liu, Xiaoyan; Sun, Xiao; Shang, Mengmeng; Liu, Qing

2016-01-01

Abstract The purpose of the study was to establish a mathematical model for correlating the combination of ultrasonography and noncontrast helical computerized tomography (NCHCT) with the total energy of Holmium laser lithotripsy. In this study, from March 2013 to February 2014, 180 patients with single urinary calculus were examined using ultrasonography and NCHCT before Holmium laser lithotripsy. The calculus location and size, acoustic shadowing (AS) level, twinkling artifact intensity (TAI), and CT value were all documented. The total energy of lithotripsy (TEL) and the calculus composition were also recorded postoperatively. Data were analyzed using Spearman's rank correlation coefficient, with the SPSS 17.0 software package. Multiple linear regression was also used for further statistical analysis. A significant difference in the TEL was observed between renal calculi and ureteral calculi (r = –0.565, P < 0.001), and there was a strong correlation between the calculus size and the TEL (r = 0.675, P < 0.001). The difference in the TEL between the calculi with and without AS was highly significant (r = 0.325, P < 0.001). The CT value of the calculi was significantly correlated with the TEL (r = 0.386, P < 0.001). A correlation between the TAI and TEL was also observed (r = 0.391, P < 0.001). Multiple linear regression analysis revealed that the location, size, and TAI of the calculi were related to the TEL, and the location and size were statistically significant predictors (adjusted r2 = 0.498, P < 0.001). A mathematical model correlating the combination of ultrasonography and NCHCT with TEL was established; this model may provide a foundation to guide the use of energy in Holmium laser lithotripsy. The TEL can be estimated by the location, size, and TAI of the calculus. PMID:27930563

Outcomes associated with preoperative weight loss after laparoscopic Roux-en-Y gastric bypass

PubMed Central

Blackledge, Camille; Graham, Laura A.; Gullick, Allison A.; Richman, Joshua; Stahl, Richard; Grams, Jayleen

2016-01-01

Background Laparoscopic Roux-en-Y gastric bypass (LRYGB) is an effective treatment for achieving and maintaining weight loss and for improving obesity-related comorbidities. As part of the approval process for bariatric surgery, many insurance companies require patients to have documented recent participation in a supervised weight loss program. The goal of this study was to evaluate the relationship of preoperative weight changes with outcomes following LRYGB. Methods A retrospective review was conducted of adult patients undergoing LRYGB between 2008 and 2012 at a single institution. Patients were stratified into quartiles based on % excess weight gain (0–4.99 % and ≥5 % EWG) and % excess weight loss (0–4.99 % and ≥5 % EWL). Generalized linear models were used to examine differences in postoperative weight outcomes at 6, 12, and 24 months. Covariates included in the final adjusted models were determined using backwards stepwise selection. Results Of the 300 patients included in the study, there were no significant demographic differences among the quartiles. However, there was an increased time to operation for patients who gained or lost ≥5 % excess body weight (p < 0.001). Although there was no statistical significance in postoperative complications, there was a higher rate of complications in patients with ≥5 % EWG compared to those with ≥5 % EWL (12.5 vs. 4.8 %, respectively; p = 0.29). Unadjusted and adjusted generalized linear models showed no statistically significant association between preoperative % excess weight change and weight loss outcomes at 24 months. Conclusion Patients with the greatest % preoperative excess weight change had the longest intervals from initial visit to operation. No significant differences were seen in perioperative and postoperative outcomes. This study suggests preoperative weight loss requirements may delay the time to operation without improving postoperative outcomes or weight loss. PMID:26969666

Increased fibulin-1 plasma levels in polycystic ovary syndrome (PCOS) patients: possible contribution to the link between PCOS and cardiovascular risk.

PubMed

Scarinci, E; Tropea, A; Russo, G; Notaristefano, G; Messana, C; Alesiani, O; Fabozzi, S M; Lanzone, A; Apa, R

2018-04-21

To investigate a possible relation between fibulin-1 plasma levels and PCOS. ELISA quantitative determination of human fibulin-1. 50 women with PCOS and 40 control patients who attended the Unit of Human Reproductive Pathophysiology, Università Cattolica del Sacro Cuore, Rome, were enrolled. Ultrasonographic pelvic examinations, hormonal profile assays, oral tolerance test OGTT, lipid profile and ELISA quantitative determination of human fibulin-1 were performed. Fibulin-1 levels were found to be statistically significantly higher in PCOS patients than in matched control women. No statistically significant positive correlation was found between fibulin-1 and AUCi, HOMA-IR, total cholesterol, LDL, AMH, androstenedione and FAI, whereas a statistically significant positive correlation was found between fibulin-1 and 17OHP (p = 0.016) in the PCOS group. However, multivariable linear regression analysis showed that 17 OH P did not independently predict fibulin-1 levels (p = 0.089). Our data could contribute to explain the hypothesized increased cardiovascular risk and vascular damage in patients with PCOS. A better understanding of the cellular and molecular mechanisms involved in cardiometabolic disorders associated with PCOS is mandatory to identify new therapeutic strategies to eventually prevent the progression of cardiovascular diseases in these patients.

Relationship between self-reported upper limb disability and quantitative tests in hand-arm vibration syndrome.

PubMed

Poole, Kerry; Mason, Howard

2007-03-15

To establish the relationship between quantitative tests of hand function and upper limb disability, as measured by the Disability of the Arm, Shoulder and Hand (DASH) questionnaire, in hand-arm vibration syndrome (HAVS). A total of 228 individuals with HAVS were included in this study. Each had undergone a full HAVS assessment by an experienced physician, including quantitative tests of vibrotactile and thermal perception thresholds, maximal hand-grip strength (HG) and the Purdue pegboard (PP) test. Individuals were also asked to complete a DASH questionnaire. PP and HG of the quantitative tests gave the best and statistically significant individual correlations with the DASH disability score (r2 = 0.168 and 0.096). Stepwise linear regression analysis revealed that only PP and HG measurements were statistically significant predictors of upper limb disability (r2 = 0.178). Overall a combination of the PP and HG measurements, rather than each alone, gave slightly better discrimination, although not statistically significant, between normal and abnormal DASH scores with a sensitivity of 73.1% and specificity of 64.3%. Measurements of manual dexterity and hand-grip strength using PP and HG may be useful in helping to confirm lack of upper limb function and 'perceived' disability in HAVS.

Analysis of variance to assess statistical significance of Laplacian estimation accuracy improvement due to novel variable inter-ring distances concentric ring electrodes.

PubMed

Makeyev, Oleksandr; Joe, Cody; Lee, Colin; Besio, Walter G

2017-07-01

Concentric ring electrodes have shown promise in non-invasive electrophysiological measurement demonstrating their superiority to conventional disc electrodes, in particular, in accuracy of Laplacian estimation. Recently, we have proposed novel variable inter-ring distances concentric ring electrodes. Analytic and finite element method modeling results for linearly increasing distances electrode configurations suggested they may decrease the truncation error resulting in more accurate Laplacian estimates compared to currently used constant inter-ring distances configurations. This study assesses statistical significance of Laplacian estimation accuracy improvement due to novel variable inter-ring distances concentric ring electrodes. Full factorial design of analysis of variance was used with one categorical and two numerical factors: the inter-ring distances, the electrode diameter, and the number of concentric rings in the electrode. The response variables were the Relative Error and the Maximum Error of Laplacian estimation computed using a finite element method model for each of the combinations of levels of three factors. Effects of the main factors and their interactions on Relative Error and Maximum Error were assessed and the obtained results suggest that all three factors have statistically significant effects in the model confirming the potential of using inter-ring distances as a means of improving accuracy of Laplacian estimation.

Geographical distribution patterns of iodine in drinking-water and its associations with geological factors in Shandong Province, China.

PubMed

Gao, Jie; Zhang, Zhijie; Hu, Yi; Bian, Jianchao; Jiang, Wen; Wang, Xiaoming; Sun, Liqian; Jiang, Qingwu

2014-05-19

County-based spatial distribution characteristics and the related geological factors for iodine in drinking-water were studied in Shandong Province (China). Spatial autocorrelation analysis and spatial scan statistic were applied to analyze the spatial characteristics. Generalized linear models (GLMs) and geographically weighted regression (GWR) studies were conducted to explore the relationship between water iodine level and its related geological factors. The spatial distribution of iodine in drinking-water was significantly heterogeneous in Shandong Province (Moran's I = 0.52, Z = 7.4, p < 0.001). Two clusters for high iodine in drinking-water were identified in the south-western and north-western parts of Shandong Province by the purely spatial scan statistic approach. Both GLMs and GWR indicated a significantly global association between iodine in drinking-water and geological factors. Furthermore, GWR showed obviously spatial variability across the study region. Soil type and distance to Yellow River were statistically significant at most areas of Shandong Province, confirming the hypothesis that the Yellow River causes iodine deposits in Shandong Province. Our results suggested that the more effective regional monitoring plan and water improvement strategies should be strengthened targeting at the cluster areas based on the characteristics of geological factors and the spatial variability of local relationships between iodine in drinking-water and geological factors.

Introducing linear functions: an alternative statistical approach

NASA Astrophysics Data System (ADS)

Nolan, Caroline; Herbert, Sandra

2015-12-01

The introduction of linear functions is the turning point where many students decide if mathematics is useful or not. This means the role of parameters and variables in linear functions could be considered to be `threshold concepts'. There is recognition that linear functions can be taught in context through the exploration of linear modelling examples, but this has its limitations. Currently, statistical data is easily attainable, and graphics or computer algebra system (CAS) calculators are common in many classrooms. The use of this technology provides ease of access to different representations of linear functions as well as the ability to fit a least-squares line for real-life data. This means these calculators could support a possible alternative approach to the introduction of linear functions. This study compares the results of an end-of-topic test for two classes of Australian middle secondary students at a regional school to determine if such an alternative approach is feasible. In this study, test questions were grouped by concept and subjected to concept by concept analysis of the means of test results of the two classes. This analysis revealed that the students following the alternative approach demonstrated greater competence with non-standard questions.

Regression assumptions in clinical psychology research practice-a systematic review of common misconceptions.

PubMed

Ernst, Anja F; Albers, Casper J

2017-01-01

Misconceptions about the assumptions behind the standard linear regression model are widespread and dangerous. These lead to using linear regression when inappropriate, and to employing alternative procedures with less statistical power when unnecessary. Our systematic literature review investigated employment and reporting of assumption checks in twelve clinical psychology journals. Findings indicate that normality of the variables themselves, rather than of the errors, was wrongfully held for a necessary assumption in 4% of papers that use regression. Furthermore, 92% of all papers using linear regression were unclear about their assumption checks, violating APA-recommendations. This paper appeals for a heightened awareness for and increased transparency in the reporting of statistical assumption checking.

Regression assumptions in clinical psychology research practice—a systematic review of common misconceptions

PubMed Central

Ernst, Anja F.

2017-01-01

Misconceptions about the assumptions behind the standard linear regression model are widespread and dangerous. These lead to using linear regression when inappropriate, and to employing alternative procedures with less statistical power when unnecessary. Our systematic literature review investigated employment and reporting of assumption checks in twelve clinical psychology journals. Findings indicate that normality of the variables themselves, rather than of the errors, was wrongfully held for a necessary assumption in 4% of papers that use regression. Furthermore, 92% of all papers using linear regression were unclear about their assumption checks, violating APA-recommendations. This paper appeals for a heightened awareness for and increased transparency in the reporting of statistical assumption checking. PMID:28533971

Adjusted scaling of FDG positron emission tomography images for statistical evaluation in patients with suspected Alzheimer's disease.

PubMed

Buchert, Ralph; Wilke, Florian; Chakrabarti, Bhismadev; Martin, Brigitte; Brenner, Winfried; Mester, Janos; Clausen, Malte

2005-10-01

Statistical parametric mapping (SPM) gained increasing acceptance for the voxel-based statistical evaluation of brain positron emission tomography (PET) with the glucose analog 2-[18F]-fluoro-2-deoxy-d-glucose (FDG) in patients with suspected Alzheimer's disease (AD). To increase the sensitivity for detection of local changes, individual differences of total brain FDG uptake are usually compensated for by proportional scaling. However, in cases of extensive hypometabolic areas, proportional scaling overestimates scaled uptake. This may cause significant underestimation of the extent of hypometabolic areas by the statistical test. To detect this problem, the authors tested for hypermetabolism. In patients with no visual evidence of true focal hypermetabolism, significant clusters of hypermetabolism in the presence of extended hypometabolism were interpreted as false-positive findings, indicating relevant overestimation of scaled uptake. In this case, scaled uptake was reduced step by step until there were no more significant clusters of hypermetabolism. In 22 consecutive patients with suspected AD, proportional scaling resulted in relevant overestimation of scaled uptake in 9 patients. Scaled uptake had to be reduced by 11.1% +/- 5.3% in these cases to eliminate the artifacts. Adjusted scaling resulted in extension of existing and appearance of new clusters of hypometabolism. Total volume of the additional voxels with significant hypometabolism depended linearly on the extent of the additional scaling and was 202 +/- 118 mL on average. Adjusted scaling helps to identify characteristic metabolic patterns in patients with suspected AD. It is expected to increase specificity of FDGPET in this group of patients.

Effect of repeated simulated clinical use and sterilization on the cutting efficiency and flexibility of Hyflex CM nickel-titanium rotary files.

PubMed

Seago, Scott T; Bergeron, Brian E; Kirkpatrick, Timothy C; Roberts, Mark D; Roberts, Howard W; Himel, Van T; Sabey, Kent A

2015-05-01

Recent nickel-titanium manufacturing processes have resulted in an alloy that remains in a twinned martensitic phase at operating temperature. This alloy has been shown to have increased flexibility with added tolerance to cyclic and torsional fatigue. The aim of this study was to assess the effect of repeated simulated clinical use and sterilization on cutting efficiency and flexibility of Hyflex CM rotary files. Cutting efficiency was determined by measuring the load required to maintain a constant feed rate while instrumenting simulated canals. Flexibility was determined by using a 3-point bending test. Files were autoclaved after each use according to the manufacturer's recommendations. Files were tested through 10 simulated clinical uses. For cutting efficiency, mean data were analyzed by using multiple factor analysis of variance and the Dunnett post hoc test (P < .05). For flexibility, mean data were analyzed by using Levene's Test of Equality of Error and a general linear model (P < .05). No statistically significant decrease in cutting efficiency was noted in groups 2, 5, 6, and 7. A statistically significant decrease in cutting efficiency was noted in groups 3, 4, 8, 9, and 10. No statistically significant decrease in flexibility was noted in groups 2, 3, and 7. A statistically significant decrease in flexibility was noted in groups 4, 5, 6, 8, 9, 10, and 11. Repeated simulated clinical use and sterilization showed no effect on cutting efficiency through 1 use and no effect on flexibility through 2 uses. Published by Elsevier Inc.

Least median of squares and iteratively re-weighted least squares as robust linear regression methods for fluorimetric determination of α-lipoic acid in capsules in ideal and non-ideal cases of linearity.

PubMed

Korany, Mohamed A; Gazy, Azza A; Khamis, Essam F; Ragab, Marwa A A; Kamal, Miranda F

2018-06-01

This study outlines two robust regression approaches, namely least median of squares (LMS) and iteratively re-weighted least squares (IRLS) to investigate their application in instrument analysis of nutraceuticals (that is, fluorescence quenching of merbromin reagent upon lipoic acid addition). These robust regression methods were used to calculate calibration data from the fluorescence quenching reaction (∆F and F-ratio) under ideal or non-ideal linearity conditions. For each condition, data were treated using three regression fittings: Ordinary Least Squares (OLS), LMS and IRLS. Assessment of linearity, limits of detection (LOD) and quantitation (LOQ), accuracy and precision were carefully studied for each condition. LMS and IRLS regression line fittings showed significant improvement in correlation coefficients and all regression parameters for both methods and both conditions. In the ideal linearity condition, the intercept and slope changed insignificantly, but a dramatic change was observed for the non-ideal condition and linearity intercept. Under both linearity conditions, LOD and LOQ values after the robust regression line fitting of data were lower than those obtained before data treatment. The results obtained after statistical treatment indicated that the linearity ranges for drug determination could be expanded to lower limits of quantitation by enhancing the regression equation parameters after data treatment. Analysis results for lipoic acid in capsules, using both fluorimetric methods, treated by parametric OLS and after treatment by robust LMS and IRLS were compared for both linearity conditions. Copyright © 2018 John Wiley & Sons, Ltd.

Truncated Linear Statistics Associated with the Eigenvalues of Random Matrices II. Partial Sums over Proper Time Delays for Chaotic Quantum Dots

NASA Astrophysics Data System (ADS)

Grabsch, Aurélien; Majumdar, Satya N.; Texier, Christophe

2017-06-01

Invariant ensembles of random matrices are characterized by the distribution of their eigenvalues \\{λ _1,\\ldots ,λ _N\\}. We study the distribution of truncated linear statistics of the form \\tilde{L}=\\sum _{i=1}^p f(λ _i) with p

Central Tendency and Dispersion Measures of the Fundamental Frequencies of Four Vowels as Produced by Two Year-Old and Four-Year Children.

NASA Astrophysics Data System (ADS)

Monroe, Roberta Lynn

The intrinsic fundamental frequency effect among vowels is a vocalic phenomenon of adult speech in which high vowels have higher fundamental frequencies in relation to low vowels. Acoustic investigations of children's speech have shown that variability of the speech signal decreases as children's ages increase. Fundamental frequency measures have been suggested as an indirect metric for the development of laryngeal stability and coordination. Studies of the intrinsic fundamental frequency effect have been conducted among 8- and 9-year old children and in infants. The present study investigated this effect among 2- and 4-year old children. Eight 2-year old and eight 4-year old children produced four vowels, /ae/, /i/, /u/, and /a/, in CVC syllables. Three measures of fundamental frequency were taken. These were mean fundamental frequency, the intra-utterance standard deviation of the fundamental frequency, and the extent to which the cycle-to-cycle pattern of the fundamental frequency was predicted by a linear trend. An analysis of variance was performed to compare the two age groups, the four vowels, and the earlier and later repetitions of the CVC syllables. A significant difference between the two age groups was detected using the intra-utterance standard deviation of the fundamental frequency. Mean fundamental frequencies and linear trend analysis showed that voicing of the preceding consonant determined the statistical significance of the age-group comparisons. Statistically significant differences among the fundamental frequencies of the four vowels were not detected for either age group.

Quantitative structure-retention relationships of polycyclic aromatic hydrocarbons gas-chromatographic retention indices.

PubMed

Drosos, Juan Carlos; Viola-Rhenals, Maricela; Vivas-Reyes, Ricardo

2010-06-25

Polycyclic aromatic compounds (PAHs) are of concern in environmental chemistry and toxicology. In the present work, a QSRR study was performed for 209 previously reported PAHs using quantum mechanics and other sources descriptors estimated by different approaches. The B3LYP/6-31G* level of theory was used for geometrical optimization and quantum mechanics related variables. A good linear relationship between gas-chromatographic retention index and electronic or topologic descriptors was found by stepwise linear regression analysis. The molecular polarizability (alpha) and the second order molecular connectivity Kier and Hall index ((2)chi) showed evidence of significant correlation with retention index by means of important squared coefficient of determination, (R(2)), values (R(2)=0.950 and 0.962, respectively). A one variable QSRR model is presented for each descriptor and both models demonstrates a significant predictive capacity established using the leave-many-out LMO (excluding 25% of rows) cross validation method's q(2) cross-validation coefficients q(2)(CV-LMO25%), (obtained q(2)(CV-LMO25%) 0.947 and 0.960, respectively). Furthermore, the physicochemical interpretation of selected descriptors allowed detailed explanation of the source of the observed statistical correlation. The model analysis suggests that only one descriptor is sufficient to establish a consistent retention index-structure relationship. Moderate or non-significant improve was observed for quantitative results or statistical validation parameters when introducing more terms in predictive equation. The one parameter QSRR proposed model offers a consistent scheme to predict chromatographic properties of PAHs compounds. Copyright 2010 Elsevier B.V. All rights reserved.

High-throughput linear optical stretcher for mechanical characterization of blood cells.

PubMed

Roth, Kevin B; Neeves, Keith B; Squier, Jeff; Marr, David W M

2016-04-01

This study describes a linear optical stretcher as a high-throughput mechanical property cytometer. Custom, inexpensive, and scalable optics image a linear diode bar source into a microfluidic channel, where cells are hydrodynamically focused into the optical stretcher. Upon entering the stretching region, antipodal optical forces generated by the refraction of tightly focused laser light at the cell membrane deform each cell in flow. Each cell relaxes as it flows out of the trap and is compared to the stretched state to determine deformation. The deformation response of untreated red blood cells and neutrophils were compared to chemically treated cells. Statistically significant differences were observed between normal, diamide-treated, and glutaraldehyde-treated red blood cells, as well as between normal and cytochalasin D-treated neutrophils. Based on the behavior of the pure, untreated populations of red cells and neutrophils, a mixed population of these cells was tested and the discrete populations were identified by deformability. © 2015 International Society for Advancement of Cytometry. © 2015 International Society for Advancement of Cytometry.

Within crown variation in the relationship between foliage biomass and sapwood area in jack pine.

PubMed

Schneider, Robert; Berninger, Frank; Ung, Chhun-Huor; Mäkelä, Annikki; Swift, D Edwin; Zhang, S Y

2011-01-01

The relationship between sapwood area and foliage biomass is the basis for a lot of research on eco-phyisology. In this paper, foliage biomass change between two consecutive whorls is studied, using different variations in the pipe model theory. Linear and non-linear mixed-effect models relating foliage differences to sapwood area increments were tested to take into account whorl location, with the best fit statistics supporting the non-linear formulation. The estimated value of the exponent is 0.5130, which is significantly different from 1, the expected value given by the pipe model theory. When applied to crown stem sapwood taper, the model indicates that foliage biomass distribution influences the foliage biomass to sapwood area at crown base ratio. This result is interpreted as being the consequence of differences in the turnover rates of sapwood and foliage. More importantly, the model explains previously reported trends in jack pine sapwood area at crown base to tree foliage biomass ratio.

Quasi-closed phase forward-backward linear prediction analysis of speech for accurate formant detection and estimation.

PubMed

Gowda, Dhananjaya; Airaksinen, Manu; Alku, Paavo

2017-09-01

Recently, a quasi-closed phase (QCP) analysis of speech signals for accurate glottal inverse filtering was proposed. However, the QCP analysis which belongs to the family of temporally weighted linear prediction (WLP) methods uses the conventional forward type of sample prediction. This may not be the best choice especially in computing WLP models with a hard-limiting weighting function. A sample selective minimization of the prediction error in WLP reduces the effective number of samples available within a given window frame. To counter this problem, a modified quasi-closed phase forward-backward (QCP-FB) analysis is proposed, wherein each sample is predicted based on its past as well as future samples thereby utilizing the available number of samples more effectively. Formant detection and estimation experiments on synthetic vowels generated using a physical modeling approach as well as natural speech utterances show that the proposed QCP-FB method yields statistically significant improvements over the conventional linear prediction and QCP methods.

[Inferring landmark displacements from changes in cephalometric angles].

PubMed

Xu, T; Baumrind, S

2001-07-01

To investigate the appropriateness of using changes in angular measurements to reflect the actually profile changes. The sample consists of 48 growing malocclusion patients, contained 24 Class I and 24 Class II subjects, treated by an experienced orthodontist using Edgewise technique. Landmark and superimpositional data were extracted from the previously prepared numerical database. Three pairs of angular and linear measures were computed by the Craniofacial Software Package. Although the associations between all three angular measures and their corresponding linear measures are statistically significant at the 0.001 level, the disagreement between these three pairs of measures are 10.4%, 22.9% and 37.5% respectively in this sample. The direction of displacement of anterior facial landmarks during growth and treatment cannot reliably be inferred merely from changes in cephalometric Angles.

Using a generalized linear mixed model approach to explore the role of age, motor proficiency, and cognitive styles in children's reach estimation accuracy.

PubMed

Caçola, Priscila M; Pant, Mohan D

2014-10-01

The purpose was to use a multi-level statistical technique to analyze how children's age, motor proficiency, and cognitive styles interact to affect accuracy on reach estimation tasks via Motor Imagery and Visual Imagery. Results from the Generalized Linear Mixed Model analysis (GLMM) indicated that only the 7-year-old age group had significant random intercepts for both tasks. Motor proficiency predicted accuracy in reach tasks, and cognitive styles (object scale) predicted accuracy in the motor imagery task. GLMM analysis is suitable to explore age and other parameters of development. In this case, it allowed an assessment of motor proficiency interacting with age to shape how children represent, plan, and act on the environment.

Post-mortem prediction of primal and selected retail cut weights of New Zealand lamb from carcass and animal characteristics.

PubMed

Ngo, L; Ho, H; Hunter, P; Quinn, K; Thomson, A; Pearson, G

2016-02-01

Post-mortem measurements (cold weight, grade and external carcass linear dimensions) as well as live animal data (age, breed, sex) were used to predict ovine primal and retail cut weights for 792 lamb carcases. Significant levels of variance could be explained using these predictors. The predictive power of those measurements on primal and retail cut weights was studied by using the results from principal component analysis and the absolute value of the t-statistics of the linear regression model. High prediction accuracy for primal cut weight was achieved (adjusted R(2) up to 0.95), as well as moderate accuracy for key retail cut weight: tenderloins (adj-R(2)=0.60), loin (adj-R(2)=0.62), French rack (adj-R(2)=0.76) and rump (adj-R(2)=0.75). The carcass cold weight had the best predictive power, with the accuracy increasing by around 10% after including the next three most significant variables. Copyright © 2015 Elsevier Ltd. All rights reserved.

On correct evaluation techniques of brightness enhancement effect measurement data

NASA Astrophysics Data System (ADS)

Kukačka, Leoš; Dupuis, Pascal; Motomura, Hideki; Rozkovec, Jiří; Kolář, Milan; Zissis, Georges; Jinno, Masafumi

2017-11-01

This paper aims to establish confidence intervals of the quantification of brightness enhancement effects resulting from the use of pulsing bright light. It is found that the methods used so far may yield significant bias in the published results, overestimating or underestimating the enhancement effect. The authors propose to use a linear algebra method called the total least squares. Upon an example dataset, it is shown that this method does not yield biased results. The statistical significance of the results is also computed. It is concluded over an observation set that the currently used linear algebra methods present many patterns of noise sensitivity. Changing algorithm details leads to inconsistent results. It is thus recommended to use the method with the lowest noise sensitivity. Moreover, it is shown that this method also permits one to obtain an estimate of the confidence interval. This paper neither aims to publish results about a particular experiment nor to draw any particular conclusion about existence or nonexistence of the brightness enhancement effect.

Discrete dynamical system modelling for gene regulatory networks of 5-hydroxymethylfurfural tolerance for ethanologenic yeast.

PubMed

Song, M; Ouyang, Z; Liu, Z L

2009-05-01

Composed of linear difference equations, a discrete dynamical system (DDS) model was designed to reconstruct transcriptional regulations in gene regulatory networks (GRNs) for ethanologenic yeast Saccharomyces cerevisiae in response to 5-hydroxymethylfurfural (HMF), a bioethanol conversion inhibitor. The modelling aims at identification of a system of linear difference equations to represent temporal interactions among significantly expressed genes. Power stability is imposed on a system model under the normal condition in the absence of the inhibitor. Non-uniform sampling, typical in a time-course experimental design, is addressed by a log-time domain interpolation. A statistically significant DDS model of the yeast GRN derived from time-course gene expression measurements by exposure to HMF, revealed several verified transcriptional regulation events. These events implicate Yap1 and Pdr3, transcription factors consistently known for their regulatory roles by other studies or postulated by independent sequence motif analysis, suggesting their involvement in yeast tolerance and detoxification of the inhibitor.

Paroxysmal atrial fibrillation prediction method with shorter HRV sequences.

PubMed

Boon, K H; Khalil-Hani, M; Malarvili, M B; Sia, C W

2016-10-01

This paper proposes a method that predicts the onset of paroxysmal atrial fibrillation (PAF), using heart rate variability (HRV) segments that are shorter than those applied in existing methods, while maintaining good prediction accuracy. PAF is a common cardiac arrhythmia that increases the health risk of a patient, and the development of an accurate predictor of the onset of PAF is clinical important because it increases the possibility to stabilize (electrically) and prevent the onset of atrial arrhythmias with different pacing techniques. We investigate the effect of HRV features extracted from different lengths of HRV segments prior to PAF onset with the proposed PAF prediction method. The pre-processing stage of the predictor includes QRS detection, HRV quantification and ectopic beat correction. Time-domain, frequency-domain, non-linear and bispectrum features are then extracted from the quantified HRV. In the feature selection, the HRV feature set and classifier parameters are optimized simultaneously using an optimization procedure based on genetic algorithm (GA). Both full feature set and statistically significant feature subset are optimized by GA respectively. For the statistically significant feature subset, Mann-Whitney U test is used to filter non-statistical significance features that cannot pass the statistical test at 20% significant level. The final stage of our predictor is the classifier that is based on support vector machine (SVM). A 10-fold cross-validation is applied in performance evaluation, and the proposed method achieves 79.3% prediction accuracy using 15-minutes HRV segment. This accuracy is comparable to that achieved by existing methods that use 30-minutes HRV segments, most of which achieves accuracy of around 80%. More importantly, our method significantly outperforms those that applied segments shorter than 30 minutes. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Simulated linear test applied to quantitative proteomics.

PubMed

Pham, T V; Jimenez, C R

2016-09-01

Omics studies aim to find significant changes due to biological or functional perturbation. However, gene and protein expression profiling experiments contain inherent technical variation. In discovery proteomics studies where the number of samples is typically small, technical variation plays an important role because it contributes considerably to the observed variation. Previous methods place both technical and biological variations in tightly integrated mathematical models that are difficult to adapt for different technological platforms. Our aim is to derive a statistical framework that allows the inclusion of a wide range of technical variability. We introduce a new method called the simulated linear test, or the s-test, that is easy to implement and easy to adapt for different models of technical variation. It generates virtual data points from the observed values according to a pre-defined technical distribution and subsequently employs linear modeling for significance analysis. We demonstrate the flexibility of the proposed approach by deriving a new significance test for quantitative discovery proteomics for which missing values have been a major issue for traditional methods such as the t-test. We evaluate the result on two label-free (phospho) proteomics datasets based on ion-intensity quantitation. Available at http://www.oncoproteomics.nl/software/stest.html : t.pham@vumc.nl. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

(Draft) Community air pollution and mortality: Analysis of 1980 data from US metropolitan areas

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

Lipfert, F.W.

1992-11-01

1980 data from up to 149 metropolitan areas were used to define cross-sectional associations between community air pollution and ``excess`` human mortality. The regression model proposed by Ozkaynak and Thurston (1987), which accounted for age, race, education, poverty, and population density, was evaluated and several new models were developed. The new models also accounted for migration, drinking water hardness, and smoking, and included a more detailed description of race. Cause-of-death categories analyzed include all causes, all ``non-external`` causes, major cardiovascular diseases, and chronic obstructive pulmonary diseases (COPD). Both annual mortality rates and their logarithms were analyzed. Air quality data weremore » obtained from the EPA AIRS database (TSP, SO{sub 4}{sup =}, Mn, and ozone) and from the inhalable particulate network (PM{sub 15}, PM{sub 2.5} and SO{sub 4}{sup =}, for 63{sup 4} locations). The data on particulates were averaged across all monitoring stations available for each SMSA and the TSP data were restricted to the year 1980. The associations between mortality and air pollution were found to be dependent on the socioeconomic factors included in the models, the specific locations included in the data set, and the type of statistical model used. Statistically significant associations were found as follows: between TSP and mortality due to non-external causes with log-linear models, but not with a linear model betweenestimated 10-year average (1980--90) ozone levels and 1980 non-external and cardiovascular deaths; and between TSP and COPD mortality for both linear and log-linear models. When the sulfate contribution to TSP was subtracted, the relationship with COPD mortality was strengthened.« less

(Draft) Community air pollution and mortality: Analysis of 1980 data from US metropolitan areas

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

Lipfert, F.W.

1992-11-01

1980 data from up to 149 metropolitan areas were used to define cross-sectional associations between community air pollution and excess'' human mortality. The regression model proposed by Ozkaynak and Thurston (1987), which accounted for age, race, education, poverty, and population density, was evaluated and several new models were developed. The new models also accounted for migration, drinking water hardness, and smoking, and included a more detailed description of race. Cause-of-death categories analyzed include all causes, all non-external'' causes, major cardiovascular diseases, and chronic obstructive pulmonary diseases (COPD). Both annual mortality rates and their logarithms were analyzed. Air quality data weremore » obtained from the EPA AIRS database (TSP, SO[sub 4][sup =], Mn, and ozone) and from the inhalable particulate network (PM[sub 15], PM[sub 2.5] and SO[sub 4][sup =], for 63[sup 4] locations). The data on particulates were averaged across all monitoring stations available for each SMSA and the TSP data were restricted to the year 1980. The associations between mortality and air pollution were found to be dependent on the socioeconomic factors included in the models, the specific locations included in the data set, and the type of statistical model used. Statistically significant associations were found as follows: between TSP and mortality due to non-external causes with log-linear models, but not with a linear model betweenestimated 10-year average (1980--90) ozone levels and 1980 non-external and cardiovascular deaths; and between TSP and COPD mortality for both linear and log-linear models. When the sulfate contribution to TSP was subtracted, the relationship with COPD mortality was strengthened.« less

Robust Linear Models for Cis-eQTL Analysis.

PubMed

Rantalainen, Mattias; Lindgren, Cecilia M; Holmes, Christopher C

2015-01-01

Expression Quantitative Trait Loci (eQTL) analysis enables characterisation of functional genetic variation influencing expression levels of individual genes. In outbread populations, including humans, eQTLs are commonly analysed using the conventional linear model, adjusting for relevant covariates, assuming an allelic dosage model and a Gaussian error term. However, gene expression data generally have noise that induces heavy-tailed errors relative to the Gaussian distribution and often include atypical observations, or outliers. Such departures from modelling assumptions can lead to an increased rate of type II errors (false negatives), and to some extent also type I errors (false positives). Careful model checking can reduce the risk of type-I errors but often not type II errors, since it is generally too time-consuming to carefully check all models with a non-significant effect in large-scale and genome-wide studies. Here we propose the application of a robust linear model for eQTL analysis to reduce adverse effects of deviations from the assumption of Gaussian residuals. We present results from a simulation study as well as results from the analysis of real eQTL data sets. Our findings suggest that in many situations robust models have the potential to provide more reliable eQTL results compared to conventional linear models, particularly in respect to reducing type II errors due to non-Gaussian noise. Post-genomic data, such as that generated in genome-wide eQTL studies, are often noisy and frequently contain atypical observations. Robust statistical models have the potential to provide more reliable results and increased statistical power under non-Gaussian conditions. The results presented here suggest that robust models should be considered routinely alongside other commonly used methodologies for eQTL analysis.

Effect of correlation on covariate selection in linear and nonlinear mixed effect models.

PubMed

Bonate, Peter L

2017-01-01

The effect of correlation among covariates on covariate selection was examined with linear and nonlinear mixed effect models. Demographic covariates were extracted from the National Health and Nutrition Examination Survey III database. Concentration-time profiles were Monte Carlo simulated where only one covariate affected apparent oral clearance (CL/F). A series of univariate covariate population pharmacokinetic models was fit to the data and compared with the reduced model without covariate. The "best" covariate was identified using either the likelihood ratio test statistic or AIC. Weight and body surface area (calculated using Gehan and George equation, 1970) were highly correlated (r = 0.98). Body surface area was often selected as a better covariate than weight, sometimes as high as 1 in 5 times, when weight was the covariate used in the data generating mechanism. In a second simulation, parent drug concentration and three metabolites were simulated from a thorough QT study and used as covariates in a series of univariate linear mixed effects models of ddQTc interval prolongation. The covariate with the largest significant LRT statistic was deemed the "best" predictor. When the metabolite was formation-rate limited and only parent concentrations affected ddQTc intervals the metabolite was chosen as a better predictor as often as 1 in 5 times depending on the slope of the relationship between parent concentrations and ddQTc intervals. A correlated covariate can be chosen as being a better predictor than another covariate in a linear or nonlinear population analysis by sheer correlation These results explain why for the same drug different covariates may be identified in different analyses. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Are V1 Simple Cells Optimized for Visual Occlusions? A Comparative Study

PubMed Central

Bornschein, Jörg; Henniges, Marc; Lücke, Jörg

2013-01-01

Simple cells in primary visual cortex were famously found to respond to low-level image components such as edges. Sparse coding and independent component analysis (ICA) emerged as the standard computational models for simple cell coding because they linked their receptive fields to the statistics of visual stimuli. However, a salient feature of image statistics, occlusions of image components, is not considered by these models. Here we ask if occlusions have an effect on the predicted shapes of simple cell receptive fields. We use a comparative approach to answer this question and investigate two models for simple cells: a standard linear model and an occlusive model. For both models we simultaneously estimate optimal receptive fields, sparsity and stimulus noise. The two models are identical except for their component superposition assumption. We find the image encoding and receptive fields predicted by the models to differ significantly. While both models predict many Gabor-like fields, the occlusive model predicts a much sparser encoding and high percentages of ‘globular’ receptive fields. This relatively new center-surround type of simple cell response is observed since reverse correlation is used in experimental studies. While high percentages of ‘globular’ fields can be obtained using specific choices of sparsity and overcompleteness in linear sparse coding, no or only low proportions are reported in the vast majority of studies on linear models (including all ICA models). Likewise, for the here investigated linear model and optimal sparsity, only low proportions of ‘globular’ fields are observed. In comparison, the occlusive model robustly infers high proportions and can match the experimentally observed high proportions of ‘globular’ fields well. Our computational study, therefore, suggests that ‘globular’ fields may be evidence for an optimal encoding of visual occlusions in primary visual cortex. PMID:23754938

The effectiveness of repeat lumbar transforaminal epidural steroid injections.

PubMed

Murthy, Naveen S; Geske, Jennifer R; Shelerud, Randy A; Wald, John T; Diehn, Felix E; Thielen, Kent R; Kaufmann, Timothy J; Morris, Jonathan M; Lehman, Vance T; Amrami, Kimberly K; Carter, Rickey E; Maus, Timothy P

2014-10-01

The aim of this study was to determine 1) if repeat lumbar transforaminal epidural steroid injections (TFESIs) resulted in recovery of pain relief, which has waned since an index injection, and 2) if cumulative benefit could be achieved by repeat injections within 3 months of the index injection. Retrospective observational study with statistical modeling of the response to repeat TFESI. Academic radiology practice. Two thousand eighty-seven single-level TFESIs were performed for radicular pain on 933 subjects. Subjects received repeat TFESIs >2 weeks and <1 year from the index injection. Hierarchical linear modeling was performed to evaluate changes in continuous and categorical pain relief outcomes after repeat TFESI. Subgroup analyses were performed on patients with <3 months duration of pain (acute pain), patients receiving repeat injections within 3 months (clustered injections), and in patients with both acute pain and clustered injections. Repeat TFESIs achieved pain relief in both continuous and categorical outcomes. Relative to the index injection, there was a minimal but statistically significant decrease in pain relief in modeled continuous outcome measures with subsequent injections. Acute pain patients recovered all prior benefit with a statistically significant cumulative benefit. Patients receiving clustered injections achieved statistically significant cumulative benefit, of greater magnitude in acute pain patients. Repeat TFESI may be performed for recurrence of radicular pain with the expectation of recovery of most or all previously achieved benefit; acute pain patients will likely recover all prior benefit. Repeat TFESIs within 3 months of the index injection can provide cumulative benefit. Wiley Periodicals, Inc.

Caries prevention during orthodontic treatment: In-vivo assessment of high-fluoride varnish to prevent white spot lesions.

PubMed

Perrini, Federico; Lombardo, Luca; Arreghini, Angela; Medori, Silvia; Siciliani, Giuseppe

2016-02-01

Our objective was to evaluate the efficacy of a fluoridated varnish in preventing white spot lesions in patients with fixed appliances. A laser-induced fluorescence device was used to determine any correlations between the degree of demineralization and the length of the observation period, the arch sector, the frequency of varnish application, and the specific tooth site. A split-mouth study design was used for 24 orthodontic patients, allocated randomly to 2 subgroups with differing frequencies of Duraphat varnish (Colgate-Palmolive, New York, NY) application. Repeated measures of the degree of demineralization were taken on the vestibular surfaces of 12 teeth (6 varnished and 6 unvarnished controls). Measurements were taken at 4 sites using a DIAGNOdent Pen 2190 laser (KaVo, Biberach an der Riss, Germany) and then subjected to statistical analysis. Generalized linear model and coefficient model analysis showed differences in the degrees of demineralization between treated and untreated teeth, but this was not statistically significant in terms of time point, frequency of application, or specific tooth site. However, when we analyzed the position of the teeth, the varnished anterior teeth showed a statistically significant reduction in demineralization compared with their unvarnished counterparts. Periodic application of fluoride varnish can offer some protection against white spots, but not to a statistically significant degree if the patients have excellent oral hygiene. Copyright © 2016 American Association of Orthodontists. Published by Elsevier Inc. All rights reserved.

Temperature variation during apicectomy with Er:YAG laser.

PubMed

Bodrumlu, Emre; Keskiner, Ilker; Sumer, Mahmut; Sumer, A Pinar; Telcıoglu, N Tuba

2012-08-01

The purpose of this in vitro study was to evaluate the generated temperature of the Er:YAG laser, with three different pulse durations for apicectomy, compared with tungsten bur and surgical saw. Apicectomy is an endodontic surgery performed to remove the root apex and curette adjacent periapical tissue because of lesions of the apical area that are not healing properly. Sixty single-rooted extracted human teeth were resected by three cutting methods: tungsten bur, surgical saw, and Er:YAG laser irradiation with three different pulse durations; pulse duration 50 μs, pulse duration 100 μs, and pulse duration 300 μs. Teflon-insulated, type K thermocouples were used to measure temperature changes during the apicectomy process. Data were analyzed using the general linear models procedure of the SPSS statistical software program. Although there was no statistically significant difference for the mean values of temperature changes at 1 mm away to the cutting site of teeth, there was statistically significant difference among groups for the mean values of temperature changes at 3 mm away to the cutting site of teeth. Additionally, there was statistically significant difference among groups for the total time required for apicectomy. The laser irradiation with pulse duration 50 μs appears to have the lowest temperature rise and the shortest time required for apicectomy of the three pulse durations. However, Er:YAG laser for apicectomy in all pulse durations could be used safely for resection in endodontics in the presence of sufficient water.

Extending local canonical correlation analysis to handle general linear contrasts for FMRI data.

PubMed

Jin, Mingwu; Nandy, Rajesh; Curran, Tim; Cordes, Dietmar

2012-01-01

Local canonical correlation analysis (CCA) is a multivariate method that has been proposed to more accurately determine activation patterns in fMRI data. In its conventional formulation, CCA has several drawbacks that limit its usefulness in fMRI. A major drawback is that, unlike the general linear model (GLM), a test of general linear contrasts of the temporal regressors has not been incorporated into the CCA formalism. To overcome this drawback, a novel directional test statistic was derived using the equivalence of multivariate multiple regression (MVMR) and CCA. This extension will allow CCA to be used for inference of general linear contrasts in more complicated fMRI designs without reparameterization of the design matrix and without reestimating the CCA solutions for each particular contrast of interest. With the proper constraints on the spatial coefficients of CCA, this test statistic can yield a more powerful test on the inference of evoked brain regional activations from noisy fMRI data than the conventional t-test in the GLM. The quantitative results from simulated and pseudoreal data and activation maps from fMRI data were used to demonstrate the advantage of this novel test statistic.

Extending Local Canonical Correlation Analysis to Handle General Linear Contrasts for fMRI Data

PubMed Central

Jin, Mingwu; Nandy, Rajesh; Curran, Tim; Cordes, Dietmar

2012-01-01

Local canonical correlation analysis (CCA) is a multivariate method that has been proposed to more accurately determine activation patterns in fMRI data. In its conventional formulation, CCA has several drawbacks that limit its usefulness in fMRI. A major drawback is that, unlike the general linear model (GLM), a test of general linear contrasts of the temporal regressors has not been incorporated into the CCA formalism. To overcome this drawback, a novel directional test statistic was derived using the equivalence of multivariate multiple regression (MVMR) and CCA. This extension will allow CCA to be used for inference of general linear contrasts in more complicated fMRI designs without reparameterization of the design matrix and without reestimating the CCA solutions for each particular contrast of interest. With the proper constraints on the spatial coefficients of CCA, this test statistic can yield a more powerful test on the inference of evoked brain regional activations from noisy fMRI data than the conventional t-test in the GLM. The quantitative results from simulated and pseudoreal data and activation maps from fMRI data were used to demonstrate the advantage of this novel test statistic. PMID:22461786

Statistical Tutorial | Center for Cancer Research

Cancer.gov

Recent advances in cancer biology have resulted in the need for increased statistical analysis of research data.  ST is designed as a follow up to Statistical Analysis of Research Data (SARD) held in April 2018.  The tutorial will apply the general principles of statistical analysis of research data including descriptive statistics, z- and t-tests of means and mean differences, simple and multiple linear regression, ANOVA tests, and Chi-Squared distribution.

General anesthesia in orthognathic surgeries: does it affect horizontal jaw relations?

PubMed

Yaghmaei, Masoud; Ejlali, Masoud; Nikzad, Sekieneh; Sayyedi, Ashraf; Shafaeifard, Shahrouz; Pourdanesh, Fereydoun

2013-10-01

The aim of this study was to evaluate the influence of general anesthesia on centric jaw relation (CR) records of orthognathic surgical patients in different postural positions. Fifty patients undergoing orthognathic surgery at Taleghani Hospital (Tehran, Iran) in 2008 were prospectively studied. CR records were obtained in conscious patients in 2 different positions (upright and supine) 1 day before surgery and in the supine position under general anesthesia. The impressions were made and the corresponding casts were mounted on a semiadjustable articulator. Differences were measured to the nearest 0.10 mm using a caliper. Paired t test and a general linear regression model were used for statistical analysis. Fifty patients (27 women and 23 men; mean age, 22.5 ± 3.5 yr) were enrolled. Angle Class I (group I), Class II (group II), and Class III (group III) malocclusions were detected in 16% (n = 8), 54% (n = 27), and 30% (n = 15) of patients, respectively. Although mean changes were smaller than 2 mm, statistically significant differences were found by paired t test in all Angle classification groups. No significant differences were found between the supine and conscious and the supine and unconscious patient positions in groups I and III (P > .05). However, in group II, this difference was statistically significant (P = .001). Regarding the impact of anesthesia on CR records of patients with different Angle classes, this study showed a significant effect, particularly in group II. Assessment of the outcome of interest (difference between the supine and conscious and the upright and conscious positions) versus position after adjustment for Angle class using a general linear regression model showed that the difference was significant only for Angle class (β = +0.29; t = 3.05; P = .003). General anesthesia may not adversely affect the mandibular condylar position in orthognathic patients in a supine position compared with a supine and conscious position. However, among all study groups, group II showed more significant changes in CR records under general anesthesia. Oral and maxillofacial surgeons should be well aware of such changes in these particular positions and avoid possible mismanagement and potential complications. Copyright © 2013 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.

Helical tomotherapy to LINAC plan conversion utilizing RayStation Fallback planning.

PubMed

Zhang, Xin; Penagaricano, Jose; Narayanasamy, Ganesh; Corry, Peter; Liu, TianXiao; Sanjay, Maraboyina; Paudel, Nava; Morrill, Steven

2017-01-01

RaySearch RayStation Fallback (FB) planning module can generate an equivalent backup radiotherapy treatment plan facilitating treatment on other linear accelerators. FB plans were generated from the RayStation FB module by simulating the original plan target and organ at risk (OAR) dose distribution and delivered in various backup linear accelerators. In this study, helical tomotherapy (HT) backup plans used in Varian TrueBeam linear accelerator were generated with the RayStation FB module. About 30 patients, 10 with lung cancer, 10 with head and neck (HN) cancer, and 10 with prostate cancer, who were treated with HT, were included in this study. Intensity-modulated radiotherapy Fallback plans (FB-IMRT) were generated for all patients, and three-dimensional conformal radiotherapy Fallback plans (FB-3D) were only generated for lung cancer patients. Dosimetric comparison study evaluated FB plans based on dose coverage to 95% of the PTV volume (R 95 ), PTV mean dose (D mean ), Paddick's conformity index (CI), and dose homogeneity index (HI). The evaluation results showed that all IMRT plans were statistically comparable between HT and FB-IMRT plans except that PTV HI was worse in prostate, and PTV R 95 and HI were worse in HN multitarget plans for FB-IMRT plans. For 3D lung cancer plans, only the PTV R 95 was statistically comparable between HT and FB-3D plans, PTV D mean was higher, and CI and HI were worse compared to HT plans. The FB plans using a TrueBeam linear accelerator generally offer better OAR sparing compared to HT plans for all the patients. In this study, all cases of FB-IMRT plans and 9/10 cases of FB-3D plans were clinically acceptable without further modification and optimization once the FB plans were generated. However, the statistical differences between HT and FB-IMRT/3D plans might not be of any clinically significant. One FB-3D plan failed to simulate the original plan without further optimization. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Impulse oscillometry at preschool age is a strong predictor of lung function by flow-volume spirometry in adolescence.

PubMed

Lauhkonen, Eero; Riikonen, Riikka; Törmänen, Sari; Koponen, Petri; Nuolivirta, Kirsi; Helminen, Merja; Toikka, Jyri; Korppi, Matti

2018-05-01

The transition from early childhood wheezing to persistent asthma is linked to lung function impairment over time. Little is known how the methods used to study lung function at different ages correlate longitudinally. Sixty-four children with a history of hospitalization for bronchiolitis before 6 months of age were prospectively studied with impulse oscillometry (IOS) at the mean age of 6.3 years and these preschool IOS results were compared with flow-volume spirometry (FVS) measurements at mean age of 11.4 years. The baseline respiratory system resistance at 5 Hz (Rrs5) showed a modest statistically significant correlation with all baseline FVS parameters except FVC. The post-bronchodilator (post-BD) Rrs5 showed a modest statistically significant correlation with post-BD FEV 1 and FEV 1 /FVC. The bronchodilator-induced decrease in Rrs5 showed a modest statistically significant correlation with the percent increase in FEV 1 . Baseline and post-BD respiratory reactance at 5 Hz (Xrs5) showed a modest statistically significant correlation with baseline and post-BD FVS parameters except post-BD FEV 1 /FVC, respectively, and post-BD Xrs5 showed a strong correlation with post-BD FVC (ρ = 0.61) and post-BD FEV 1 (ρ = 0.59). In adjusted linear regression, preschool Xrs5 remained as a statistically significant independent predictor of FVS parameters in adolescence; the one-unit decrease in the Z-score of preschool post-BD Xrs5 predicted 9.6% lower post-BD FEV 1 , 9.3% lower post-BD FVC, and 9.7% lower post-BD MEF 50 when expressed as %-predicted parameters. Persistent post-BD small airway impairment in children with a history of bronchiolitis detected with IOS at preschool age predicted FVS results measured in early adolescence. © 2018 Wiley Periodicals, Inc.

Groundwater-level prediction using multiple linear regression and artificial neural network techniques: a comparative assessment

NASA Astrophysics Data System (ADS)

Sahoo, Sasmita; Jha, Madan K.

2013-12-01

The potential of multiple linear regression (MLR) and artificial neural network (ANN) techniques in predicting transient water levels over a groundwater basin were compared. MLR and ANN modeling was carried out at 17 sites in Japan, considering all significant inputs: rainfall, ambient temperature, river stage, 11 seasonal dummy variables, and influential lags of rainfall, ambient temperature, river stage and groundwater level. Seventeen site-specific ANN models were developed, using multi-layer feed-forward neural networks trained with Levenberg-Marquardt backpropagation algorithms. The performance of the models was evaluated using statistical and graphical indicators. Comparison of the goodness-of-fit statistics of the MLR models with those of the ANN models indicated that there is better agreement between the ANN-predicted groundwater levels and the observed groundwater levels at all the sites, compared to the MLR. This finding was supported by the graphical indicators and the residual analysis. Thus, it is concluded that the ANN technique is superior to the MLR technique in predicting spatio-temporal distribution of groundwater levels in a basin. However, considering the practical advantages of the MLR technique, it is recommended as an alternative and cost-effective groundwater modeling tool.

Steganalysis of recorded speech

NASA Astrophysics Data System (ADS)

Johnson, Micah K.; Lyu, Siwei; Farid, Hany

2005-03-01

Digital audio provides a suitable cover for high-throughput steganography. At 16 bits per sample and sampled at a rate of 44,100 Hz, digital audio has the bit-rate to support large messages. In addition, audio is often transient and unpredictable, facilitating the hiding of messages. Using an approach similar to our universal image steganalysis, we show that hidden messages alter the underlying statistics of audio signals. Our statistical model begins by building a linear basis that captures certain statistical properties of audio signals. A low-dimensional statistical feature vector is extracted from this basis representation and used by a non-linear support vector machine for classification. We show the efficacy of this approach on LSB embedding and Hide4PGP. While no explicit assumptions about the content of the audio are made, our technique has been developed and tested on high-quality recorded speech.

Composite Linear Models | Division of Cancer Prevention

Cancer.gov

By Stuart G. Baker The composite linear models software is a matrix approach to compute maximum likelihood estimates and asymptotic standard errors for models for incomplete multinomial data. It implements the method described in Baker SG. Composite linear models for incomplete multinomial data. Statistics in Medicine 1994;13:609-622. The software includes a library of thirty

Can we detect a nonlinear response to temperature in European plant phenology?

NASA Astrophysics Data System (ADS)

Jochner, Susanne; Sparks, Tim H.; Laube, Julia; Menzel, Annette

2016-10-01

Over a large temperature range, the statistical association between spring phenology and temperature is often regarded and treated as a linear function. There are suggestions that a sigmoidal relationship with definite upper and lower limits to leaf unfolding and flowering onset dates might be more realistic. We utilised European plant phenological records provided by the European phenology database PEP725 and gridded monthly mean temperature data for 1951-2012 calculated from the ENSEMBLES data set E-OBS (version 7.0). We analysed 568,456 observations of ten spring flowering or leafing phenophases derived from 3657 stations in 22 European countries in order to detect possible nonlinear responses to temperature. Linear response rates averaged for all stations ranged between -7.7 (flowering of hazel) and -2.7 days °C-1 (leaf unfolding of beech and oak). A lower sensitivity at the cooler end of the temperature range was detected for most phenophases. However, a similar lower sensitivity at the warmer end was not that evident. For only ˜14 % of the station time series (where a comparison between linear and nonlinear model was possible), nonlinear models described the relationship significantly better than linear models. Although in most cases simple linear models might be still sufficient to predict future changes, this linear relationship between phenology and temperature might not be appropriate when incorporating phenological data of very cold (and possibly very warm) environments. For these cases, extrapolations on the basis of linear models would introduce uncertainty in expected ecosystem changes.

Toward the improvement in fetal monitoring during labor with the inclusion of maternal heart rate analysis.

PubMed

Gonçalves, Hernâni; Pinto, Paula; Silva, Manuela; Ayres-de-Campos, Diogo; Bernardes, João

2016-04-01

Fetal heart rate (FHR) monitoring is used routinely in labor, but conventional methods have a limited capacity to detect fetal hypoxia/acidosis. An exploratory study was performed on the simultaneous assessment of maternal heart rate (MHR) and FHR variability, to evaluate their evolution during labor and their capacity to detect newborn acidemia. MHR and FHR were simultaneously recorded in 51 singleton term pregnancies during the last two hours of labor and compared with newborn umbilical artery blood (UAB) pH. Linear/nonlinear indices were computed separately for MHR and FHR. Interaction between MHR and FHR was quantified through the same indices on FHR-MHR and through their correlation and cross-entropy. Univariate and bivariate statistical analysis included nonparametric confidence intervals and statistical tests, receiver operating characteristic curves and linear discriminant analysis. Progression of labor was associated with a significant increase in most MHR and FHR linear indices, whereas entropy indices decreased. FHR alone and in combination with MHR as FHR-MHR evidenced the highest auROC values for prediction of fetal acidemia, with 0.76 and 0.88 for the UAB pH thresholds 7.20 and 7.15, respectively. The inclusion of MHR on bivariate analysis achieved sensitivity and specificity values of nearly 100 and 89.1%, respectively. These results suggest that simultaneous analysis of MHR and FHR may improve the identification of fetal acidemia compared with FHR alone, namely during the last hour of labor.

Flow Equation Approach to the Statistics of Nonlinear Dynamical Systems

NASA Astrophysics Data System (ADS)

Marston, J. B.; Hastings, M. B.

2005-03-01

The probability distribution function of non-linear dynamical systems is governed by a linear framework that resembles quantum many-body theory, in which stochastic forcing and/or averaging over initial conditions play the role of non-zero . Besides the well-known Fokker-Planck approach, there is a related Hopf functional methodootnotetextUriel Frisch, Turbulence: The Legacy of A. N. Kolmogorov (Cambridge University Press, 1995) chapter 9.5.; in both formalisms, zero modes of linear operators describe the stationary non-equilibrium statistics. To access the statistics, we investigate the method of continuous unitary transformationsootnotetextS. D. Glazek and K. G. Wilson, Phys. Rev. D 48, 5863 (1993); Phys. Rev. D 49, 4214 (1994). (also known as the flow equation approachootnotetextF. Wegner, Ann. Phys. 3, 77 (1994).), suitably generalized to the diagonalization of non-Hermitian matrices. Comparison to the more traditional cumulant expansion method is illustrated with low-dimensional attractors. The treatment of high-dimensional dynamical systems is also discussed.

Solar granulation and statistical crystallography: A modeling approach using size-shape relations

NASA Technical Reports Server (NTRS)

Noever, D. A.

1994-01-01

The irregular polygonal pattern of solar granulation is analyzed for size-shape relations using statistical crystallography. In contrast to previous work which has assumed perfectly hexagonal patterns for granulation, more realistic accounting of cell (granule) shapes reveals a broader basis for quantitative analysis. Several features emerge as noteworthy: (1) a linear correlation between number of cell-sides and neighboring shapes (called Aboav-Weaire's law); (2) a linear correlation between both average cell area and perimeter and the number of cell-sides (called Lewis's law and a perimeter law, respectively) and (3) a linear correlation between cell area and squared perimeter (called convolution index). This statistical picture of granulation is consistent with a finding of no correlation in cell shapes beyond nearest neighbors. A comparative calculation between existing model predictions taken from luminosity data and the present analysis shows substantial agreements for cell-size distributions. A model for understanding grain lifetimes is proposed which links convective times to cell shape using crystallographic results.

On Fluctuations of Eigenvalues of Random Band Matrices

NASA Astrophysics Data System (ADS)

Shcherbina, M.

2015-10-01

We consider the fluctuations of linear eigenvalue statistics of random band matrices whose entries have the form with i.i.d. possessing the th moment, where the function u has a finite support , so that M has only nonzero diagonals. The parameter b (called the bandwidth) is assumed to grow with n in a way such that . Without any additional assumptions on the growth of b we prove CLT for linear eigenvalue statistics for a rather wide class of test functions. Thus we improve and generalize the results of the previous papers (Jana et al., arXiv:1412.2445; Li et al. Random Matrices 2:04, 2013), where CLT was proven under the assumption . Moreover, we develop a method which allows to prove automatically the CLT for linear eigenvalue statistics of the smooth test functions for almost all classical models of random matrix theory: deformed Wigner and sample covariance matrices, sparse matrices, diluted random matrices, matrices with heavy tales etc.

Cell therapy with bone marrow mononuclear cells in elastase-induced pulmonary emphysema.

PubMed

Longhini-Dos-Santos, Nathalia; Barbosa-de-Oliveira, Valter Abraão; Kozma, Rodrigo Heras; Faria, Carolina Arruda de; Stessuk, Talita; Frei, Fernando; Ribeiro-Paes, João Tadeu

2013-04-01

Emphysema is characterized by destruction of alveolar walls with loss of gas exchange surface and consequent progressive dyspnea. This study aimed to evaluate the efficiency of cell therapy with bone marrow mononuclear cells (BMMC) in an animal model of elastase-induced pulmonary emphysema. Emphysema was induced in C57Bl/J6 female mice by intranasal instillation of elastase. After 21 days, the mice received bone marrow mononuclear cells from EGFP male mice with C57Bl/J6 background. The groups were assessed by comparison and statistically significant differences (p < 0.05) were observed among the groups treated with BMMC and evaluated after 7, 14 and 21 days. Analysis of the mean linear intercept (Lm) values for the different groups allowed to observe that the group treated with BMMC and evaluated after 21 days showed the most significant result. The group that received no treatment showed a statistically significant difference when compared to other groups, except the group treated and evaluated after 21 days, evidencing the efficacy of cell therapy with BMMC in pulmonary emphysema.

Imaging of the midpalatal suture in a porcine model: flat-panel volume computed tomography compared with multislice computed tomography.

PubMed

Hahn, Wolfram; Fricke-Zech, Susanne; Fialka-Fricke, Julia; Dullin, Christian; Zapf, Antonia; Gruber, Rudolf; Sennhenn-kirchner, Sabine; Kubein-Meesenburg, Dietmar; Sadat-Khonsari, Reza

2009-09-01

An investigation was conducted to compare the image quality of prototype flat-panel volume computed tomography (fpVCT) and multislice computed tomography (MSCT) of suture structures. Bone samples were taken from the midpalatal suture of 5 young (16 weeks) and 5 old (200 weeks) Sus scrofa domestica and fixed in formalin solution. An fpVCT prototype and an MSCT were used to obtain images of the specimens. The facial reformations were assessed by 4 observers using a 1 (excellent) to 5 (poor) rating scale for the weighted criteria visualization of the suture structure. A linear mixed model was used for statistical analysis. Results with P < .05 were considered to be statistically significant. The visualization of the suture of young specimens was significantly better than that of older animals (P < .001). The visualization of the suture with fpVCT was significantly better than that with MSCT (P < .001). Compared with MSCT, fpVCT produces superior results in the visualization of the midpalatal suture in a Sus scrofa domestica model.

Ultrasonographic evaluation of the renal dimensions in captive tigers.

PubMed

Huaijantug, Somkiat; Manatpreprem, Komsan; Manatpreprem, Sukhumarn; Yatmark, Paranee

2017-01-10

Ultrasonographic measurements of kidney size are useful in the practical diagnosis of kidney diseases in animals. In tigers, there is a lack of information regarding the ultrasonography methods used to measure the kidney size of the tiger. Thirty-three healthy captive tigers (Panthera tigris) were placed in lateral recumbency for ultrasonography. The measurements obtained from the ultrasonography were computed, and the results showed that there was a statistically significant difference between genders in terms of body weight and renal length. The length of the right kidney was significantly different from that of the left kidney (10.23 ± 0.76 cm in males versus 9.94 ± 0.80 cm in females; P<0.05). Interestingly, this study demonstrated that kidney length was statistically significantly associated with the body weight, and it also had a positive linear relationship with the body weight. Therefore, ultrasonographic renal dimensions could prove to be beneficial and modality for use in the evaluation of kidneys in unconscious tigers. However, kidney size evaluation must be performed using not only ultrasound but other clinical forms of technology and parameters.

Computational Analysis for Rocket-Based Combined-Cycle Systems During Rocket-Only Operation

NASA Technical Reports Server (NTRS)

Steffen, C. J., Jr.; Smith, T. D.; Yungster, S.; Keller, D. J.

2000-01-01

A series of Reynolds-averaged Navier-Stokes calculations were employed to study the performance of rocket-based combined-cycle systems operating in an all-rocket mode. This parametric series of calculations were executed within a statistical framework, commonly known as design of experiments. The parametric design space included four geometric and two flowfield variables set at three levels each, for a total of 729 possible combinations. A D-optimal design strategy was selected. It required that only 36 separate computational fluid dynamics (CFD) solutions be performed to develop a full response surface model, which quantified the linear, bilinear, and curvilinear effects of the six experimental variables. The axisymmetric, Reynolds-averaged Navier-Stokes simulations were executed with the NPARC v3.0 code. The response used in the statistical analysis was created from Isp efficiency data integrated from the 36 CFD simulations. The influence of turbulence modeling was analyzed by using both one- and two-equation models. Careful attention was also given to quantify the influence of mesh dependence, iterative convergence, and artificial viscosity upon the resulting statistical model. Thirteen statistically significant effects were observed to have an influence on rocket-based combined-cycle nozzle performance. It was apparent that the free-expansion process, directly downstream of the rocket nozzle, can influence the Isp efficiency. Numerical schlieren images and particle traces have been used to further understand the physical phenomena behind several of the statistically significant results.

Are conventional statistical techniques exhaustive for defining metal background concentrations in harbour sediments? A case study: The Coastal Area of Bari (Southeast Italy).

PubMed

Mali, Matilda; Dell'Anna, Maria Michela; Mastrorilli, Piero; Damiani, Leonardo; Ungaro, Nicola; Belviso, Claudia; Fiore, Saverio

2015-11-01

Sediment contamination by metals poses significant risks to coastal ecosystems and is considered to be problematic for dredging operations. The determination of the background values of metal and metalloid distribution based on site-specific variability is fundamental in assessing pollution levels in harbour sediments. The novelty of the present work consists of addressing the scope and limitation of analysing port sediments through the use of conventional statistical techniques (such as: linear regression analysis, construction of cumulative frequency curves and the iterative 2σ technique), that are commonly employed for assessing Regional Geochemical Background (RGB) values in coastal sediments. This study ascertained that although the tout court use of such techniques in determining the RGB values in harbour sediments seems appropriate (the chemical-physical parameters of port sediments fit well with statistical equations), it should nevertheless be avoided because it may be misleading and can mask key aspects of the study area that can only be revealed by further investigations, such as mineralogical and multivariate statistical analyses. Copyright © 2015 Elsevier Ltd. All rights reserved.

Variable Selection with Prior Information for Generalized Linear Models via the Prior LASSO Method.

PubMed

Jiang, Yuan; He, Yunxiao; Zhang, Heping

LASSO is a popular statistical tool often used in conjunction with generalized linear models that can simultaneously select variables and estimate parameters. When there are many variables of interest, as in current biological and biomedical studies, the power of LASSO can be limited. Fortunately, so much biological and biomedical data have been collected and they may contain useful information about the importance of certain variables. This paper proposes an extension of LASSO, namely, prior LASSO (pLASSO), to incorporate that prior information into penalized generalized linear models. The goal is achieved by adding in the LASSO criterion function an additional measure of the discrepancy between the prior information and the model. For linear regression, the whole solution path of the pLASSO estimator can be found with a procedure similar to the Least Angle Regression (LARS). Asymptotic theories and simulation results show that pLASSO provides significant improvement over LASSO when the prior information is relatively accurate. When the prior information is less reliable, pLASSO shows great robustness to the misspecification. We illustrate the application of pLASSO using a real data set from a genome-wide association study.

Plant selection for ethnobotanical uses on the Amalfi Coast (Southern Italy).

PubMed

Savo, V; Joy, R; Caneva, G; McClatchey, W C

2015-07-15

Many ethnobotanical studies have investigated selection criteria for medicinal and non-medicinal plants. In this paper we test several statistical methods using different ethnobotanical datasets in order to 1) define to which extent the nature of the datasets can affect the interpretation of results; 2) determine if the selection for different plant uses is based on phylogeny, or other selection criteria. We considered three different ethnobotanical datasets: two datasets of medicinal plants and a dataset of non-medicinal plants (handicraft production, domestic and agro-pastoral practices) and two floras of the Amalfi Coast. We performed residual analysis from linear regression, the binomial test and the Bayesian approach for calculating under-used and over-used plant families within ethnobotanical datasets. Percentages of agreement were calculated to compare the results of the analyses. We also analyzed the relationship between plant selection and phylogeny, chorology, life form and habitat using the chi-square test. Pearson's residuals for each of the significant chi-square analyses were examined for investigating alternative hypotheses of plant selection criteria. The three statistical analysis methods differed within the same dataset, and between different datasets and floras, but with some similarities. In the two medicinal datasets, only Lamiaceae was identified in both floras as an over-used family by all three statistical methods. All statistical methods in one flora agreed that Malvaceae was over-used and Poaceae under-used, but this was not found to be consistent with results of the second flora in which one statistical result was non-significant. All other families had some discrepancy in significance across methods, or floras. Significant over- or under-use was observed in only a minority of cases. The chi-square analyses were significant for phylogeny, life form and habitat. Pearson's residuals indicated a non-random selection of woody species for non-medicinal uses and an under-use of plants of temperate forests for medicinal uses. Our study showed that selection criteria for plant uses (including medicinal) are not always based on phylogeny. The comparison of different statistical methods (regression, binomial and Bayesian) under different conditions led to the conclusion that the most conservative results are obtained using regression analysis.

Extreme value statistics analysis of fracture strengths of a sintered silicon nitride failing from pores

NASA Technical Reports Server (NTRS)

Chao, Luen-Yuan; Shetty, Dinesh K.

1992-01-01

Statistical analysis and correlation between pore-size distribution and fracture strength distribution using the theory of extreme-value statistics is presented for a sintered silicon nitride. The pore-size distribution on a polished surface of this material was characterized, using an automatic optical image analyzer. The distribution measured on the two-dimensional plane surface was transformed to a population (volume) distribution, using the Schwartz-Saltykov diameter method. The population pore-size distribution and the distribution of the pore size at the fracture origin were correllated by extreme-value statistics. Fracture strength distribution was then predicted from the extreme-value pore-size distribution, usin a linear elastic fracture mechanics model of annular crack around pore and the fracture toughness of the ceramic. The predicted strength distribution was in good agreement with strength measurements in bending. In particular, the extreme-value statistics analysis explained the nonlinear trend in the linearized Weibull plot of measured strengths without postulating a lower-bound strength.

Detecting temporal change in freshwater fisheries surveys: statistical power and the important linkages between management questions and monitoring objectives

USGS Publications Warehouse

Wagner, Tyler; Irwin, Brian J.; James R. Bence,; Daniel B. Hayes,

2016-01-01

Monitoring to detect temporal trends in biological and habitat indices is a critical component of fisheries management. Thus, it is important that management objectives are linked to monitoring objectives. This linkage requires a definition of what constitutes a management-relevant “temporal trend.” It is also important to develop expectations for the amount of time required to detect a trend (i.e., statistical power) and for choosing an appropriate statistical model for analysis. We provide an overview of temporal trends commonly encountered in fisheries management, review published studies that evaluated statistical power of long-term trend detection, and illustrate dynamic linear models in a Bayesian context, as an additional analytical approach focused on shorter term change. We show that monitoring programs generally have low statistical power for detecting linear temporal trends and argue that often management should be focused on different definitions of trends, some of which can be better addressed by alternative analytical approaches.

An investigation into the causes of stratospheric ozone loss in the southern Australasian region

NASA Astrophysics Data System (ADS)

Lehmann, P.; Karoly, D. J.; Newmann, P. A.; Clarkson, T. S.; Matthews, W. A.

1992-07-01

Measurements of total ozone at Macquarie Island (55 deg S, 159 deg E) reveal statistically significant reductions of approximately twelve percent during July to September when comparing the mean levels for 1987-90 with those in the seventies. In order to investigate the possibility that these ozone changes may not be a result of dynamic variability of the stratosphere, a simple linear model of ozone was created from statistical analysis of tropopause height and isentropic transient eddy heat flux, which were assumed representative of the dominant dynamic influences. Comparison of measured and modeled ozone indicates that the recent downward trend in ozone at Macquarie Island is not related to stratospheric dynamic variability and therefore suggests another mechanism, possibly changes in photochemical destruction of ozone.

Linear Dimensional Stability of Irreversible Hydrocolloid Materials Over Time.

PubMed

Garrofé, Analía B; Ferrari, Beatriz A; Picca, Mariana; Kaplan, Andrea E

2015-12-01

The aim of this study was to evaluate the linear dimensional stability of different irreversible hydrocolloid materials over time. A metal mold was designed with custom trays made of thermoplastic sheets (Sabilex, sheets 0.125 mm thick). Perforations were made in order to improve retention of the material. Five impressions were taken with each of the following: Kromopan 100 (LASCOD) [AlKr], which has dimensional stability of 100 hours, and Phase Plus (ZHERMACK) [AlPh], which has dimensional stability of 48 hours. Standardized digital photographs were taken at different time intervals (0, 15, 30, 45, 60, 120 minutes; 12, 24 and 96 hours), using an "ad-hoc" device. The images were analyzed with software (UTHSCSA Image Tool) by measuring the distance between intersection of the lines previously made at the top of the mold. The results were analyzed by ANOVA for repeated measures. Initial and final values were (mean and standard deviation): AlKr: 16.44 (0.22) and 16.34 (0.11), AlPh: 16.40 (0.06) and 16.18 (0.06). Statistical evaluation showed significant effect of material and time factors. Under the conditions in this study, time significantly affects the linear dimensional stability of irreversible hydrocolloid materials. Sociedad Argentina de Investigación Odontológica.

An evaluation of three statistical estimation methods for assessing health policy effects on prescription drug claims.

PubMed

Mittal, Manish; Harrison, Donald L; Thompson, David M; Miller, Michael J; Farmer, Kevin C; Ng, Yu-Tze

2016-01-01

While the choice of analytical approach affects study results and their interpretation, there is no consensus to guide the choice of statistical approaches to evaluate public health policy change. This study compared and contrasted three statistical estimation procedures in the assessment of a U.S. Food and Drug Administration (FDA) suicidality warning, communicated in January 2008 and implemented in May 2009, on antiepileptic drug (AED) prescription claims. Longitudinal designs were utilized to evaluate Oklahoma (U.S. State) Medicaid claim data from January 2006 through December 2009. The study included 9289 continuously eligible individuals with prevalent diagnoses of epilepsy and/or psychiatric disorder. Segmented regression models using three estimation procedures [i.e., generalized linear models (GLM), generalized estimation equations (GEE), and generalized linear mixed models (GLMM)] were used to estimate trends of AED prescription claims across three time periods: before (January 2006-January 2008); during (February 2008-May 2009); and after (June 2009-December 2009) the FDA warning. All three statistical procedures estimated an increasing trend (P < 0.0001) in AED prescription claims before the FDA warning period. No procedures detected a significant change in trend during (GLM: -30.0%, 99% CI: -60.0% to 10.0%; GEE: -20.0%, 99% CI: -70.0% to 30.0%; GLMM: -23.5%, 99% CI: -58.8% to 1.2%) and after (GLM: 50.0%, 99% CI: -70.0% to 160.0%; GEE: 80.0%, 99% CI: -20.0% to 200.0%; GLMM: 47.1%, 99% CI: -41.2% to 135.3%) the FDA warning when compared to pre-warning period. Although the three procedures provided consistent inferences, the GEE and GLMM approaches accounted appropriately for correlation. Further, marginal models estimated using GEE produced more robust and valid population-level estimations. Copyright © 2016 Elsevier Inc. All rights reserved.

An Analytic Solution to the Computation of Power and Sample Size for Genetic Association Studies under a Pleiotropic Mode of Inheritance.

PubMed

Gordon, Derek; Londono, Douglas; Patel, Payal; Kim, Wonkuk; Finch, Stephen J; Heiman, Gary A

2016-01-01

Our motivation here is to calculate the power of 3 statistical tests used when there are genetic traits that operate under a pleiotropic mode of inheritance and when qualitative phenotypes are defined by use of thresholds for the multiple quantitative phenotypes. Specifically, we formulate a multivariate function that provides the probability that an individual has a vector of specific quantitative trait values conditional on having a risk locus genotype, and we apply thresholds to define qualitative phenotypes (affected, unaffected) and compute penetrances and conditional genotype frequencies based on the multivariate function. We extend the analytic power and minimum-sample-size-necessary (MSSN) formulas for 2 categorical data-based tests (genotype, linear trend test [LTT]) of genetic association to the pleiotropic model. We further compare the MSSN of the genotype test and the LTT with that of a multivariate ANOVA (Pillai). We approximate the MSSN for statistics by linear models using a factorial design and ANOVA. With ANOVA decomposition, we determine which factors most significantly change the power/MSSN for all statistics. Finally, we determine which test statistics have the smallest MSSN. In this work, MSSN calculations are for 2 traits (bivariate distributions) only (for illustrative purposes). We note that the calculations may be extended to address any number of traits. Our key findings are that the genotype test usually has lower MSSN requirements than the LTT. More inclusive thresholds (top/bottom 25% vs. top/bottom 10%) have higher sample size requirements. The Pillai test has a much larger MSSN than both the genotype test and the LTT, as a result of sample selection. With these formulas, researchers can specify how many subjects they must collect to localize genes for pleiotropic phenotypes. © 2017 S. Karger AG, Basel.

Statistics and Machine Learning based Outlier Detection Techniques for Exoplanets

NASA Astrophysics Data System (ADS)

Goel, Amit; Montgomery, Michele

2015-08-01

Architectures of planetary systems are observable snapshots in time that can indicate formation and dynamic evolution of planets. The observable key parameters that we consider are planetary mass and orbital period. If planet masses are significantly less than their host star masses, then Keplerian Motion is defined as P^2 = a^3 where P is the orbital period in units of years and a is the orbital period in units of Astronomical Units (AU). Keplerian motion works on small scales such as the size of the Solar System but not on large scales such as the size of the Milky Way Galaxy. In this work, for confirmed exoplanets of known stellar mass, planetary mass, orbital period, and stellar age, we analyze Keplerian motion of systems based on stellar age to seek if Keplerian motion has an age dependency and to identify outliers. For detecting outliers, we apply several techniques based on statistical and machine learning methods such as probabilistic, linear, and proximity based models. In probabilistic and statistical models of outliers, the parameters of a closed form probability distributions are learned in order to detect the outliers. Linear models use regression analysis based techniques for detecting outliers. Proximity based models use distance based algorithms such as k-nearest neighbour, clustering algorithms such as k-means, or density based algorithms such as kernel density estimation. In this work, we will use unsupervised learning algorithms with only the proximity based models. In addition, we explore the relative strengths and weaknesses of the various techniques by validating the outliers. The validation criteria for the outliers is if the ratio of planetary mass to stellar mass is less than 0.001. In this work, we present our statistical analysis of the outliers thus detected.

SU-F-R-20: Image Texture Features Correlate with Time to Local Failure in Lung SBRT Patients

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

Andrews, M; Abazeed, M; Woody, N

Purpose: To explore possible correlation between CT image-based texture and histogram features and time-to-local-failure in early stage non-small cell lung cancer (NSCLC) patients treated with stereotactic body radiotherapy (SBRT).Methods and Materials: From an IRB-approved lung SBRT registry for patients treated between 2009–2013 we selected 48 (20 male, 28 female) patients with local failure. Median patient age was 72.3±10.3 years. Mean time to local failure was 15 ± 7.1 months. Physician-contoured gross tumor volumes (GTV) on the planning CT images were processed and 3D gray-level co-occurrence matrix (GLCM) based texture and histogram features were calculated in Matlab. Data were exported tomore » R and a multiple linear regression model was used to examine the relationship between texture features and time-to-local-failure. Results: Multiple linear regression revealed that entropy (p=0.0233, multiple R2=0.60) from GLCM-based texture analysis and the standard deviation (p=0.0194, multiple R2=0.60) from the histogram-based features were statistically significantly correlated with the time-to-local-failure. Conclusion: Image-based texture analysis can be used to predict certain aspects of treatment outcomes of NSCLC patients treated with SBRT. We found entropy and standard deviation calculated for the GTV on the CT images displayed a statistically significant correlation with and time-to-local-failure in lung SBRT patients.« less

Is anorectal endosonography valuable in dyschesia?

PubMed Central

Van Outryve, S M; Van Outryve, M J; De Winter, B Y; Pelckmans, P A

2002-01-01

Aims: Dyschesia can be provoked by inappropriate defecation movements. The aim of this prospective study was to demonstrate dysfunction of the anal sphincter and/or the musculus (m.) puborectalis in patients with dyschesia using anorectal endosonography. Methods: Twenty consecutive patients with a medical history of dyschesia and a control group of 20 healthy subjects underwent linear anorectal endosonography (Toshiba models IUV 5060 and PVL-625 RT). In both groups, the dimensions of the anal sphincter and the m. puborectalis were measured at rest, and during voluntary squeezing and straining. Statistical analysis was performed within and between the two groups. Results: The anal sphincter became paradoxically shorter and/or thicker during straining (versus the resting state) in 85% of patients but in only 35% of control subjects. Changes in sphincter length were statistically significantly different (p<0.01, χ2 test) in patients compared with control subjects. The m. puborectalis became paradoxically shorter and/or thicker during straining in 80% of patients but in only 30% of controls. Both the changes in length and thickness of the m. puborectalis were significantly different (p<0.01, χ2 test) in patients versus control subjects. Conclusions: Linear anorectal endosonography demonstrated incomplete or even absent relaxation of the anal sphincter and the m. puborectalis during a defecation movement in the majority of our patients with dyschesia. This study highlights the value of this elegant ultrasonographic technique in the diagnosis of “pelvic floor dyssynergia” or “anismus”. PMID:12377809

Virtual school teacher's science efficacy beliefs: The effects of community of practice on science-teaching efficacy beliefs

NASA Astrophysics Data System (ADS)

Uzoff, Phuong Pham

The purpose of this study was to examine how much K-12 science teachers working in a virtual school experience a community of practice and how that experience affects personal science-teaching efficacy and science-teaching outcome expectancy. The study was rooted in theoretical frameworks from Lave and Wenger's (1991) community of practice and Bandura's (1977) self-efficacy beliefs. The researcher used three surveys to examine schoolteachers' experiences of a community of practice and science-teaching efficacy beliefs. The instrument combined Mangieri's (2008) virtual teacher demographic survey, Riggs and Enochs (1990) Science-teaching efficacy Beliefs Instrument-A (STEBI-A), and Cadiz, Sawyer, and Griffith's (2009) Experienced Community of Practice (eCoP) instrument. The results showed a significant linear statistical relationship between the science teachers' experiences of community of practice and personal science-teaching efficacy. In addition, the study found that there was also a significant linear statistical relationship between teachers' community of practice experiences and science-teaching outcome expectancy. The results from this study were in line with numerous studies that have found teachers who are involved in a community of practice report higher science-teaching efficacy beliefs (Akerson, Cullen, & Hanson, 2009; Fazio, 2009; Lakshmanan, Heath, Perlmutter, & Elder, 2011; Liu, Lee, & Lin, 2010; Sinclair, Naizer, & Ledbetter, 2010). The researcher concluded that school leaders, policymakers, and researchers should increase professional learning opportunities that are grounded in social constructivist theoretical frameworks in order to increase teachers' science efficacy.

Effects of metal- and fiber-reinforced composite root canal posts on flexural properties.

PubMed

Kim, Su-Hyeon; Oh, Tack-Oon; Kim, Ju-Young; Park, Chun-Woong; Baek, Seung-Ho; Park, Eun-Seok

2016-01-01

The aim of this study was to observe the effects of different test conditions on the flexural properties of root canal post. Metal- and fiber-reinforced composite root canal posts of various diameters were measured to determine flexural properties using a threepoint bending test at different conditions. In this study, the span length/post diameter ratio of root canal posts varied from 3.0 to 10.0. Multiple regression models for maximum load as a dependent variable were statistically significant. The models for flexural properties as dependent variables were statistically significant, but linear regression models could not be fitted to data sets. At a low span length/post diameter ratio, the flexural properties were distorted by occurrence of shear stress in short samples. It was impossible to obtain high span length/post diameter ratio with root canal posts. The addition of parameters or coefficients is necessary to appropriately represent the flexural properties of root canal posts.

Assessing the Effects of Financial Literacy on Patient Engagement.

PubMed

Meyer, Melanie A; Hudak, Ronald P

2016-07-01

We investigated the relationship between financial literacy and patient engagement while considering the possible interaction effects due to patient financial responsibility and patient-physician shared decision making, and the impact of personal attributes. Participants consisted of an Internet-based sample of American adults (N = 160). Hierarchical multiple linear regression analysis was conducted to examine the relationship of the study variables on patient engagement. We found that patient financial responsibility (β = -.19, p < .05) and patient-physician shared decision-making (β = .17, p < .05) predicted patient engagement. However, there was no statistically significant relationship between patient financial literacy and patient engagement; moreover, the moderation effects of patient financial responsibility and shared decision making with financial literacy also were not statistically significant. Increasing patient financial responsibility and patient-physician shared decision making can impact patient engagement. Understanding the predictors of patient engagement and the factors that influence financial behaviors may allow for the development of interventions to enable patients to make better healthcare decisions, and ultimately, improve health outcomes.

Round-off errors in cutting plane algorithms based on the revised simplex procedure

NASA Technical Reports Server (NTRS)

Moore, J. E.

1973-01-01

This report statistically analyzes computational round-off errors associated with the cutting plane approach to solving linear integer programming problems. Cutting plane methods require that the inverse of a sequence of matrices be computed. The problem basically reduces to one of minimizing round-off errors in the sequence of inverses. Two procedures for minimizing this problem are presented, and their influence on error accumulation is statistically analyzed. One procedure employs a very small tolerance factor to round computed values to zero. The other procedure is a numerical analysis technique for reinverting or improving the approximate inverse of a matrix. The results indicated that round-off accumulation can be effectively minimized by employing a tolerance factor which reflects the number of significant digits carried for each calculation and by applying the reinversion procedure once to each computed inverse. If 18 significant digits plus an exponent are carried for each variable during computations, then a tolerance value of 0.1 x 10 to the minus 12th power is reasonable.

A multi-criteria evaluation system for marine litter pollution based on statistical analyses of OSPAR beach litter monitoring time series.

PubMed

Schulz, Marcus; Neumann, Daniel; Fleet, David M; Matthies, Michael

2013-12-01

During the last decades, marine pollution with anthropogenic litter has become a worldwide major environmental concern. Standardized monitoring of litter since 2001 on 78 beaches selected within the framework of the Convention for the Protection of the Marine Environment of the North-East Atlantic (OSPAR) has been used to identify temporal trends of marine litter. Based on statistical analyses of this dataset a two-part multi-criteria evaluation system for beach litter pollution of the North-East Atlantic and the North Sea is proposed. Canonical correlation analyses, linear regression analyses, and non-parametric analyses of variance were used to identify different temporal trends. A classification of beaches was derived from cluster analyses and served to define different states of beach quality according to abundances of 17 input variables. The evaluation system is easily applicable and relies on the above-mentioned classification and on significant temporal trends implied by significant rank correlations. Copyright © 2013 Elsevier Ltd. All rights reserved.

Non-linear learning in online tutorial to enhance students’ knowledge on normal distribution application topic

NASA Astrophysics Data System (ADS)

Kartono; Suryadi, D.; Herman, T.

2018-01-01

This study aimed to analyze the enhancement of non-linear learning (NLL) in the online tutorial (OT) content to students’ knowledge of normal distribution application (KONDA). KONDA is a competence expected to be achieved after students studied the topic of normal distribution application in the course named Education Statistics. The analysis was performed by quasi-experiment study design. The subject of the study was divided into an experimental class that was given OT content in NLL model and a control class which was given OT content in conventional learning (CL) model. Data used in this study were the results of online objective tests to measure students’ statistical prior knowledge (SPK) and students’ pre- and post-test of KONDA. The statistical analysis test of a gain score of KONDA of students who had low and moderate SPK’s scores showed students’ KONDA who learn OT content with NLL model was better than students’ KONDA who learn OT content with CL model. Meanwhile, for students who had high SPK’s scores, the gain score of students who learn OT content with NLL model had relatively similar with the gain score of students who learn OT content with CL model. Based on those findings it could be concluded that the NLL model applied to OT content could enhance KONDA of students in low and moderate SPK’s levels. Extra and more challenging didactical situation was needed for students in high SPK’s level to achieve the significant gain score.

Linear and Nonlinear Analysis of Brain Dynamics in Children with Cerebral Palsy

ERIC Educational Resources Information Center

Sajedi, Firoozeh; Ahmadlou, Mehran; Vameghi, Roshanak; Gharib, Masoud; Hemmati, Sahel

2013-01-01

This study was carried out to determine linear and nonlinear changes of brain dynamics and their relationships with the motor dysfunctions in CP children. For this purpose power of EEG frequency bands (as a linear analysis) and EEG fractality (as a nonlinear analysis) were computed in eyes-closed resting state and statistically compared between 26…

Correlation and simple linear regression.

PubMed

Eberly, Lynn E

2007-01-01

This chapter highlights important steps in using correlation and simple linear regression to address scientific questions about the association of two continuous variables with each other. These steps include estimation and inference, assessing model fit, the connection between regression and ANOVA, and study design. Examples in microbiology are used throughout. This chapter provides a framework that is helpful in understanding more complex statistical techniques, such as multiple linear regression, linear mixed effects models, logistic regression, and proportional hazards regression.

Maxillary sinus augmentation by crestal access: a retrospective study on cavity size and outcome correlation.

PubMed

Spinato, Sergio; Bernardello, Fabio; Galindo-Moreno, Pablo; Zaffe, Davide

2015-12-01

Cone-beam computed tomography (CBCT) and radiographic outcomes of crestal sinus elevation, performed using mineralized human bone allograft, were analyzed to correlate results with maxillary sinus size. A total of 60 sinus augmentations in 60 patients, with initial bone ≤5 mm, were performed. Digital radiographs were taken at surgical implant placement time up to post-prosthetic loading follow-up (12-72 months), when CBCT evaluation was carried out. Marginal bone loss (MBL) was radiographically analyzed at 6 months and follow-up time post-loading. Sinus size (BPD), implant distance from palatal (PID) and buccal wall (BID), and absence of bone coverage of implant (intra-sinus bone loss--IBL) were evaluated and statistically evaluated by ANOVA and linear regression analyses. MBL increased as a function of time. MBL at final follow-up was statistically associated with MBL at 6 months. A statistically significant correlation of IBL with wall distance and of IBL/mm with time was identified with greater values in wide sinuses (WS ≥ 13.27 mm) than in narrow sinuses (NS < 13.27 mm). This study is the first quantitative and statistically significant confirmation that crestal technique with residual ridge height <5 mm is more appropriate and predictable, in terms of intra-sinus bone coverage, in narrow than in WS. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Morphological texture assessment of oral bone as a screening tool for osteoporosis

NASA Astrophysics Data System (ADS)

Analoui, Mostafa; Eggertsson, Hafsteinn; Eckert, George

2001-07-01

Three classes of texture analysis approaches have been employed to assess the textural characteristic of oral bone. A set of linear structuring elements was used to compute granulometric features of trabecular bone. Multifractal analysis was also used to compute the fractal dimension of the corresponding tissues. In addition, some statistical features and histomorphometric parameters were computed. To assess the proposed approach we acquired digital intraoral radiographs of 47 subjects (14 males and 33 females). All radiographs were captured at 12 bits/pixel. Images were converted to binary form through a sliding locally adaptive thresholding approach. Each subject was scanned by DEXA for bone dosimetry. Subject were classified into one of the following three categories according World Health Organization (WHO) standard (1) healthy, (2) with osteopenia and (3) osteoporosis. In this study fractal dimension showed very low correlation with bone mineral density (BMD) measurements, which did not reach a level of statistical significance (p<0.5). However, entropy of pattern spectrum (EPS), along with statistical features and histomorphometric parameters, has shown correlation coefficients ranging from low to high, with statistical significance for both males and females. The results of this study indicate the utility of this approach for bone texture analysis. It is conjectured that designing a 2-D structuring element, specially tuned to trabecular bone texture, will increase the efficacy of the proposed method.

Linear regression models and k-means clustering for statistical analysis of fNIRS data.

PubMed

Bonomini, Viola; Zucchelli, Lucia; Re, Rebecca; Ieva, Francesca; Spinelli, Lorenzo; Contini, Davide; Paganoni, Anna; Torricelli, Alessandro

2015-02-01

We propose a new algorithm, based on a linear regression model, to statistically estimate the hemodynamic activations in fNIRS data sets. The main concern guiding the algorithm development was the minimization of assumptions and approximations made on the data set for the application of statistical tests. Further, we propose a K-means method to cluster fNIRS data (i.e. channels) as activated or not activated. The methods were validated both on simulated and in vivo fNIRS data. A time domain (TD) fNIRS technique was preferred because of its high performances in discriminating cortical activation and superficial physiological changes. However, the proposed method is also applicable to continuous wave or frequency domain fNIRS data sets.

Linear regression models and k-means clustering for statistical analysis of fNIRS data

PubMed Central

Bonomini, Viola; Zucchelli, Lucia; Re, Rebecca; Ieva, Francesca; Spinelli, Lorenzo; Contini, Davide; Paganoni, Anna; Torricelli, Alessandro

2015-01-01

We propose a new algorithm, based on a linear regression model, to statistically estimate the hemodynamic activations in fNIRS data sets. The main concern guiding the algorithm development was the minimization of assumptions and approximations made on the data set for the application of statistical tests. Further, we propose a K-means method to cluster fNIRS data (i.e. channels) as activated or not activated. The methods were validated both on simulated and in vivo fNIRS data. A time domain (TD) fNIRS technique was preferred because of its high performances in discriminating cortical activation and superficial physiological changes. However, the proposed method is also applicable to continuous wave or frequency domain fNIRS data sets. PMID:25780751

Consumption of fruit, but not vegetables, may reduce risk of gastric cancer: results from a meta-analysis of cohort studies.

PubMed

Wang, Qingbing; Chen, Yi; Wang, Xiaolin; Gong, Gaoquan; Li, Guoping; Li, Changyu

2014-05-01

Quantification of the association between consumption of fruit and vegetables and risk of gastric cancer (GC) is controversial. We aimed to conduct a meta-analysis of cohort studies to evaluate the associations. Eligible studies published up to 31st August 2013 were retrieved via both computer searches of PubMed and EMBASE and a manual review of references. Random-effects models were used to calculate summary relative risk (SRR). Heterogeneity among studies was assessed using Cochran's Q and I(2) statistics. A total of 17 articles (24 studies), were included in this meta-analysis. There were >2.4 million individuals (6632 GC events) with a median follow-up of 10years. Based on the high versus low analysis, consumption of fruit, but not vegetables, may reduce risk of gastric cancer (fruit: SRR=0.90, 95% confidence interval (CI): 0.83-0.98, Pheterogeneity=0.450; vegetable: SRR=0.96, 95% CI: 0.88-1.06, Pheterogeneity=0.150). Meta regression analysis suggested that outcome (incidence versus mortality) and study quality (high versus low) contributed significantly to heterogeneity. The same results were also shown in the linear dose-response analysis (per 100-g/day) (fruit: SRR=0.95, 95% CI: 0.91-0.99; vegetable: SRR=0.96, 95% CI: 0.91-1.01). Significant inverse associations emerged in non-linear models for consumption of fruit (Pnon-linearity=0.04), but not for consumption of vegetables (Pnon-linearity=0.551). Findings from this meta-analysis indicate a significant protective effect for the consumption of fruit on GC risk, but not for the consumption of vegetables. Copyright © 2014 Elsevier Ltd. All rights reserved.

Accuracy of a Computer-Aided Surgical Simulation (CASS) Protocol for Orthognathic Surgery: A Prospective Multicenter Study

PubMed Central

Hsu, Sam Sheng-Pin; Gateno, Jaime; Bell, R. Bryan; Hirsch, David L.; Markiewicz, Michael R.; Teichgraeber, John F.; Zhou, Xiaobo; Xia, James J.

2012-01-01

Purpose The purpose of this prospective multicenter study was to assess the accuracy of a computer-aided surgical simulation (CASS) protocol for orthognathic surgery. Materials and Methods The accuracy of the CASS protocol was assessed by comparing planned and postoperative outcomes of 65 consecutive patients enrolled from 3 centers. Computer-generated surgical splints were used for all patients. For the genioplasty, one center utilized computer-generated chin templates to reposition the chin segment only for patients with asymmetry. Standard intraoperative measurements were utilized without the chin templates for the remaining patients. The primary outcome measurements were linear and angular differences for the maxilla, mandible and chin when the planned and postoperative models were registered at the cranium. The secondary outcome measurements were: maxillary dental midline difference between the planned and postoperative positions; and linear and angular differences of the chin segment between the groups with and without the use of the template. The latter was measured when the planned and postoperative models were registered at mandibular body. Statistical analyses were performed, and the accuracy was reported using root mean square deviation (RMSD) and Bland and Altman's method for assessing measurement agreement. Results In the primary outcome measurements, there was no statistically significant difference among the 3 centers for the maxilla and mandible. The largest RMSD was 1.0mm and 1.5° for the maxilla, and 1.1mm and 1.8° for the mandible. For the chin, there was a statistically significant difference between the groups with and without the use of the chin template. The chin template group showed excellent accuracy with largest positional RMSD of 1.0mm and the largest orientational RSMD of 2.2°. However, larger variances were observed in the group not using the chin template. This was significant in anteroposterior and superoinferior directions, as in pitch and yaw orientations. In the secondary outcome measurements, the RMSD of maxillary dental midline positions was 0.9mm. When registered at the body of the mandible, the linear and angular differences of the chin segment between the groups with and without the use of the chin template were consistent with the results found in the primary outcome measurements. Conclusion Using the CASS protocol, the computerized plan can be accurately and consistently transferred to the patient to position the maxilla and mandible at the time of surgery. The computer-generated chin template provides more accuracy in repositioning the chin segment than the intraoperative measurements. PMID:22695016

Order Selection for General Expression of Nonlinear Autoregressive Model Based on Multivariate Stepwise Regression

NASA Astrophysics Data System (ADS)

Shi, Jinfei; Zhu, Songqing; Chen, Ruwen

2017-12-01

An order selection method based on multiple stepwise regressions is proposed for General Expression of Nonlinear Autoregressive model which converts the model order problem into the variable selection of multiple linear regression equation. The partial autocorrelation function is adopted to define the linear term in GNAR model. The result is set as the initial model, and then the nonlinear terms are introduced gradually. Statistics are chosen to study the improvements of both the new introduced and originally existed variables for the model characteristics, which are adopted to determine the model variables to retain or eliminate. So the optimal model is obtained through data fitting effect measurement or significance test. The simulation and classic time-series data experiment results show that the method proposed is simple, reliable and can be applied to practical engineering.

Use of simulation tools to illustrate the effect of data management practices for low and negative plate counts on the estimated parameters of microbial reduction models.

PubMed

Garcés-Vega, Francisco; Marks, Bradley P

2014-08-01

In the last 20 years, the use of microbial reduction models has expanded significantly, including inactivation (linear and nonlinear), survival, and transfer models. However, a major constraint for model development is the impossibility to directly quantify the number of viable microorganisms below the limit of detection (LOD) for a given study. Different approaches have been used to manage this challenge, including ignoring negative plate counts, using statistical estimations, or applying data transformations. Our objective was to illustrate and quantify the effect of negative plate count data management approaches on parameter estimation for microbial reduction models. Because it is impossible to obtain accurate plate counts below the LOD, we performed simulated experiments to generate synthetic data for both log-linear and Weibull-type microbial reductions. We then applied five different, previously reported data management practices and fit log-linear and Weibull models to the resulting data. The results indicated a significant effect (α = 0.05) of the data management practices on the estimated model parameters and performance indicators. For example, when the negative plate counts were replaced by the LOD for log-linear data sets, the slope of the subsequent log-linear model was, on average, 22% smaller than for the original data, the resulting model underpredicted lethality by up to 2.0 log, and the Weibull model was erroneously selected as the most likely correct model for those data. The results demonstrate that it is important to explicitly report LODs and related data management protocols, which can significantly affect model results, interpretation, and utility. Ultimately, we recommend using only the positive plate counts to estimate model parameters for microbial reduction curves and avoiding any data value substitutions or transformations when managing negative plate counts to yield the most accurate model parameters.

Linear response of mutans streptococci to increasing frequency of xylitol chewing gum use: a randomized controlled trial [ISRCTN43479664].

PubMed

Ly, Kiet A; Milgrom, Peter; Roberts, Marilyn C; Yamaguchi, David K; Rothen, Marilynn; Mueller, Greg

2006-03-24

Xylitol is a naturally occurring sugar substitute that has been shown to reduce the level of mutans streptococci in plaque and saliva and to reduce tooth decay. It has been suggested that the degree of reduction is dependent on both the amount and the frequency of xylitol consumption. For xylitol to be successfully and cost-effectively used in public health prevention strategies dosing and frequency guidelines should be established. This study determined the reduction in mutans streptococci levels in plaque and unstimulated saliva to increasing frequency of xylitol gum use at a fixed total daily dose of 10.32 g over five weeks. Participants (n = 132) were randomized to either active groups (10.32 g xylitol/day) or a placebo control (9.828 g sorbitol and 0.7 g maltitol/day). All groups chewed 12 pieces of gum per day. The control group chewed 4 times/day and active groups chewed xylitol gum at a frequency of 2 times/day, 3 times/day, or 4 times/day. The 12 gum pieces were evenly divided into the frequency assigned to each group. Plaque and unstimulated saliva samples were taken at baseline and five-weeks and were cultured on modified Mitis Salivarius agar for mutans streptococci enumeration. There were no significant differences in mutans streptococci level among the groups at baseline. At five-weeks, mutans streptococci levels in plaque and unstimulated saliva showed a linear reduction with increasing frequency of xylitol chewing gum use at the constant daily dose. Although the difference observed for the group that chewed xylitol 2 times/day was consistent with the linear model, the difference was not significant. There was a linear reduction in mutans streptococci levels in plaque and saliva with increasing frequency of xylitol gum use at a constant daily dose. Reduction at a consumption frequency of 2 times per day was small and consistent with the linear-response line but was not statistically significant.

Know your market: use of online query tools to quantify trends in patient information-seeking behavior for varicose vein treatment.

PubMed

Harsha, Asheesh K; Schmitt, J Eric; Stavropoulos, S William

2014-01-01

To analyze Internet search data to characterize the temporal and geographic interest of Internet users in the United States in varicose vein treatment. From January 1, 2004, to September 1, 2012, the Google Trends tool was used to analyze query data for "varicose vein treatment" to identify individuals seeking treatment information for varicose veins. The term "varicose vein treatment" returned a search volume index (SVI), representing the search frequency relative to the total search volume during a specific time interval and region. Linear regression analysis and Kruskal-Wallis one-way analysis of variance were employed to characterize search results. Search traffic for varicose vein treatment increased by 520% over the 104-month study period. There was an annual mean increase of 28% (range, -18%-100%; standard deviation [SD], 35%), with a statistically significant linear increase in average yearly SVI over time (R(2) = 0.94, P < .0001). All years showed positive growth in mean SVI except for 2008 (18% decrease). There were statistically significant differences in SVI by month (Kruskal-Wallis, P < .0001) with significantly higher mean SVI compared with other months in May (190% increase; range, 26%-670%; SD, 15%) and June (209% increase; range, 35%-700%; SD, 20%). The southern United States showed significantly higher search traffic than all other regions (Tukey-Kramer, P < .00001). There have been significant increases in Internet search traffic related to varicose vein treatment in the past 8 years. Reflected in this trend is an annual peak in search traffic in the late spring months with an overall geographic bias toward southern states. Rigorous analysis of Internet search queries for medical procedures may prove useful to guide the efficient use of limited resources and marketing dollars. © 2013 The Society of Interventional Radiology Published by SIR All rights reserved.

High intensity click statistics from a 10 × 10 avalanche photodiode array

NASA Astrophysics Data System (ADS)

Kröger, Johannes; Ahrens, Thomas; Sperling, Jan; Vogel, Werner; Stolz, Heinrich; Hage, Boris

2017-11-01

Photon-number measurements are a fundamental technique for the discrimination and characterization of quantum states of light. Beyond the abilities of state-of-the-art devices, we present measurements with an array of 100 avalanche photodiodes exposed to photon-numbers ranging from well below to significantly above one photon per diode. Despite each single diode only discriminating between zero and non-zero photon-numbers we were able to extract a second order moment, which acts as a nonclassicality indicator. We demonstrate a vast enhancement of the applicable intensity range by two orders of magnitude relative to the standard application of such devices. It turns out that the probabilistic mapping of arbitrary photon-numbers on a finite number of registered clicks is not per se a disadvantage compared with true photon counters. Such detector arrays can bridge the gap between single-photon and linear detection, by investigation of the click statistics, without the necessity of photon statistics reconstruction.

Cognitive load, emotion, and performance in high-fidelity simulation among beginning nursing students: a pilot study.

PubMed

Schlairet, Maura C; Schlairet, Timothy James; Sauls, Denise H; Bellflowers, Lois

2015-03-01

Establishing the impact of the high-fidelity simulation environment on student performance, as well as identifying factors that could predict learning, would refine simulation outcome expectations among educators. The purpose of this quasi-experimental pilot study was to explore the impact of simulation on emotion and cognitive load among beginning nursing students. Forty baccalaureate nursing students participated in teaching simulations, rated their emotional state and cognitive load, and completed evaluation simulations. Two principal components of emotion were identified representing the pleasant activation and pleasant deactivation components of affect. Mean rating of cognitive load following simulation was high. Linear regression identiffed slight but statistically nonsignificant positive associations between principal components of emotion and cognitive load. Logistic regression identified a negative but statistically nonsignificant effect of cognitive load on assessment performance. Among lower ability students, a more pronounced effect of cognitive load on assessment performance was observed; this also was statistically non-significant. Copyright 2015, SLACK Incorporated.

On the Statistical Dependency of Identity Theft on Demographics

NASA Astrophysics Data System (ADS)

di Crescenzo, Giovanni

An improved understanding of the identity theft problem is widely agreed to be necessary to succeed in counter-theft efforts in legislative, financial and research institutions. In this paper we report on a statistical study about the existence of relationships between identity theft and area demographics in the US. The identity theft data chosen was the number of citizen complaints to the Federal Trade Commission in a large number of US municipalities. The list of demographics used for any such municipality included: estimated population, median resident age, estimated median household income, percentage of citizens with a high school or higher degree, percentage of unemployed residents, percentage of married residents, percentage of foreign born residents, percentage of residents living in poverty, density of law enforcement employees, crime index, and political orientation according to the 2004 presidential election. Our study findings, based on linear regression techniques, include statistically significant relationships between the number of identity theft complaints and a non-trivial subset of these demographics.

A statistical investigation into the relationship between meteorological parameters and suicide

NASA Astrophysics Data System (ADS)

Dixon, Keith W.; Shulman, Mark D.

1983-06-01

Many previous studies of relationships between weather and suicides have been inconclusive and contradictory. This study investigated the relationship between suicide frequency and meteorological conditions in people who are psychologically predisposed to commit suicide. Linear regressions of diurnal temperature change, departure of temperature from the climatic norm, mean daytime sky cover, and the number of hours of precipitation for each day were performed on daily suicide totals using standard computer methods. Statistical analyses of suicide data for days with and without frontal passages were also performed. Days with five or more suicides (clusterdays) were isolated, and their weather parameters compared with those of nonclusterdays. Results show that neither suicide totals nor clusterday occurrence can be predicted using these meteorological parameters, since statistically significant relationships were not found. Although the data hinted that frontal passages and large daily temperature changes may occur on days with above average suicide totals, it was concluded that the influence of the weather parameters used, on the suicide rate, is a minor one, if indeed one exists.

Comparison of seronegative and seropositive rheumatoid arthritis with regard to some clinical characteristics.

PubMed

Sahatçiu-Meka, Vjollca; Izairi, Remzi; Rexhepi, Sylejman; Manxhuka-Kerliu, Suzana

2009-01-01

The aim of this study is to establish a scientific comparative analysis between seronegative and seropositive rheumatoid arthritis (RA), with regard to some clinical characteristics. The studied group consisted of RA seronegative patients with titters lower then 1:64 defined by Rose-Waaler test, while the control group consisted of RA seropositive patients with titters of 1:64 or higher. Examinees all belonged to the 2nd and 3rd functional classes according to ARA criteria, were between 25-60 years of age (Xb = 49.96), with disease duration between 1-27 years (Xbox = 6.41). In the disease onset most frequently affected joints were metacarpophalangeal (MCP) and proximal interphalangeal (PIP) joint of the hands, almost equally represented with regard to sero-status and sex. During the examination seropositive patients showed a higher presence of inflamation of peripheral joints of hand and foot, but only the presence of PIP of the hands was statistically significant (chi2 = 15.63, p < 0.01). Knees, talocrural joints and elbows were more frequently affected in seropositive patients, whereas humeroscapular, coxofemoral and sacroiliacal joints were more frequently affected in seronegative patients, but without significant statistical difference with regard to sero-status. The presence of affected PIP of the hands (chi2 = 9.96, p < 0.01) and knees (chi2 = 4.17, p < 0.05) with regard to sex was statistically significant in seropositive female patients, as well as the presence of atacked PIP of the hands (chi2 = 6.08, p < 0.05), and cervical vertebrae (chi2 = 6.00, p < 0.05) in seropositive male patients. There were some differences between groups with regard to sex in metatarsophalangealjoints (MTP), PIP of the foot, and other joints, but without any statistical significance. In both subsets statistically significant domination was found in affected second (chi2 = 20.85, p < 0.01) and third (chi2 = 15.70, p < 0.01) fingers of the PIP level of hands and third finger (chi2 = 6.52, p < 0.05) of the MCP level. The mentioned parameters did not show a significant statistical difference with regard to sero-status and sex. Majority of patients had 1-4 deformities. Seropositive group had prevalent knee contractures, e.g. the eversion of the foot, while seronegative group had more "swan neck" deformities. The mentioned parameters did not show a significant statistical difference with regard to sero-status and sex. Longer duration of the disease resulted in an increased number of deformities, and this difference was statistically significant (t = 5.92, p < 0.01). Linear correlation between these two parameters resulted as high positive in general (r = 0.49, p < 0.01) and for groups separately, but without significant statistical difference with regard to sero-status. Duration of the disease with regard to the type of deformities was different in both subsets: in case of the longer duration of the disease "buttonhole" was prevalent with statistically significant difference in seropositive patients (t = 2.10, p < 0.05), whereas "fibular deviation" was prevalent in seronegative patients (t = 2.64, p < 0.01).

On the Statistical Errors of RADAR Location Sensor Networks with Built-In Wi-Fi Gaussian Linear Fingerprints

PubMed Central

Zhou, Mu; Xu, Yu Bin; Ma, Lin; Tian, Shuo

2012-01-01

The expected errors of RADAR sensor networks with linear probabilistic location fingerprints inside buildings with varying Wi-Fi Gaussian strength are discussed. As far as we know, the statistical errors of equal and unequal-weighted RADAR networks have been suggested as a better way to evaluate the behavior of different system parameters and the deployment of reference points (RPs). However, up to now, there is still not enough related work on the relations between the statistical errors, system parameters, number and interval of the RPs, let alone calculating the correlated analytical expressions of concern. Therefore, in response to this compelling problem, under a simple linear distribution model, much attention will be paid to the mathematical relations of the linear expected errors, number of neighbors, number and interval of RPs, parameters in logarithmic attenuation model and variations of radio signal strength (RSS) at the test point (TP) with the purpose of constructing more practical and reliable RADAR location sensor networks (RLSNs) and also guaranteeing the accuracy requirements for the location based services in future ubiquitous context-awareness environments. Moreover, the numerical results and some real experimental evaluations of the error theories addressed in this paper will also be presented for our future extended analysis. PMID:22737027

On the statistical errors of RADAR location sensor networks with built-in Wi-Fi Gaussian linear fingerprints.

PubMed

Zhou, Mu; Xu, Yu Bin; Ma, Lin; Tian, Shuo

2012-01-01

The expected errors of RADAR sensor networks with linear probabilistic location fingerprints inside buildings with varying Wi-Fi Gaussian strength are discussed. As far as we know, the statistical errors of equal and unequal-weighted RADAR networks have been suggested as a better way to evaluate the behavior of different system parameters and the deployment of reference points (RPs). However, up to now, there is still not enough related work on the relations between the statistical errors, system parameters, number and interval of the RPs, let alone calculating the correlated analytical expressions of concern. Therefore, in response to this compelling problem, under a simple linear distribution model, much attention will be paid to the mathematical relations of the linear expected errors, number of neighbors, number and interval of RPs, parameters in logarithmic attenuation model and variations of radio signal strength (RSS) at the test point (TP) with the purpose of constructing more practical and reliable RADAR location sensor networks (RLSNs) and also guaranteeing the accuracy requirements for the location based services in future ubiquitous context-awareness environments. Moreover, the numerical results and some real experimental evaluations of the error theories addressed in this paper will also be presented for our future extended analysis.

Statistical Mechanics of the Human Placenta: A Stationary State of a Near-Equilibrium System in a Linear Regime.

PubMed

Lecarpentier, Yves; Claes, Victor; Hébert, Jean-Louis; Krokidis, Xénophon; Blanc, François-Xavier; Michel, Francine; Timbely, Oumar

2015-01-01

All near-equilibrium systems under linear regime evolve to stationary states in which there is constant entropy production rate. In an open chemical system that exchanges matter and energy with the exterior, we can identify both the energy and entropy flows associated with the exchange of matter and energy. This can be achieved by applying statistical mechanics (SM), which links the microscopic properties of a system to its bulk properties. In the case of contractile tissues such as human placenta, Huxley's equations offer a phenomenological formalism for applying SM. SM was investigated in human placental stem villi (PSV) (n = 40). PSV were stimulated by means of KCl exposure (n = 20) and tetanic electrical stimulation (n = 20). This made it possible to determine statistical entropy (S), internal energy (E), affinity (A), thermodynamic force (A / T) (T: temperature), thermodynamic flow (v) and entropy production rate (A / T x v). We found that PSV operated near equilibrium, i.e., A ≺≺ 2500 J/mol and in a stationary linear regime, i.e., (A / T) varied linearly with v. As v was dramatically low, entropy production rate which quantified irreversibility of chemical processes appeared to be the lowest ever observed in any contractile system.

Simultaneous fitting of genomic-BLUP and Bayes-C components in a genomic prediction model.

PubMed

Iheshiulor, Oscar O M; Woolliams, John A; Svendsen, Morten; Solberg, Trygve; Meuwissen, Theo H E

2017-08-24

The rapid adoption of genomic selection is due to two key factors: availability of both high-throughput dense genotyping and statistical methods to estimate and predict breeding values. The development of such methods is still ongoing and, so far, there is no consensus on the best approach. Currently, the linear and non-linear methods for genomic prediction (GP) are treated as distinct approaches. The aim of this study was to evaluate the implementation of an iterative method (called GBC) that incorporates aspects of both linear [genomic-best linear unbiased prediction (G-BLUP)] and non-linear (Bayes-C) methods for GP. The iterative nature of GBC makes it less computationally demanding similar to other non-Markov chain Monte Carlo (MCMC) approaches. However, as a Bayesian method, GBC differs from both MCMC- and non-MCMC-based methods by combining some aspects of G-BLUP and Bayes-C methods for GP. Its relative performance was compared to those of G-BLUP and Bayes-C. We used an imputed 50 K single-nucleotide polymorphism (SNP) dataset based on the Illumina Bovine50K BeadChip, which included 48,249 SNPs and 3244 records. Daughter yield deviations for somatic cell count, fat yield, milk yield, and protein yield were used as response variables. GBC was frequently (marginally) superior to G-BLUP and Bayes-C in terms of prediction accuracy and was significantly better than G-BLUP only for fat yield. On average across the four traits, GBC yielded a 0.009 and 0.006 increase in prediction accuracy over G-BLUP and Bayes-C, respectively. Computationally, GBC was very much faster than Bayes-C and similar to G-BLUP. Our results show that incorporating some aspects of G-BLUP and Bayes-C in a single model can improve accuracy of GP over the commonly used method: G-BLUP. Generally, GBC did not statistically perform better than G-BLUP and Bayes-C, probably due to the close relationships between reference and validation individuals. Nevertheless, it is a flexible tool, in the sense, that it simultaneously incorporates some aspects of linear and non-linear models for GP, thereby exploiting family relationships while also accounting for linkage disequilibrium between SNPs and genes with large effects. The application of GBC in GP merits further exploration.

Folded concave penalized sparse linear regression: sparsity, statistical performance, and algorithmic theory for local solutions.

PubMed

Liu, Hongcheng; Yao, Tao; Li, Runze; Ye, Yinyu

2017-11-01

This paper concerns the folded concave penalized sparse linear regression (FCPSLR), a class of popular sparse recovery methods. Although FCPSLR yields desirable recovery performance when solved globally, computing a global solution is NP-complete. Despite some existing statistical performance analyses on local minimizers or on specific FCPSLR-based learning algorithms, it still remains open questions whether local solutions that are known to admit fully polynomial-time approximation schemes (FPTAS) may already be sufficient to ensure the statistical performance, and whether that statistical performance can be non-contingent on the specific designs of computing procedures. To address the questions, this paper presents the following threefold results: (i) Any local solution (stationary point) is a sparse estimator, under some conditions on the parameters of the folded concave penalties. (ii) Perhaps more importantly, any local solution satisfying a significant subspace second-order necessary condition (S 3 ONC), which is weaker than the second-order KKT condition, yields a bounded error in approximating the true parameter with high probability. In addition, if the minimal signal strength is sufficient, the S 3 ONC solution likely recovers the oracle solution. This result also explicates that the goal of improving the statistical performance is consistent with the optimization criteria of minimizing the suboptimality gap in solving the non-convex programming formulation of FCPSLR. (iii) We apply (ii) to the special case of FCPSLR with minimax concave penalty (MCP) and show that under the restricted eigenvalue condition, any S 3 ONC solution with a better objective value than the Lasso solution entails the strong oracle property. In addition, such a solution generates a model error (ME) comparable to the optimal but exponential-time sparse estimator given a sufficient sample size, while the worst-case ME is comparable to the Lasso in general. Furthermore, to guarantee the S 3 ONC admits FPTAS.

Non-linear dynamics of human locomotion: effects of rhythmic auditory cueing on local dynamic stability.

PubMed

Terrier, Philippe; Dériaz, Olivier

2013-01-01

It has been observed that times series of gait parameters [stride length (SL), stride time (ST), and stride speed (SS)], exhibit long-term persistence and fractal-like properties. Synchronizing steps with rhythmic auditory stimuli modifies the persistent fluctuation pattern to anti-persistence. Another non-linear method estimates the degree of resilience of gait control to small perturbations, i.e., the local dynamic stability (LDS). The method makes use of the maximal Lyapunov exponent, which estimates how fast a non-linear system embedded in a reconstructed state space (attractor) diverges after an infinitesimal perturbation. We propose to use an instrumented treadmill to simultaneously measure basic gait parameters (time series of SL, ST, and SS from which the statistical persistence among consecutive strides can be assessed), and the trajectory of the center of pressure (from which the LDS can be estimated). In 20 healthy participants, the response to rhythmic auditory cueing (RAC) of LDS and of statistical persistence [assessed with detrended fluctuation analysis (DFA)] was compared. By analyzing the divergence curves, we observed that long-term LDS (computed as the reverse of the average logarithmic rate of divergence between the 4th and the 10th strides downstream from nearest neighbors in the reconstructed attractor) was strongly enhanced (relative change +73%). That is likely the indication of a more dampened dynamics. The change in short-term LDS (divergence over one step) was smaller (+3%). DFA results (scaling exponents) confirmed an anti-persistent pattern in ST, SL, and SS. Long-term LDS (but not short-term LDS) and scaling exponents exhibited a significant correlation between them (r = 0.7). Both phenomena probably result from the more conscious/voluntary gait control that is required by RAC. We suggest that LDS and statistical persistence should be used to evaluate the efficiency of cueing therapy in patients with neurological gait disorders.

Inferring gene regression networks with model trees

PubMed Central

2010-01-01

Background Novel strategies are required in order to handle the huge amount of data produced by microarray technologies. To infer gene regulatory networks, the first step is to find direct regulatory relationships between genes building the so-called gene co-expression networks. They are typically generated using correlation statistics as pairwise similarity measures. Correlation-based methods are very useful in order to determine whether two genes have a strong global similarity but do not detect local similarities. Results We propose model trees as a method to identify gene interaction networks. While correlation-based methods analyze each pair of genes, in our approach we generate a single regression tree for each gene from the remaining genes. Finally, a graph from all the relationships among output and input genes is built taking into account whether the pair of genes is statistically significant. For this reason we apply a statistical procedure to control the false discovery rate. The performance of our approach, named REGNET, is experimentally tested on two well-known data sets: Saccharomyces Cerevisiae and E.coli data set. First, the biological coherence of the results are tested. Second the E.coli transcriptional network (in the Regulon database) is used as control to compare the results to that of a correlation-based method. This experiment shows that REGNET performs more accurately at detecting true gene associations than the Pearson and Spearman zeroth and first-order correlation-based methods. Conclusions REGNET generates gene association networks from gene expression data, and differs from correlation-based methods in that the relationship between one gene and others is calculated simultaneously. Model trees are very useful techniques to estimate the numerical values for the target genes by linear regression functions. They are very often more precise than linear regression models because they can add just different linear regressions to separate areas of the search space favoring to infer localized similarities over a more global similarity. Furthermore, experimental results show the good performance of REGNET. PMID:20950452

Factors associated with frailty in chronically ill older adults.

PubMed

Hackstaff, Lynn

2009-01-01

An ex post facto analysis of a secondary dataset examined relationships between physical frailty, depression, and the self-perceived domains of health status and quality-of-life in older adults. The randomized sample included 992 community-dwelling, chronically ill, and functionally impaired adults age 65 and older who received care from a Southern California Kaiser Permanente medical center between 1998 and 2002. Physical frailty represents a level of physiologic vulnerability and functional loss that results in dependence on others for basic, daily living needs (Fried et al., 2001). The purpose of the study was to identify possible intervention junctures related to self-efficacy of older adults in order to help optimize their functionality. Multivariate correlation analyses showed statistically significant positive correlations between frailty level and depression (r = .18; p = < .05), number of medical conditions (r = .09; p = < .05), and self-rated quality-of-life (r = .24; p = < .05). Frailty level showed a statistically significant negative correlation with self-perceived health status (r = -.25; p = < .05). Notably, no statistically significant correlation was found between age and frailty level (r = -.03; p = < .05). In linear regression, self-perceived health status had a partial variance with frailty level (part r = -.18). The significant correlations found support further research to identify interventions to help vulnerable, older adults challenge self-perceived capabilities so that they may achieve optimum functionality through increased physical activity earlier on, and increased self-efficacy to support successful adaptation to aging-related losses.

Longitudinal changes in maternal and neonatal anthropometrics: a case study of the Helsinki Birth Cohort, 1934-1944.

PubMed

Moltchanova, E; Eriksson, J G

2015-08-01

Changes in anthropometrics often reflect changes in living conditions, and one's characteristics at birth may be associated with future health. The aim of this study was to investigate the secular trends in maternal and neonatal anthropometrics in the Helsinki Birth Cohort Study. The study participants, thus, comprised all 13,345 live births recorded in Helsinki, Finland, between 1934 and 1944. Adult characteristics of the clinical subsample comprised of 2003 individuals, alive during 2003, were also analyzed. Linear Regression analysis with seasonal terms was applied to see whether clinically and statistically significant trends can be found in maternal age, height and body mass index (BMI) at pregnancy; gestational age, birth weight, ponderal index and sex ratio; and adult height, BMI and fat percentage. Statistically significant trends were found in maternal age and maternal BMI with abrupt changes between 1941 and 1944. Gestational age increased by an average of 0.11% per year (P<0.0001), and the proportion of premature births dropped from 7.9% in 1934 to 4.5% in 1944 (P<0.0001). In the clinical sample, a statistically significant, although small, average annual increase of 0.1% in adult heights was detected (P=0.0012 for men and P=0.0035 for women). In conclusion, although no significant changes were found in either neonatal or adult anthropometrics of babies born in Helsinki between 1934 and 1944, there were abrupt changes in the characteristics of their mothers.

Variation of microorganism concentrations in urban stormwater runoff with land use and seasons.

PubMed

Selvakumar, Ariamalar; Borst, Michael

2006-03-01

Stormwater runoff samples were collected from outfalls draining small municipal separate storm sewer systems. The samples were collected from three different land use areas based on local designation (high-density residential, low-density residential and landscaped commercial). The concentrations of microorganisms in the stormwater runoff were found to be similar in magnitude to, but less variable than, those reported in the stormwater National Pollutant Discharge Elimination System (NPDES) database. Microorganism concentrations from high-density residential areas were higher than those associated with low-density residential and landscaped commercial areas. Since the outfalls were free of sanitary wastewater cross-connections, the major sources of microorganisms to the stormwater runoff were most likely from the feces of domestic animals and wildlife. Concentrations of microorganisms were significantly affected by the season during which the samples were collected. The lowest concentrations were observed during winter except for Staphylococcus aureus. The Pearson correlation coefficients among different indicators showed weak linear relationships and the relationships were statistically significant. However, the relationships between indicators and pathogens were poorly correlated and were not statistically significant, suggesting the use of indicators as evidence of the presence of pathogens is not appropriate. Further, the correlation between the concentration of the traditionally monitored indicators (total coliforms and fecal coliforms) and the suggested substitutes (enterococci and E. coli) is weak, but statistically significant, suggesting that historical time series will be only a qualitative indicator of impaired waters under the revised criteria for recreational water quality by the US EPA.

Malignant testicular tumour incidence and mortality trends

PubMed Central

Wojtyła-Buciora, Paulina; Więckowska, Barbara; Krzywinska-Wiewiorowska, Małgorzata; Gromadecka-Sutkiewicz, Małgorzata

2016-01-01

Aim of the study In Poland testicular tumours are the most frequent cancer among men aged 20–44 years. Testicular tumour incidence since the 1980s and 1990s has been diversified geographically, with an increased risk of mortality in Wielkopolska Province, which was highlighted at the turn of the 1980s and 1990s. The aim of the study was the comparative analysis of the tendencies in incidence and death rates due to malignant testicular tumours observed among men in Poland and in Wielkopolska Province. Material and methods Data from the National Cancer Registry were used for calculations. The incidence/mortality rates among men due to malignant testicular cancer as well as the tendencies in incidence/death ratio observed in Poland and Wielkopolska were established based on regression equation. The analysis was deepened by adopting the multiple linear regression model. A p-value < 0.05 was arbitrarily adopted as the criterion of statistical significance, and for multiple comparisons it was modified according to the Bonferroni adjustment to a value of p < 0.0028. Calculations were performed with the use of PQStat v1.4.8 package. Results The incidence of malignant testicular neoplasms observed among men in Poland and in Wielkopolska Province indicated a significant rising tendency. The multiple linear regression model confirmed that the year variable is a strong incidence forecast factor only within the territory of Poland. A corresponding analysis of mortality rates among men in Poland and in Wielkopolska Province did not show any statistically significant correlations. Conclusions Late diagnosis of Polish patients calls for undertaking appropriate educational activities that would facilitate earlier reporting of the patients, thus increasing their chances for recovery. Introducing preventive examinations in the regions of increased risk of testicular tumour may allow earlier diagnosis. PMID:27095941

Distributed lags time series analysis versus linear correlation analysis (Pearson's r) in identifying the relationship between antipseudomonal antibiotic consumption and the susceptibility of Pseudomonas aeruginosa isolates in a single Intensive Care Unit of a tertiary hospital.

PubMed

Erdeljić, Viktorija; Francetić, Igor; Bošnjak, Zrinka; Budimir, Ana; Kalenić, Smilja; Bielen, Luka; Makar-Aušperger, Ksenija; Likić, Robert

2011-05-01

The relationship between antibiotic consumption and selection of resistant strains has been studied mainly by employing conventional statistical methods. A time delay in effect must be anticipated and this has rarely been taken into account in previous studies. Therefore, distributed lags time series analysis and simple linear correlation were compared in their ability to evaluate this relationship. Data on monthly antibiotic consumption for ciprofloxacin, piperacillin/tazobactam, carbapenems and cefepime as well as Pseudomonas aeruginosa susceptibility were retrospectively collected for the period April 2006 to July 2007. Using distributed lags analysis, a significant temporal relationship was identified between ciprofloxacin, meropenem and cefepime consumption and the resistance rates of P. aeruginosa isolates to these antibiotics. This effect was lagged for ciprofloxacin and cefepime [1 month (R=0.827, P=0.039) and 2 months (R=0.962, P=0.001), respectively] and was simultaneous for meropenem (lag 0, R=0.876, P=0.002). Furthermore, a significant concomitant effect of meropenem consumption on the appearance of multidrug-resistant P. aeruginosa strains (resistant to three or more representatives of classes of antibiotics) was identified (lag 0, R=0.992, P<0.001). This effect was not delayed and it was therefore identified both by distributed lags analysis and the Pearson's correlation coefficient. Correlation coefficient analysis was not able to identify relationships between antibiotic consumption and bacterial resistance when the effect was delayed. These results indicate that the use of diverse statistical methods can yield significantly different results, thus leading to the introduction of possibly inappropriate infection control measures. Copyright © 2010 Elsevier B.V. and the International Society of Chemotherapy. All rights reserved.

Ontogenetic scaling of caudal fin shape in Squalus acanthias (Chondrichthyes, Elasmobranchii): a geometric morphometric analysis with implications for caudal fin functional morphology.

PubMed

Reiss, Katie L; Bonnan, Matthew F

2010-07-01

The shark heterocercal caudal fin and its contribution to locomotion are of interest to biologists and paleontologists. Current hydrodynamic data show that the stiff dorsal lobe leads the ventral lobe, both lobes of the tail are synchronized during propulsion, and tail shape reflects its overall locomotor function. Given the difficulties surrounding the analysis of shark caudal fins in vivo, little is known about changes in tail shape related to ontogeny and sex in sharks. A quantifiable analysis of caudal fin shape may provide an acceptable proxy for inferring gross functional morphology where direct testing is difficult or impossible. We examined ontogenetic and sex-related shape changes in the caudal fins of 115 Squalus acanthias museum specimens, to test the hypothesis that significant shape changes in the caudal fin shape occur with increasing size and between the sexes. Using linear and geometric morphometrics, we examined caudal shape changes within the context of current hydrodynamic models. We found no statistically significant linear or shape difference between sexes, and near-isometric scaling trends for caudal dimensions. These results suggest that lift and thrust increase linearly with size and caudal span. Thin-plate splines results showed a significant allometric shape change associated with size and caudal span: the dorsal lobe elongates and narrows, whereas the ventral lobe broadens and expands ventrally. Our data suggest a combination of caudal fin morphology with other body morphology aspects, would refine, and better elucidate the hydrodynamic factors (if any) that underlie the significant shape changes we report here for S. acanthias.

Geographical Distribution Patterns of Iodine in Drinking-Water and Its Associations with Geological Factors in Shandong Province, China

PubMed Central

Gao, Jie; Zhang, Zhijie; Hu, Yi; Bian, Jianchao; Jiang, Wen; Wang, Xiaoming; Sun, Liqian; Jiang, Qingwu

2014-01-01

County-based spatial distribution characteristics and the related geological factors for iodine in drinking-water were studied in Shandong Province (China). Spatial autocorrelation analysis and spatial scan statistic were applied to analyze the spatial characteristics. Generalized linear models (GLMs) and geographically weighted regression (GWR) studies were conducted to explore the relationship between water iodine level and its related geological factors. The spatial distribution of iodine in drinking-water was significantly heterogeneous in Shandong Province (Moran’s I = 0.52, Z = 7.4, p < 0.001). Two clusters for high iodine in drinking-water were identified in the south-western and north-western parts of Shandong Province by the purely spatial scan statistic approach. Both GLMs and GWR indicated a significantly global association between iodine in drinking-water and geological factors. Furthermore, GWR showed obviously spatial variability across the study region. Soil type and distance to Yellow River were statistically significant at most areas of Shandong Province, confirming the hypothesis that the Yellow River causes iodine deposits in Shandong Province. Our results suggested that the more effective regional monitoring plan and water improvement strategies should be strengthened targeting at the cluster areas based on the characteristics of geological factors and the spatial variability of local relationships between iodine in drinking-water and geological factors. PMID:24852390

Social Media Self-Efficacy of Health Education Specialists: Training and Organizational Development Implications.

PubMed

Alber, Julia M; Paige, Samantha; Stellefson, Michael; Bernhardt, Jay M

2016-11-01

A growing number of public health organizations are applying the power of social media (SM) for health promotion and behavior change. This cross-sectional study of health education specialists (n = 353) examined which demographic and occupational factors were associated with SM self-efficacy, and evaluated SM self-efficacy related to each of the Seven Areas of Responsibility. A series of one-way analyses of variance were conducted to determine whether differences in SM self-efficacy existed by sex, age, years of work experience, and SM access at work. A multiple linear regression examined the relationship between SM self-efficacy and SM experience when controlling for demographic and occupational factors. Statistically significant differences in SM self-efficacy existed by age, F(2, 289) = 6.54, p = .002. SM experience (β = 1.43, t = 11.35, p < .001) was a statistically significant predictor of SM self-efficacy, even after controlling for age, sex, years of work experience, and level of SM access, F(5, 290) = 30.88, p < .001, R 2 = .35. Results revealed statistically significant differences in mean SM self-efficacy scores by the Areas of Responsibility, F(4.69, 1425.46) = 22.46, p < .001. Professional health organizations should have policies in place and trainings that are conducive to learning and applying SM for health education research and practice. © 2016 Society for Public Health Education.

Stress Management and Resiliency Training (SMART) program among Department of Radiology faculty: a pilot randomized clinical trial.

PubMed

Sood, Amit; Sharma, Varun; Schroeder, Darrell R; Gorman, Brian

2014-01-01

To test the efficacy of a Stress Management and Resiliency Training (SMART) program for decreasing stress and anxiety and improving resilience and quality of life among Department of Radiology physicians. The study was approved by the institutional review board. A total of 26 Department of Radiology physicians were randomized in a single-blind trial to either the SMART program or a wait-list control arm for 12 weeks. The program involved a single 90-min group session in the SMART training with two follow-up phone calls. Primary outcomes measured at baseline and week 12 included the Perceived Stress Scale, Linear Analog Self-Assessment Scale, Mindful Attention Awareness Scale, and Connor-Davidson Resilience Scale. A total of 22 physicians completed the study. A statistically significant improvement in perceived stress, anxiety, quality of life, and mindfulness at 12 weeks was observed in the study arm compared to the wait-list control arm; resilience also improved in the active arm, but the changes were not statistically significant when compared to the control arm. A single session to decrease stress among radiologists using the SMART program is feasible. Furthermore, the intervention afforded statistically significant and clinically meaningful improvement in anxiety, stress, quality of life, and mindful attention. Further studies including larger sample size and longer follow-up are warranted. Copyright © 2014. Published by Elsevier Inc.

Seasonality of climate change and oscillations in the Northeast Asia and Northwest Pacific

NASA Astrophysics Data System (ADS)

Ponomarev, V.; Salomatin, A.; Kaplunenko, D.; Krokhin, V.

2003-04-01

The main goals of this study are to estimate and compare the seasonality of centennial/semi-centennial climatic tendencies and dominated oscillations in surface air temperature and precipitation over continental and marginal areas of the Northeast Asia, as well as in the Northwest Pacific SST. We use monthly mean data for the 20th century from the NOAA Global History Climatic Network, JMA data base and WMU/COADS World Atlas of Surface Marine Data. Details of climate change/oscillations associated with cooling or warming in different areas and periods of a year are revealed. Wavelet analyses and two methods of the linear trend estimation are applied. First one is least-squares (LS) method with Fisher’s test for statistical significance level. Second one is nonparametric robust (NR) method, based on Theil's rank regression and Kendall's test for statistical significance level. The NR method should be applied to time series with abnormal distribution function typical for precipitation time series. Application of the NR method result in increase the statistical significance of both positive and negative linear trends in all cases of abnormal distribution with negative/positive skewness and low/high kurtosis. Using this method, we have determined spatial patterns of statistically significant climatic trends in surface air temperature, precipitation in the Northeast Asia, and in the Northwest Pacific SST. The most substantial centennial warming in the vast continental area of the mid-latitude band is found mainly for December March. The semi-centennial/ centennial cooling occurs in South Siberia and the subarctic mid-continental area in June September. Opposite tendencies were also revealed in precipitation and SST. Positive semi-centennial tendency in the SST in the second half of the 20th century predominates in the Kuroshio region and in the northwestern area of the subarctic gyre in winter. Negative tendency in the SST dominates in the southwestern subarctic gyre and the offshore area of the subtropic gyre in summer. Comparison of air temperature, precipitation, SST trends and oscillations in different seasons over land marginal and continental areas, as well as in the subarctic and subtropic zones indicates general features of the Northeast Asian Monsoon change/oscillation in 20th century and its second half. Similar features of seasonality in centennial, semi-centennial trends and dominated oscillations are manifested. Climate change and oscillation in the Northwest Pacific marginal seas revealed for the 20th century are explained.

Seasonality of climate change and oscillations in the Northeast Asia and Northwest Pacific

NASA Astrophysics Data System (ADS)

Ponomarev, V.; Salomatin, A.; Kaplunenko, D.; Krokhin, V.

2003-04-01

The main goals of this study are to estimate and compare the centennial/semi-centennial climatic tendencies and oscillations in surface air temperature and precipitation over continental and marginal areas of the Northeast Asian, as well as in the Northwest Pacific SST for all months of a year. We use monthly mean data for the 20th century from the NOAA Global History Climatic Network, JMA data base and WMU/COADS World Atlas of Surface Marine Data. Details of climate change/oscillations associated with cooling or warming in different areas and periods of a year are revealed. Wavelet analyses and two methods of the linear trend estimation are applied. First one is least-squares (LS) method with Fisher’s test for statistical significance level. Second one is nonparametric robust (NR) method, based on Theil's rank regression and Kendall's test for statistical significance level. The NR method should be applied to time series with abnormal distribution function typical for precipitation time series. Application of the NR method result in increase the statistical significance of both positive and negative linear trends in all cases of abnormal distribution with negative/positive skewness and low/high kurtosis. Using this method, we have determined spatial patterns of statistically significant climatic trends in surface air temperature, precipitation in the Northeast Asia, and in the Northwest Pacific SST. The most substantial centennial warming in the vast continental area of the mid-latitude band is found mainly for December March. The semi-centennial/ centennial cooling occurs in South Siberia and the subarctic mid-continental area in June September. Opposite tendencies were also revealed in precipitation and SST. Positive semi-centennial tendency in the SST in the second half of the 20th century predominates in the Kuroshio region and in the northwestern area of the subarctic gyre in winter. Negative tendency in the SST dominates in the southwestern subarctic gyre and the offshore area of the subtropic gyre in summer. Comparison of air temperature, precipitation, SST trends and oscillations in different seasons over land marginal and continental areas, as well as in the subarctic and subtropic zones indicates general features of the Northeast Asian Monsoon change/oscillation in 20th century and its second half. Similar features of seasonality in centennial, semi-centennial trends and dominated oscillations are manifested. Climate change and oscillation in the Northwest Pacific marginal seas revealed for the 20th century are explained.

Computational Complexity of Bosons in Linear Networks

DTIC Science & Technology

2017-03-01

photon statistics while strongly reducing emission probabilities: thus leading experimental teams pursuing large-scale BOSONSAMPLING have faced a hard...Potentially, this could motivate new validation protocols exploiting statistics that include this temporal degree of freedom. The impact of...photon- statistics polluted by higher-order terms, which can be mistakenly interpreted as decreased photon-indistinguishability. In fact, in many cases

K-nearest neighbors based methods for identification of different gear crack levels under different motor speeds and loads: Revisited

NASA Astrophysics Data System (ADS)

Wang, Dong

2016-03-01

Gears are the most commonly used components in mechanical transmission systems. Their failures may cause transmission system breakdown and result in economic loss. Identification of different gear crack levels is important to prevent any unexpected gear failure because gear cracks lead to gear tooth breakage. Signal processing based methods mainly require expertize to explain gear fault signatures which is usually not easy to be achieved by ordinary users. In order to automatically identify different gear crack levels, intelligent gear crack identification methods should be developed. The previous case studies experimentally proved that K-nearest neighbors based methods exhibit high prediction accuracies for identification of 3 different gear crack levels under different motor speeds and loads. In this short communication, to further enhance prediction accuracies of existing K-nearest neighbors based methods and extend identification of 3 different gear crack levels to identification of 5 different gear crack levels, redundant statistical features are constructed by using Daubechies 44 (db44) binary wavelet packet transform at different wavelet decomposition levels, prior to the use of a K-nearest neighbors method. The dimensionality of redundant statistical features is 620, which provides richer gear fault signatures. Since many of these statistical features are redundant and highly correlated with each other, dimensionality reduction of redundant statistical features is conducted to obtain new significant statistical features. At last, the K-nearest neighbors method is used to identify 5 different gear crack levels under different motor speeds and loads. A case study including 3 experiments is investigated to demonstrate that the developed method provides higher prediction accuracies than the existing K-nearest neighbors based methods for recognizing different gear crack levels under different motor speeds and loads. Based on the new significant statistical features, some other popular statistical models including linear discriminant analysis, quadratic discriminant analysis, classification and regression tree and naive Bayes classifier, are compared with the developed method. The results show that the developed method has the highest prediction accuracies among these statistical models. Additionally, selection of the number of new significant features and parameter selection of K-nearest neighbors are thoroughly investigated.

A FORTRAN technique for correlating a circular environmental variable with a linear physiological variable in the sugar maple.

PubMed

Pease, J M; Morselli, M F

1987-01-01

This paper deals with a computer program adapted to a statistical method for analyzing an unlimited quantity of binary recorded data of an independent circular variable (e.g. wind direction), and a linear variable (e.g. maple sap flow volume). Circular variables cannot be statistically analyzed with linear methods, unless they have been transformed. The program calculates a critical quantity, the acrophase angle (PHI, phi o). The technique is adapted from original mathematics [1] and is written in Fortran 77 for easier conversion between computer networks. Correlation analysis can be performed following the program or regression which, because of the circular nature of the independent variable, becomes periodic regression. The technique was tested on a file of approximately 4050 data pairs.

Dose-Response Relationship between Dietary Magnesium Intake and Risk of Type 2 Diabetes Mellitus: A Systematic Review and Meta-Regression Analysis of Prospective Cohort Studies.

PubMed

Fang, Xin; Han, Hedong; Li, Mei; Liang, Chun; Fan, Zhongjie; Aaseth, Jan; He, Jia; Montgomery, Scott; Cao, Yang

2016-11-19

The epidemiological evidence for a dose-response relationship between magnesium intake and risk of type 2 diabetes mellitus (T2D) is sparse. The aim of the study was to summarize the evidence for the association of dietary magnesium intake with risk of T2D and evaluate the dose-response relationship. We conducted a systematic review and meta-analysis of prospective cohort studies that reported dietary magnesium intake and risk of incident T2D. We identified relevant studies by searching major scientific literature databases and grey literature resources from their inception to February 2016. We included cohort studies that provided risk ratios, i.e., relative risks (RRs), odds ratios (ORs) or hazard ratios (HRs), for T2D. Linear dose-response relationships were assessed using random-effects meta-regression. Potential nonlinear associations were evaluated using restricted cubic splines. A total of 25 studies met the eligibility criteria. These studies comprised 637,922 individuals including 26,828 with a T2D diagnosis. Compared with the lowest magnesium consumption group in the population, the risk of T2D was reduced by 17% across all the studies; 19% in women and 16% in men. A statistically significant linear dose-response relationship was found between incremental magnesium intake and T2D risk. After adjusting for age and body mass index, the risk of T2D incidence was reduced by 8%-13% for per 100 mg/day increment in dietary magnesium intake. There was no evidence to support a nonlinear dose-response relationship between dietary magnesium intake and T2D risk. The combined data supports a role for magnesium in reducing risk of T2D, with a statistically significant linear dose-response pattern within the reference dose range of dietary intake among Asian and US populations. The evidence from Europe and black people is limited and more prospective studies are needed for the two subgroups.

A theory of fine structure image models with an application to detection and classification of dementia

PubMed Central

Penn, Richard; Werner, Michael; Thomas, Justin

2015-01-01

Background Estimation of stochastic process models from data is a common application of time series analysis methods. Such system identification processes are often cast as hypothesis testing exercises whose intent is to estimate model parameters and test them for statistical significance. Ordinary least squares (OLS) regression and the Levenberg-Marquardt algorithm (LMA) have proven invaluable computational tools for models being described by non-homogeneous, linear, stationary, ordinary differential equations. Methods In this paper we extend stochastic model identification to linear, stationary, partial differential equations in two independent variables (2D) and show that OLS and LMA apply equally well to these systems. The method employs an original nonparametric statistic as a test for the significance of estimated parameters. Results We show gray scale and color images are special cases of 2D systems satisfying a particular autoregressive partial difference equation which estimates an analogous partial differential equation. Several applications to medical image modeling and classification illustrate the method by correctly classifying demented and normal OLS models of axial magnetic resonance brain scans according to subject Mini Mental State Exam (MMSE) scores. Comparison with 13 image classifiers from the literature indicates our classifier is at least 14 times faster than any of them and has a classification accuracy better than all but one. Conclusions Our modeling method applies to any linear, stationary, partial differential equation and the method is readily extended to 3D whole-organ systems. Further, in addition to being a robust image classifier, estimated image models offer insights into which parameters carry the most diagnostic image information and thereby suggest finer divisions could be made within a class. Image models can be estimated in milliseconds which translate to whole-organ models in seconds; such runtimes could make real-time medicine and surgery modeling possible. PMID:26029638

A drift correction optimization technique for the reduction of the inter-measurement dispersion of isotope ratios measured using a multi-collector plasma mass spectrometer

NASA Astrophysics Data System (ADS)

Doherty, W.; Lightfoot, P. C.; Ames, D. E.

2014-08-01

The effects of polynomial interpolation and internal standardization drift corrections on the inter-measurement dispersion (statistical) of isotope ratios measured with a multi-collector plasma mass spectrometer were investigated using the (analyte, internal standard) isotope systems of (Ni, Cu), (Cu, Ni), (Zn, Cu), (Zn, Ga), (Sm, Eu), (Hf, Re) and (Pb, Tl). The performance of five different correction factors was compared using a (statistical) range based merit function ωm which measures the accuracy and inter-measurement range of the instrument calibration. The frequency distribution of optimal correction factors over two hundred data sets uniformly favored three particular correction factors while the remaining two correction factors accounted for a small but still significant contribution to the reduction of the inter-measurement dispersion. Application of the merit function is demonstrated using the detection of Cu and Ni isotopic fractionation in laboratory and geologic-scale chemical reactor systems. Solvent extraction (diphenylthiocarbazone (Cu, Pb) and dimethylglyoxime (Ni) was used to either isotopically fractionate the metal during extraction using the method of competition or to isolate the Cu and Ni from the sample (sulfides and associated silicates). In the best case, differences in isotopic composition of ± 3 in the fifth significant figure could be routinely and reliably detected for Cu65/63 and Ni61/62. One of the internal standardization drift correction factors uses a least squares estimator to obtain a linear functional relationship between the measured analyte and internal standard isotope ratios. Graphical analysis demonstrates that the points on these graphs are defined by highly non-linear parametric curves and not two linearly correlated quantities which is the usual interpretation of these graphs. The success of this particular internal standardization correction factor was found in some cases to be due to a fortuitous, scale dependent, parametric curve effect.

The impact of raising the minimum drinking age on driver fatalities.

PubMed

MacKinnon, D P; Woodward, J A

1986-12-01

Time series analysis was used to obtain statistical tests of the impact of raising the drinking age on monthly driver fatalities in Illinois, Michigan, and Massachusetts. A control series design permitted comparison between younger drivers (21 or less years) and older drivers (25 and older) within states where the minimum drinking age was raised. Since the two groups share the same driving conditions, it was important to demonstrate that any reduction in fatalities was limited to the young age group within which the drinking age change occurred. In addition, control states were selected to permit a comparison between driver fatalities of the young age group (21 or less) in states with the law change and young drivers in states without the law change. Significant immediate reductions in fatalities among 21 and younger drivers in Illinois and Michigan were observed after these states raised their minimum drinking age. No significant reductions in any control series were observed. A linear decrease in young driver fatalities was observed after the drinking age was raised in Massachusetts. There was also a significant linear decrease in young driver fatalities in the Connecticut control series, perhaps due to increasing awareness among young drivers of the dangers of drinking and driving.

Student performance on levels 1 and 2-CE of COMLEX-USA: do elective upper-level undergraduate science courses matter?

PubMed

Wong, Stanley K; Ramirez, Juan R; Helf, Scott C

2009-11-01

The effect of a variety of preadmission variables, including the number of elective preadmission upper-level science courses, on academic achievement is not well established. To investigate the relationship between number of preadmission variables and overall student academic achievement in osteopathic medical school. Academic records of osteopathic medical students in the 2008 and 2009 graduating classes of Western University of Health Sciences College of Osteopathic Medicine of the Pacific in Pomona, California, were analyzed. Multivariate linear regression analyses were performed to identify predictors of academic achievement based on Medical College Admission Test (MCAT) subscores, undergraduate grade point average (GPA), GPA in medical school basic science (preclinical GPA) and clinical clerkship (clinical GPA), and scores on the Comprehensive Osteopathic Medical Licensing Examination-USA (COMLEX-USA) Level 1 and Level 2-Cognitive Evaluation (CE). Records of 358 osteopathic medical students were evaluated. Analysis of beta coefficients suggested that undergraduate science GPA was the most important predictor of overall student academic achievement (P<.01). Biological sciences MCAT subscore was a more modest but still statistically significant predictor of preclinical GPA and COMLEX-USA Level 1 score (P<.01). Physical sciences MCAT subscore was also a statistically significant predictor of preclinical GPA, and verbal reasoning MCAT subscore was a statistically significant predictor of COMLEX-USA Level 2-CE score (both P<.01). Women had statistically significantly higher preclinical GPA and COMLEX-USA Level 2-CE scores than men (P<.05). Differences in some outcome variables were also associated with racial-ethnic background and age. Number of preadmission elective upper-level science courses taken by students before matriculation was not significantly correlated with any academic achievement variable. Although undergraduate science GPA and MCAT biological sciences subscore were significant predictors of overall academic achievement for osteopathic medical students, the number of elective upper-level science courses taken preadmission had no predictive value.

Geographical variation of cerebrovascular disease in New York State: the correlation with income

PubMed Central

Han, Daikwon; Carrow, Shannon S; Rogerson, Peter A; Munschauer, Frederick E

2005-01-01

Background Income is known to be associated with cerebrovascular disease; however, little is known about the more detailed relationship between cerebrovascular disease and income. We examined the hypothesis that the geographical distribution of cerebrovascular disease in New York State may be predicted by a nonlinear model using income as a surrogate socioeconomic risk factor. Results We used spatial clustering methods to identify areas with high and low prevalence of cerebrovascular disease at the ZIP code level after smoothing rates and correcting for edge effects; geographic locations of high and low clusters of cerebrovascular disease in New York State were identified with and without income adjustment. To examine effects of income, we calculated the excess number of cases using a non-linear regression with cerebrovascular disease rates taken as the dependent variable and income and income squared taken as independent variables. The resulting regression equation was: excess rate = 32.075 - 1.22*10-4(income) + 8.068*10-10(income2), and both income and income squared variables were significant at the 0.01 level. When income was included as a covariate in the non-linear regression, the number and size of clusters of high cerebrovascular disease prevalence decreased. Some 87 ZIP codes exceeded the critical value of the local statistic yielding a relative risk of 1.2. The majority of low cerebrovascular disease prevalence geographic clusters disappeared when the non-linear income effect was included. For linear regression, the excess rate of cerebrovascular disease falls with income; each $10,000 increase in median income of each ZIP code resulted in an average reduction of 3.83 observed cases. The significant nonlinear effect indicates a lessening of this income effect with increasing income. Conclusion Income is a non-linear predictor of excess cerebrovascular disease rates, with both low and high observed cerebrovascular disease rate areas associated with higher income. Income alone explains a significant amount of the geographical variance in cerebrovascular disease across New York State since both high and low clusters of cerebrovascular disease dissipate or disappear with income adjustment. Geographical modeling, including non-linear effects of income, may allow for better identification of other non-traditional risk factors. PMID:16242043

ADME evaluation in drug discovery. 1. Applications of genetic algorithms to the prediction of blood-brain partitioning of a large set of drugs.

PubMed

Hou, Tingjun; Xu, Xiaojie

2002-12-01

In this study, the relationships between the brain-blood concentration ratio of 96 structurally diverse compounds with a large number of structurally derived descriptors were investigated. The linear models were based on molecular descriptors that can be calculated for any compound simply from a knowledge of its molecular structure. The linear correlation coefficients of the models were optimized by genetic algorithms (GAs), and the descriptors used in the linear models were automatically selected from 27 structurally derived descriptors. The GA optimizations resulted in a group of linear models with three or four molecular descriptors with good statistical significance. The change of descriptor use as the evolution proceeds demonstrates that the octane/water partition coefficient and the partial negative solvent-accessible surface area multiplied by the negative charge are crucial to brain-blood barrier permeability. Moreover, we found that the predictions using multiple QSPR models from GA optimization gave quite good results in spite of the diversity of structures, which was better than the predictions using the best single model. The predictions for the two external sets with 37 diverse compounds using multiple QSPR models indicate that the best linear models with four descriptors are sufficiently effective for predictive use. Considering the ease of computation of the descriptors, the linear models may be used as general utilities to screen the blood-brain barrier partitioning of drugs in a high-throughput fashion.

Statistical and Biophysical Models for Predicting Total and Outdoor Water Use in Los Angeles

NASA Astrophysics Data System (ADS)

Mini, C.; Hogue, T. S.; Pincetl, S.

2012-04-01

Modeling water demand is a complex exercise in the choice of the functional form, techniques and variables to integrate in the model. The goal of the current research is to identify the determinants that control total and outdoor residential water use in semi-arid cities and to utilize that information in the development of statistical and biophysical models that can forecast spatial and temporal urban water use. The City of Los Angeles is unique in its highly diverse socio-demographic, economic and cultural characteristics across neighborhoods, which introduces significant challenges in modeling water use. Increasing climate variability also contributes to uncertainties in water use predictions in urban areas. Monthly individual water use records were acquired from the Los Angeles Department of Water and Power (LADWP) for the 2000 to 2010 period. Study predictors of residential water use include socio-demographic, economic, climate and landscaping variables at the zip code level collected from US Census database. Climate variables are estimated from ground-based observations and calculated at the centroid of each zip code by inverse-distance weighting method. Remotely-sensed products of vegetation biomass and landscape land cover are also utilized. Two linear regression models were developed based on the panel data and variables described: a pooled-OLS regression model and a linear mixed effects model. Both models show income per capita and the percentage of landscape areas in each zip code as being statistically significant predictors. The pooled-OLS model tends to over-estimate higher water use zip codes and both models provide similar RMSE values.Outdoor water use was estimated at the census tract level as the residual between total water use and indoor use. This residual is being compared with the output from a biophysical model including tree and grass cover areas, climate variables and estimates of evapotranspiration at very high spatial resolution. A genetic algorithm based model (Shuffled Complex Evolution-UA; SCE-UA) is also being developed to provide estimates of the predictions and parameters uncertainties and to compare against the linear regression models. Ultimately, models will be selected to undertake predictions for a range of climate change and landscape scenarios. Finally, project results will contribute to a better understanding of water demand to help predict future water use and implement targeted landscaping conservation programs to maintain sustainable water needs for a growing population under uncertain climate variability.

Can we detect a nonlinear response to temperature in European plant phenology?

PubMed

Jochner, Susanne; Sparks, Tim H; Laube, Julia; Menzel, Annette

2016-10-01

Over a large temperature range, the statistical association between spring phenology and temperature is often regarded and treated as a linear function. There are suggestions that a sigmoidal relationship with definite upper and lower limits to leaf unfolding and flowering onset dates might be more realistic. We utilised European plant phenological records provided by the European phenology database PEP725 and gridded monthly mean temperature data for 1951-2012 calculated from the ENSEMBLES data set E-OBS (version 7.0). We analysed 568,456 observations of ten spring flowering or leafing phenophases derived from 3657 stations in 22 European countries in order to detect possible nonlinear responses to temperature. Linear response rates averaged for all stations ranged between -7.7 (flowering of hazel) and -2.7 days °C -1 (leaf unfolding of beech and oak). A lower sensitivity at the cooler end of the temperature range was detected for most phenophases. However, a similar lower sensitivity at the warmer end was not that evident. For only ∼14 % of the station time series (where a comparison between linear and nonlinear model was possible), nonlinear models described the relationship significantly better than linear models. Although in most cases simple linear models might be still sufficient to predict future changes, this linear relationship between phenology and temperature might not be appropriate when incorporating phenological data of very cold (and possibly very warm) environments. For these cases, extrapolations on the basis of linear models would introduce uncertainty in expected ecosystem changes.

The effect of changes in sea surface temperature on linear growth of Porites coral in Ambon Bay

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

Corvianawatie, Corry, E-mail: corvianawatie@students.itb.ac.id; Putri, Mutiara R., E-mail: mutiara.putri@fitb.itb.ac.id; Cahyarini, Sri Y., E-mail: yuda@geotek.lipi.go.id

Coral is one of the most important organisms in the coral reef ecosystem. There are several factors affecting coral growth, one of them is changes in sea surface temperature (SST). The purpose of this research is to understand the influence of SST variability on the annual linear growth of Porites coral taken from Ambon Bay. The annual coral linear growth was calculated and compared to the annual SST from the Extended Reconstructed Sea Surface Temperature version 3b (ERSST v3b) model. Coral growth was calculated by using Coral X-radiograph Density System (CoralXDS) software. Coral sample X-radiographs were used as input data.more » Chronology was developed by calculating the coral’s annual growth bands. A pair of high and low density banding patterns observed in the coral’s X-radiograph represent one year of coral growth. The results of this study shows that Porites coral extents from 2001-2009 and had an average growth rate of 1.46 cm/year. Statistical analysis shows that the annual coral linear growth declined by 0.015 cm/year while the annual SST declined by 0.013°C/year. SST and the annual linear growth of Porites coral in the Ambon Bay is insignificantly correlated with r=0.304 (n=9, p>0.05). This indicates that annual SST variability does not significantly influence the linear growth of Porites coral from Ambon Bay. It is suggested that sedimentation load, salinity, pH or other environmental factors may affect annual linear coral growth.« less

Accuracy Assessment of Three-dimensional Surface Reconstructions of In vivo Teeth from Cone-beam Computed Tomography

PubMed Central

Sang, Yan-Hui; Hu, Hong-Cheng; Lu, Song-He; Wu, Yu-Wei; Li, Wei-Ran; Tang, Zhi-Hui

2016-01-01

Background: The accuracy of three-dimensional (3D) reconstructions from cone-beam computed tomography (CBCT) has been particularly important in dentistry, which will affect the effectiveness of diagnosis, treatment plan, and outcome in clinical practice. The aims of this study were to assess the linear, volumetric, and geometric accuracy of 3D reconstructions from CBCT and to investigate the influence of voxel size and CBCT system on the reconstructions results. Methods: Fifty teeth from 18 orthodontic patients were assigned to three groups as NewTom VG 0.15 mm group (NewTom VG; voxel size: 0.15 mm; n = 17), NewTom VG 0.30 mm group (NewTom VG; voxel size: 0.30 mm; n = 16), and VATECH DCTPRO 0.30 mm group (VATECH DCTPRO; voxel size: 0.30 mm; n = 17). The 3D reconstruction models of the teeth were segmented from CBCT data manually using Mimics 18.0 (Materialise Dental, Leuven, Belgium), and the extracted teeth were scanned by 3Shape optical scanner (3Shape A/S, Denmark). Linear and volumetric deviations were separately assessed by comparing the length and volume of the 3D reconstruction model with physical measurement by paired t-test. Geometric deviations were assessed by the root mean square value of the imposed 3D reconstruction and optical models by one-sample t-test. To assess the influence of voxel size and CBCT system on 3D reconstruction, analysis of variance (ANOVA) was used (α = 0.05). Results: The linear, volumetric, and geometric deviations were −0.03 ± 0.48 mm, −5.4 ± 2.8%, and 0.117 ± 0.018 mm for NewTom VG 0.15 mm group; −0.45 ± 0.42 mm, −4.5 ± 3.4%, and 0.116 ± 0.014 mm for NewTom VG 0.30 mm group; and −0.93 ± 0.40 mm, −4.8 ± 5.1%, and 0.194 ± 0.117 mm for VATECH DCTPRO 0.30 mm group, respectively. There were statistically significant differences between groups in terms of linear measurement (P < 0.001), but no significant difference in terms of volumetric measurement (P = 0.774). No statistically significant difference were found on geometric measurement between NewTom VG 0.15 mm and NewTom VG 0.30 mm groups (P = 0.999) while a significant difference was found between VATECH DCTPRO 0.30 mm and NewTom VG 0.30 mm groups (P = 0.006). Conclusions: The 3D reconstruction from CBCT data can achieve a high linear, volumetric, and geometric accuracy. Increasing voxel resolution from 0.30 to 0.15 mm does not result in increased accuracy of 3D tooth reconstruction while different systems can affect the accuracy. PMID:27270544

The linearized multistage model and the future of quantitative risk assessment.

PubMed

Crump, K S

1996-10-01

The linearized multistage (LMS) model has for over 15 years been the default dose-response model used by the U.S. Environmental Protection Agency (USEPA) and other federal and state regulatory agencies in the United States for calculating quantitative estimates of low-dose carcinogenic risks from animal data. The LMS model is in essence a flexible statistical model that can describe both linear and non-linear dose-response patterns, and that produces an upper confidence bound on the linear low-dose slope of the dose-response curve. Unlike its namesake, the Armitage-Doll multistage model, the parameters of the LMS do not correspond to actual physiological phenomena. Thus the LMS is 'biological' only to the extent that the true biological dose response is linear at low dose and that low-dose slope is reflected in the experimental data. If the true dose response is non-linear the LMS upper bound may overestimate the true risk by many orders of magnitude. However, competing low-dose extrapolation models, including those derived from 'biologically-based models' that are capable of incorporating additional biological information, have not shown evidence to date of being able to produce quantitative estimates of low-dose risks that are any more accurate than those obtained from the LMS model. Further, even if these attempts were successful, the extent to which more accurate estimates of low-dose risks in a test animal species would translate into improved estimates of human risk is questionable. Thus, it does not appear possible at present to develop a quantitative approach that would be generally applicable and that would offer significant improvements upon the crude bounding estimates of the type provided by the LMS model. Draft USEPA guidelines for cancer risk assessment incorporate an approach similar to the LMS for carcinogens having a linear mode of action. However, under these guidelines quantitative estimates of low-dose risks would not be developed for carcinogens having a non-linear mode of action; instead dose-response modelling would be used in the experimental range to calculate an LED10* (a statistical lower bound on the dose corresponding to a 10% increase in risk), and safety factors would be applied to the LED10* to determine acceptable exposure levels for humans. This approach is very similar to the one presently used by USEPA for non-carcinogens. Rather than using one approach for carcinogens believed to have a linear mode of action and a different approach for all other health effects, it is suggested herein that it would be more appropriate to use an approach conceptually similar to the 'LED10*-safety factor' approach for all health effects, and not to routinely develop quantitative risk estimates from animal data.

Regularized learning of linear ordered-statistic constant false alarm rate filters (Conference Presentation)

NASA Astrophysics Data System (ADS)

Havens, Timothy C.; Cummings, Ian; Botts, Jonathan; Summers, Jason E.

2017-05-01

The linear ordered statistic (LOS) is a parameterized ordered statistic (OS) that is a weighted average of a rank-ordered sample. LOS operators are useful generalizations of aggregation as they can represent any linear aggregation, from minimum to maximum, including conventional aggregations, such as mean and median. In the fuzzy logic field, these aggregations are called ordered weighted averages (OWAs). Here, we present a method for learning LOS operators from training data, viz., data for which you know the output of the desired LOS. We then extend the learning process with regularization, such that a lower complexity or sparse LOS can be learned. Hence, we discuss what 'lower complexity' means in this context and how to represent that in the optimization procedure. Finally, we apply our learning methods to the well-known constant-false-alarm-rate (CFAR) detection problem, specifically for the case of background levels modeled by long-tailed distributions, such as the K-distribution. These backgrounds arise in several pertinent imaging problems, including the modeling of clutter in synthetic aperture radar and sonar (SAR and SAS) and in wireless communications.

SOME STATISTICAL ISSUES RELATED TO MULTIPLE LINEAR REGRESSION MODELING OF BEACH BACTERIA CONCENTRATIONS

EPA Science Inventory

As a fast and effective technique, the multiple linear regression (MLR) method has been widely used in modeling and prediction of beach bacteria concentrations. Among previous works on this subject, however, several issues were insufficiently or inconsistently addressed. Those is...

Multivariate Strategies in Functional Magnetic Resonance Imaging

ERIC Educational Resources Information Center

Hansen, Lars Kai

2007-01-01

We discuss aspects of multivariate fMRI modeling, including the statistical evaluation of multivariate models and means for dimensional reduction. In a case study we analyze linear and non-linear dimensional reduction tools in the context of a "mind reading" predictive multivariate fMRI model.

Morse Code, Scrabble, and the Alphabet

ERIC Educational Resources Information Center

Richardson, Mary; Gabrosek, John; Reischman, Diann; Curtiss, Phyliss

2004-01-01

In this paper we describe an interactive activity that illustrates simple linear regression. Students collect data and analyze it using simple linear regression techniques taught in an introductory applied statistics course. The activity is extended to illustrate checks for regression assumptions and regression diagnostics taught in an…

Understanding the relationship between duration of untreated psychosis and outcomes: A statistical perspective.

PubMed

Hannigan, Ailish; Bargary, Norma; Kinsella, Anthony; Clarke, Mary

2017-06-14

Although the relationships between duration of untreated psychosis (DUP) and outcomes are often assumed to be linear, few studies have explored the functional form of these relationships. The aim of this study is to demonstrate the potential of recent advances in curve fitting approaches (splines) to explore the form of the relationship between DUP and global assessment of functioning (GAF). Curve fitting approaches were used in models to predict change in GAF at long-term follow-up using DUP for a sample of 83 individuals with schizophrenia. The form of the relationship between DUP and GAF was non-linear. Accounting for non-linearity increased the percentage of variance in GAF explained by the model, resulting in better prediction and understanding of the relationship. The relationship between DUP and outcomes may be complex and model fit may be improved by accounting for the form of the relationship. This should be routinely assessed and new statistical approaches for non-linear relationships exploited, if appropriate. © 2017 John Wiley & Sons Australia, Ltd.

The potential of composite cognitive scores for tracking progression in Huntington's disease.

PubMed

Jones, Rebecca; Stout, Julie C; Labuschagne, Izelle; Say, Miranda; Justo, Damian; Coleman, Allison; Dumas, Eve M; Hart, Ellen; Owen, Gail; Durr, Alexandra; Leavitt, Blair R; Roos, Raymund; O'Regan, Alison; Langbehn, Doug; Tabrizi, Sarah J; Frost, Chris

2014-01-01

Composite scores derived from joint statistical modelling of individual risk factors are widely used to identify individuals who are at increased risk of developing disease or of faster disease progression. We investigated the ability of composite measures developed using statistical models to differentiate progressive cognitive deterioration in Huntington's disease (HD) from natural decline in healthy controls. Using longitudinal data from TRACK-HD, the optimal combinations of quantitative cognitive measures to differentiate premanifest and early stage HD individuals respectively from controls was determined using logistic regression. Composite scores were calculated from the parameters of each statistical model. Linear regression models were used to calculate effect sizes (ES) quantifying the difference in longitudinal change over 24 months between premanifest and early stage HD groups respectively and controls. ES for the composites were compared with ES for individual cognitive outcomes and other measures used in HD research. The 0.632 bootstrap was used to eliminate biases which result from developing and testing models in the same sample. In early HD, the composite score from the HD change prediction model produced an ES for difference in rate of 24-month change relative to controls of 1.14 (95% CI: 0.90 to 1.39), larger than the ES for any individual cognitive outcome and UHDRS Total Motor Score and Total Functional Capacity. In addition, this composite gave a statistically significant difference in rate of change in premanifest HD compared to controls over 24-months (ES: 0.24; 95% CI: 0.04 to 0.44), even though none of the individual cognitive outcomes produced statistically significant ES over this period. Composite scores developed using appropriate statistical modelling techniques have the potential to materially reduce required sample sizes for randomised controlled trials.

Cosmological Constraints from Fourier Phase Statistics

NASA Astrophysics Data System (ADS)

Ali, Kamran; Obreschkow, Danail; Howlett, Cullan; Bonvin, Camille; Llinares, Claudio; Oliveira Franco, Felipe; Power, Chris

2018-06-01

Most statistical inference from cosmic large-scale structure relies on two-point statistics, i.e. on the galaxy-galaxy correlation function (2PCF) or the power spectrum. These statistics capture the full information encoded in the Fourier amplitudes of the galaxy density field but do not describe the Fourier phases of the field. Here, we quantify the information contained in the line correlation function (LCF), a three-point Fourier phase correlation function. Using cosmological simulations, we estimate the Fisher information (at redshift z = 0) of the 2PCF, LCF and their combination, regarding the cosmological parameters of the standard ΛCDM model, as well as a Warm Dark Matter (WDM) model and the f(R) and Symmetron modified gravity models. The galaxy bias is accounted for at the level of a linear bias. The relative information of the 2PCF and the LCF depends on the survey volume, sampling density (shot noise) and the bias uncertainty. For a volume of 1h^{-3}Gpc^3, sampled with points of mean density \\bar{n} = 2× 10^{-3} h3 Mpc^{-3} and a bias uncertainty of 13%, the LCF improves the parameter constraints by about 20% in the ΛCDM cosmology and potentially even more in alternative models. Finally, since a linear bias only affects the Fourier amplitudes (2PCF), but not the phases (LCF), the combination of the 2PCF and the LCF can be used to break the degeneracy between the linear bias and σ8, present in 2-point statistics.

Differential gene expression detection and sample classification using penalized linear regression models.

PubMed

Wu, Baolin

2006-02-15

Differential gene expression detection and sample classification using microarray data have received much research interest recently. Owing to the large number of genes p and small number of samples n (p > n), microarray data analysis poses big challenges for statistical analysis. An obvious problem owing to the 'large p small n' is over-fitting. Just by chance, we are likely to find some non-differentially expressed genes that can classify the samples very well. The idea of shrinkage is to regularize the model parameters to reduce the effects of noise and produce reliable inferences. Shrinkage has been successfully applied in the microarray data analysis. The SAM statistics proposed by Tusher et al. and the 'nearest shrunken centroid' proposed by Tibshirani et al. are ad hoc shrinkage methods. Both methods are simple, intuitive and prove to be useful in empirical studies. Recently Wu proposed the penalized t/F-statistics with shrinkage by formally using the (1) penalized linear regression models for two-class microarray data, showing good performance. In this paper we systematically discussed the use of penalized regression models for analyzing microarray data. We generalize the two-class penalized t/F-statistics proposed by Wu to multi-class microarray data. We formally derive the ad hoc shrunken centroid used by Tibshirani et al. using the (1) penalized regression models. And we show that the penalized linear regression models provide a rigorous and unified statistical framework for sample classification and differential gene expression detection.

SU-F-T-386: Analysis of Three QA Methods for Predicting Dose Deviation Pass Percentage for Lung SBRT VMAT Plans

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

Hardin, M; To, D; Giaddui, T

2016-06-15

Purpose: To investigate the significance of using pinpoint ionization chambers (IC) and RadCalc (RC) in determining the quality of lung SBRT VMAT plans with low dose deviation pass percentage (DDPP) as reported by ScandiDos Delta4 (D4). To quantify the relationship between DDPP and point dose deviations determined by IC (ICDD), RadCalc (RCDD), and median dose deviation reported by D4 (D4DD). Methods: Point dose deviations and D4 DDPP were compiled for 45 SBRT VMAT plans. Eighteen patients were treated on Varian Truebeam linear accelerators (linacs); the remaining 27 were treated on Elekta Synergy linacs with Agility collimators. A one-way analysis ofmore » variance (ANOVA) was performed to determine if there were any statistically significant differences between D4DD, ICDD, and RCDD. Tukey’s test was used to determine which pair of means was statistically different from each other. Multiple regression analysis was performed to determine if D4DD, ICDD, or RCDD are statistically significant predictors of DDPP. Results: Median DDPP, D4DD, ICDD, and RCDD were 80.5% (47.6%–99.2%), −0.3% (−2.0%–1.6%), 0.2% (−7.5%–6.3%), and 2.9% (−4.0%–19.7%), respectively. The ANOVA showed a statistically significant difference between D4DD, ICDD, and RCDD for a 95% confidence interval (p < 0.001). Tukey’s test revealed a statistically significant difference between two pairs of groups, RCDD-D4DD and RCDD-ICDD (p < 0.001), but no difference between ICDD-D4DD (p = 0.485). Multiple regression analysis revealed that ICDD (p = 0.04) and D4DD (p = 0.03) are statistically significant predictors of DDPP with an adjusted r{sup 2} of 0.115. Conclusion: This study shows ICDD predicts trends in D4 DDPP; however this trend is highly variable as shown by our low r{sup 2}. This work suggests that ICDD can be used as a method to verify DDPP in delivery of lung SBRT VMAT plans. RCDD may not validate low DDPP discovered in D4 QA for small field SBRT treatments.« less

Predicting oropharyngeal tumor volume throughout the course of radiation therapy from pretreatment computed tomography data using general linear models.

PubMed

Yock, Adam D; Rao, Arvind; Dong, Lei; Beadle, Beth M; Garden, Adam S; Kudchadker, Rajat J; Court, Laurence E

2014-05-01

The purpose of this work was to develop and evaluate the accuracy of several predictive models of variation in tumor volume throughout the course of radiation therapy. Nineteen patients with oropharyngeal cancers were imaged daily with CT-on-rails for image-guided alignment per an institutional protocol. The daily volumes of 35 tumors in these 19 patients were determined and used to generate (1) a linear model in which tumor volume changed at a constant rate, (2) a general linear model that utilized the power fit relationship between the daily and initial tumor volumes, and (3) a functional general linear model that identified and exploited the primary modes of variation between time series describing the changing tumor volumes. Primary and nodal tumor volumes were examined separately. The accuracy of these models in predicting daily tumor volumes were compared with those of static and linear reference models using leave-one-out cross-validation. In predicting the daily volume of primary tumors, the general linear model and the functional general linear model were more accurate than the static reference model by 9.9% (range: -11.6%-23.8%) and 14.6% (range: -7.3%-27.5%), respectively, and were more accurate than the linear reference model by 14.2% (range: -6.8%-40.3%) and 13.1% (range: -1.5%-52.5%), respectively. In predicting the daily volume of nodal tumors, only the 14.4% (range: -11.1%-20.5%) improvement in accuracy of the functional general linear model compared to the static reference model was statistically significant. A general linear model and a functional general linear model trained on data from a small population of patients can predict the primary tumor volume throughout the course of radiation therapy with greater accuracy than standard reference models. These more accurate models may increase the prognostic value of information about the tumor garnered from pretreatment computed tomography images and facilitate improved treatment management.

Nasolabial Morphology Following Nasoalveolar Molding in Infants With Unilateral Cleft Lip and Palate.

PubMed

Nur Yilmaz, Rahime Burcu; Germeç Çakan, Derya

2018-06-01

The aim of the present study is to evaluate the effects of nasoalveolar molding (NAM) therapy on nasolabial morphology three dimensionally, and compare the nasolabial linear and surface distance measurements in infants with unilateral cleft lip and palate. Facial plaster casts of 42 infants with unilateral cleft lip and palate taken at the onset (pre-NAM) and finishing stage (post-NAM) of NAM were scanned with 3dMDface stereophotogrammetry system (3dMD, Atlanta, GA). Nineteen nasolabial linear and surface distance measurements were performed on three-dimensional images. In addition to standard descriptive statistical calculations (means and SDs), pre- and post-NAM measurements were evaluated by paired t test. All measurements except lip gap, nostril floor width, and nostril diameter increased between pre-NAM and post-NAM. Nostril and lip height increased significantly on the cleft side (P < 0.05). No differences were present between linear and surface distance measurements except for nasal width measurement. Nasal and lip symmetry improved with NAM. The use of surface distance measurements may be advised particularly for continuous and curved anatomic structures in which circumference differences are expected.

Time Series Analysis and Forecasting of Wastewater Inflow into Bandar Tun Razak Sewage Treatment Plant in Selangor, Malaysia

NASA Astrophysics Data System (ADS)

Abunama, Taher; Othman, Faridah

2017-06-01

Analysing the fluctuations of wastewater inflow rates in sewage treatment plants (STPs) is essential to guarantee a sufficient treatment of wastewater before discharging it to the environment. The main objectives of this study are to statistically analyze and forecast the wastewater inflow rates into the Bandar Tun Razak STP in Kuala Lumpur, Malaysia. A time series analysis of three years’ weekly influent data (156weeks) has been conducted using the Auto-Regressive Integrated Moving Average (ARIMA) model. Various combinations of ARIMA orders (p, d, q) have been tried to select the most fitted model, which was utilized to forecast the wastewater inflow rates. The linear regression analysis was applied to testify the correlation between the observed and predicted influents. ARIMA (3, 1, 3) model was selected with the highest significance R-square and lowest normalized Bayesian Information Criterion (BIC) value, and accordingly the wastewater inflow rates were forecasted to additional 52weeks. The linear regression analysis between the observed and predicted values of the wastewater inflow rates showed a positive linear correlation with a coefficient of 0.831.

Fatigue behaviour of core-spun yarns containing filament by means of cyclic dynamic loading

NASA Astrophysics Data System (ADS)

Esin, S.; Osman, B.

2017-10-01

The behaviour of yarns under dynamic loading is important that leads to understand the growth characteristics which is exposed to repetitive loadings during usage of fabric made from these yarns. Fabric growth is undesirable property that originated from low resilience characteristics of fabric. In this study, the effects of the filament fineness and yarn linear density on fatigue behaviour of rigid-core spun yarns were determined. Cotton covered yarns containing different filament fineness of polyester (PET) draw textured yarns (DTY) (100d/36f, 100d/96f, 100d/144f, 100d/192f and 100d/333f) and yarn linear densities (37 tex, 30 tex, 25 tex and 21 tex) were manufactured by using a modified ring spinning system at the same spinning parameters. Repetitive loads were applied for 25 cycles at levels between 0.1 and 3 N. Dynamic modulus and dynamic strain of yarn samples were analyzed statistically. Results showed that filament fineness and yarn linear density have significance effect on dynamic modulus and dynamic strain after cyclic loading.

Molecular dynamics study of Al and Ni 3Al sputtering by Al clusters bombardment

NASA Astrophysics Data System (ADS)

Zhurkin, Eugeni E.; Kolesnikov, Anton S.

2002-06-01

The sputtering of Al and Ni 3Al (1 0 0) surfaces induced by impact of Al ions and Al N clusters ( N=2,4,6,9,13,55) with energies of 100 and 500 eV/atom is studied at atomic scale by means of classical molecular dynamics (MD). The MD code we used implements many-body tight binding potential splined to ZBL at short distances. Special attention has been paid to model dense cascades: we used quite big computation cells with lateral periodic and damped boundary conditions. In addition, long simulation times (10-25 ps) and representative statistics (up to 1000 runs per each case) were considered. The total sputtering yields, energy and time spectrums of sputtered particles, as well as preferential sputtering of compound target were analyzed, both in the linear and non-linear regimes. The significant "cluster enhancement" of sputtering yield was found for cluster sizes N⩾13. In parallel, we estimated collision cascade features depending on cluster size in order to interpret the nature of observed non-linear effects.

Two Paradoxes in Linear Regression Analysis.

PubMed

Feng, Ge; Peng, Jing; Tu, Dongke; Zheng, Julia Z; Feng, Changyong

2016-12-25

Regression is one of the favorite tools in applied statistics. However, misuse and misinterpretation of results from regression analysis are common in biomedical research. In this paper we use statistical theory and simulation studies to clarify some paradoxes around this popular statistical method. In particular, we show that a widely used model selection procedure employed in many publications in top medical journals is wrong. Formal procedures based on solid statistical theory should be used in model selection.

A statistical package for computing time and frequency domain analysis

NASA Technical Reports Server (NTRS)

Brownlow, J.

1978-01-01

The spectrum analysis (SPA) program is a general purpose digital computer program designed to aid in data analysis. The program does time and frequency domain statistical analyses as well as some preanalysis data preparation. The capabilities of the SPA program include linear trend removal and/or digital filtering of data, plotting and/or listing of both filtered and unfiltered data, time domain statistical characterization of data, and frequency domain statistical characterization of data.

Bayesian Statistics and Uncertainty Quantification for Safety Boundary Analysis in Complex Systems

NASA Technical Reports Server (NTRS)

He, Yuning; Davies, Misty Dawn

2014-01-01

The analysis of a safety-critical system often requires detailed knowledge of safe regions and their highdimensional non-linear boundaries. We present a statistical approach to iteratively detect and characterize the boundaries, which are provided as parameterized shape candidates. Using methods from uncertainty quantification and active learning, we incrementally construct a statistical model from only few simulation runs and obtain statistically sound estimates of the shape parameters for safety boundaries.

Statistical method to compare massive parallel sequencing pipelines.

PubMed

Elsensohn, M H; Leblay, N; Dimassi, S; Campan-Fournier, A; Labalme, A; Roucher-Boulez, F; Sanlaville, D; Lesca, G; Bardel, C; Roy, P

2017-03-01

Today, sequencing is frequently carried out by Massive Parallel Sequencing (MPS) that cuts drastically sequencing time and expenses. Nevertheless, Sanger sequencing remains the main validation method to confirm the presence of variants. The analysis of MPS data involves the development of several bioinformatic tools, academic or commercial. We present here a statistical method to compare MPS pipelines and test it in a comparison between an academic (BWA-GATK) and a commercial pipeline (TMAP-NextGENe®), with and without reference to a gold standard (here, Sanger sequencing), on a panel of 41 genes in 43 epileptic patients. This method used the number of variants to fit log-linear models for pairwise agreements between pipelines. To assess the heterogeneity of the margins and the odds ratios of agreement, four log-linear models were used: a full model, a homogeneous-margin model, a model with single odds ratio for all patients, and a model with single intercept. Then a log-linear mixed model was fitted considering the biological variability as a random effect. Among the 390,339 base-pairs sequenced, TMAP-NextGENe® and BWA-GATK found, on average, 2253.49 and 1857.14 variants (single nucleotide variants and indels), respectively. Against the gold standard, the pipelines had similar sensitivities (63.47% vs. 63.42%) and close but significantly different specificities (99.57% vs. 99.65%; p < 0.001). Same-trend results were obtained when only single nucleotide variants were considered (99.98% specificity and 76.81% sensitivity for both pipelines). The method allows thus pipeline comparison and selection. It is generalizable to all types of MPS data and all pipelines.

Modeling Effects of Temperature, Soil, Moisture, Nutrition and Variety As Determinants of Severity of Pythium Damping-Off and Root Disease in Subterranean Clover

PubMed Central

You, Ming P.; Rensing, Kelly; Renton, Michael; Barbetti, Martin J.

2017-01-01

Subterranean clover (Trifolium subterraneum) is a critical pasture legume in Mediterranean regions of southern Australia and elsewhere, including Mediterranean-type climatic regions in Africa, Asia, Australia, Europe, North America, and South America. Pythium damping-off and root disease caused by Pythium irregulare is a significant threat to subterranean clover in Australia and a study was conducted to define how environmental factors (viz. temperature, soil type, moisture and nutrition) as well as variety, influence the extent of damping-off and root disease as well as subterranean clover productivity under challenge by this pathogen. Relationships were statistically modeled using linear and generalized linear models and boosted regression trees. Modeling found complex relationships between explanatory variables and the extent of Pythium damping-off and root rot. Linear modeling identified high-level (4 or 5-way) significant interactions for each dependent variable (dry shoot and root weight, emergence, tap and lateral root disease index). Furthermore, all explanatory variables (temperature, soil, moisture, nutrition, variety) were found significant as part of some interaction within these models. A significant five-way interaction between all explanatory variables was found for both dry shoot and root dry weights, and a four way interaction between temperature, soil, moisture, and nutrition was found for both tap and lateral root disease index. A second approach to modeling using boosted regression trees provided support for and helped clarify the complex nature of the relationships found in linear models. All explanatory variables showed at least 5% relative influence on each of the five dependent variables. All models indicated differences due to soil type, with the sand-based soil having either higher weights, greater emergence, or lower disease indices; while lowest weights and less emergence, as well as higher disease indices, were found for loam soil and low temperature. There was more severe tap and lateral root rot disease in higher moisture situations. PMID:29184544

The study of interrelationship between raw water quality parameters, chlorine demand and the formation of disinfection by-products

NASA Astrophysics Data System (ADS)

Abdullah, Md. Pauzi; Yee, Lim Fang; Ata, Sadia; Abdullah, Abass; Ishak, Basar; Abidin, Khairul Nidzham Zainal

Disinfection is the most crucial process in the treatment of drinking water supply and is the final barrier against bacteriological impurities in drinking water. Chlorine is the primary disinfectant used in the drinking water treatment process throughout Malaysia. However, the occurrence of various disinfection by-products such as trihalomethanes (THM) and haloacetic acids created a major issue on the potential health hazards which may pose adverse health effects in both human and animals. To simulate real water treatment conditions and to represent the conditions inherent in a tropical country, this study was performed at an urbanized water treatment plant with a daily production of about 549,000 m 3 of treated water. The purpose of this work is to examine the relationship between the water quality parameters in the raw water with chlorine demand and the formation of disinfection by-products. This study also investigated the possibility of the statistical model applications for the prediction of chlorine demand and the THM formation. Two models were developed to estimate the chlorine demand and the THM formation. For the statistical evaluation, correlation and simple linear regression analysis were conducted using SPSS. The results of Kolmogorov-Smirnov test for the estimation of goodness-of-fit of the dependent variables of the models to the normal distribution showed that all the dependent variables followed the normal distribution at significance level of 0.05. Good linear correlations were observed between the independent parameters and formation of THM and the chlorine demand. This study also revealed that ammonia and the specific ultraviolet absorbent (SUVA) were the function of chlorine consumption in the treatment process. Chlorine dosage and SUVA increase the yield of THM. Chlorine demand and THM formation was moderately sensitive, but significant to the pH. The level of significance ( α) for the statistical tests and the inclusion of a variable in the model was 0.05. A better understanding of these relationships will help the water utilities or plant operators to minimize the THM formation, providing a healthier and better drinking water quality as well as optimizing the chlorine dosage in the disinfection process.

Estimation of stature from the foot and its segments in a sub-adult female population of North India

PubMed Central

2011-01-01

Background Establishing personal identity is one of the main concerns in forensic investigations. Estimation of stature forms a basic domain of the investigation process in unknown and co-mingled human remains in forensic anthropology case work. The objective of the present study was to set up standards for estimation of stature from the foot and its segments in a sub-adult female population. Methods The sample for the study constituted 149 young females from the Northern part of India. The participants were aged between 13 and 18 years. Besides stature, seven anthropometric measurements that included length of the foot from each toe (T1, T2, T3, T4, and T5 respectively), foot breadth at ball (BBAL) and foot breadth at heel (BHEL) were measured on both feet in each participant using standard methods and techniques. Results The results indicated that statistically significant differences (p < 0.05) between left and right feet occur in both the foot breadth measurements (BBAL and BHEL). Foot length measurements (T1 to T5 lengths) did not show any statistically significant bilateral asymmetry. The correlation between stature and all the foot measurements was found to be positive and statistically significant (p-value < 0.001). Linear regression models and multiple regression models were derived for estimation of stature from the measurements of the foot. The present study indicates that anthropometric measurements of foot and its segments are valuable in the estimation of stature. Foot length measurements estimate stature with greater accuracy when compared to foot breadth measurements. Conclusions The present study concluded that foot measurements have a strong relationship with stature in the sub-adult female population of North India. Hence, the stature of an individual can be successfully estimated from the foot and its segments using different regression models derived in the study. The regression models derived in the study may be applied successfully for the estimation of stature in sub-adult females, whenever foot remains are brought for forensic examination. Stepwise multiple regression models tend to estimate stature more accurately than linear regression models in female sub-adults. PMID:22104433

Estimation of stature from the foot and its segments in a sub-adult female population of North India.

PubMed

Krishan, Kewal; Kanchan, Tanuj; Passi, Neelam

2011-11-21

Establishing personal identity is one of the main concerns in forensic investigations. Estimation of stature forms a basic domain of the investigation process in unknown and co-mingled human remains in forensic anthropology case work. The objective of the present study was to set up standards for estimation of stature from the foot and its segments in a sub-adult female population. The sample for the study constituted 149 young females from the Northern part of India. The participants were aged between 13 and 18 years. Besides stature, seven anthropometric measurements that included length of the foot from each toe (T1, T2, T3, T4, and T5 respectively), foot breadth at ball (BBAL) and foot breadth at heel (BHEL) were measured on both feet in each participant using standard methods and techniques. The results indicated that statistically significant differences (p < 0.05) between left and right feet occur in both the foot breadth measurements (BBAL and BHEL). Foot length measurements (T1 to T5 lengths) did not show any statistically significant bilateral asymmetry. The correlation between stature and all the foot measurements was found to be positive and statistically significant (p-value < 0.001). Linear regression models and multiple regression models were derived for estimation of stature from the measurements of the foot. The present study indicates that anthropometric measurements of foot and its segments are valuable in the estimation of stature. Foot length measurements estimate stature with greater accuracy when compared to foot breadth measurements. The present study concluded that foot measurements have a strong relationship with stature in the sub-adult female population of North India. Hence, the stature of an individual can be successfully estimated from the foot and its segments using different regression models derived in the study. The regression models derived in the study may be applied successfully for the estimation of stature in sub-adult females, whenever foot remains are brought for forensic examination. Stepwise multiple regression models tend to estimate stature more accurately than linear regression models in female sub-adults.

Analysis of spontaneous MEG activity in mild cognitive impairment and Alzheimer's disease using spectral entropies and statistical complexity measures

NASA Astrophysics Data System (ADS)

Bruña, Ricardo; Poza, Jesús; Gómez, Carlos; García, María; Fernández, Alberto; Hornero, Roberto

2012-06-01

Alzheimer's disease (AD) is the most common cause of dementia. Over the last few years, a considerable effort has been devoted to exploring new biomarkers. Nevertheless, a better understanding of brain dynamics is still required to optimize therapeutic strategies. In this regard, the characterization of mild cognitive impairment (MCI) is crucial, due to the high conversion rate from MCI to AD. However, only a few studies have focused on the analysis of magnetoencephalographic (MEG) rhythms to characterize AD and MCI. In this study, we assess the ability of several parameters derived from information theory to describe spontaneous MEG activity from 36 AD patients, 18 MCI subjects and 26 controls. Three entropies (Shannon, Tsallis and Rényi entropies), one disequilibrium measure (based on Euclidean distance ED) and three statistical complexities (based on Lopez Ruiz-Mancini-Calbet complexity LMC) were used to estimate the irregularity and statistical complexity of MEG activity. Statistically significant differences between AD patients and controls were obtained with all parameters (p < 0.01). In addition, statistically significant differences between MCI subjects and controls were achieved by ED and LMC (p < 0.05). In order to assess the diagnostic ability of the parameters, a linear discriminant analysis with a leave-one-out cross-validation procedure was applied. The accuracies reached 83.9% and 65.9% to discriminate AD and MCI subjects from controls, respectively. Our findings suggest that MCI subjects exhibit an intermediate pattern of abnormalities between normal aging and AD. Furthermore, the proposed parameters provide a new description of brain dynamics in AD and MCI.

A Pulsed Thermographic Imaging System for Detection and Identification of Cotton Foreign Matter

PubMed Central

Kuzy, Jesse; Li, Changying

2017-01-01

Detection of foreign matter in cleaned cotton is instrumental to accurately grading cotton quality, which in turn impacts the marketability of the cotton. Current grading systems return estimates of the amount of foreign matter present, but provide no information about the identity of the contaminants. This paper explores the use of pulsed thermographic analysis to detect and identify cotton foreign matter. The design and implementation of a pulsed thermographic analysis system is described. A sample set of 240 foreign matter and cotton lint samples were collected. Hand-crafted waveform features and frequency-domain features were extracted and analyzed for statistical significance. Classification was performed on these features using linear discriminant analysis and support vector machines. Using waveform features and support vector machine classifiers, detection of cotton foreign matter was performed with 99.17% accuracy. Using frequency-domain features and linear discriminant analysis, identification was performed with 90.00% accuracy. These results demonstrate that pulsed thermographic imaging analysis produces data which is of significant utility for the detection and identification of cotton foreign matter. PMID:28273848

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.

Enhancing the Equating of Item Difficulty Metrics: Estimation of Reference Distribution. Research Report. ETS RR-14-07

ERIC Educational Resources Information Center

Ali, Usama S.; Walker, Michael E.

2014-01-01

Two methods are currently in use at Educational Testing Service (ETS) for equating observed item difficulty statistics. The first method involves the linear equating of item statistics in an observed sample to reference statistics on the same items. The second method, or the item response curve (IRC) method, involves the summation of conditional…

Statistical Package User’s Guide.

DTIC Science & Technology

1980-08-01

261 C. STACH Nonparametric Descriptive Statistics ... ......... ... 265 D. CHIRA Coefficient of Concordance...135 I.- -a - - W 7- Test Data: This program was tested using data from John Neter and William Wasserman, Applied Linear Statistical Models: Regression...length of data file e. new fileý name (not same as raw data file) 5. Printout as optioned for only. Comments: Ranked data are used for program CHIRA

Genomic similarity and kernel methods I: advancements by building on mathematical and statistical foundations.

PubMed

Schaid, Daniel J

2010-01-01

Measures of genomic similarity are the basis of many statistical analytic methods. We review the mathematical and statistical basis of similarity methods, particularly based on kernel methods. A kernel function converts information for a pair of subjects to a quantitative value representing either similarity (larger values meaning more similar) or distance (smaller values meaning more similar), with the requirement that it must create a positive semidefinite matrix when applied to all pairs of subjects. This review emphasizes the wide range of statistical methods and software that can be used when similarity is based on kernel methods, such as nonparametric regression, linear mixed models and generalized linear mixed models, hierarchical models, score statistics, and support vector machines. The mathematical rigor for these methods is summarized, as is the mathematical framework for making kernels. This review provides a framework to move from intuitive and heuristic approaches to define genomic similarities to more rigorous methods that can take advantage of powerful statistical modeling and existing software. A companion paper reviews novel approaches to creating kernels that might be useful for genomic analyses, providing insights with examples [1]. Copyright © 2010 S. Karger AG, Basel.

Lattice topology dictates photon statistics.

PubMed

Kondakci, H Esat; Abouraddy, Ayman F; Saleh, Bahaa E A

2017-08-21

Propagation of coherent light through a disordered network is accompanied by randomization and possible conversion into thermal light. Here, we show that network topology plays a decisive role in determining the statistics of the emerging field if the underlying lattice is endowed with chiral symmetry. In such lattices, eigenmode pairs come in skew-symmetric pairs with oppositely signed eigenvalues. By examining one-dimensional arrays of randomly coupled waveguides arranged on linear and ring topologies, we are led to a remarkable prediction: the field circularity and the photon statistics in ring lattices are dictated by its parity while the same quantities are insensitive to the parity of a linear lattice. For a ring lattice, adding or subtracting a single lattice site can switch the photon statistics from super-thermal to sub-thermal, or vice versa. This behavior is understood by examining the real and imaginary fields on a lattice exhibiting chiral symmetry, which form two strands that interleave along the lattice sites. These strands can be fully braided around an even-sited ring lattice thereby producing super-thermal photon statistics, while an odd-sited lattice is incommensurate with such an arrangement and the statistics become sub-thermal.

Upper extremity disorders in heavy industry workers in Greece.

PubMed

Tsouvaltzidou, Thomaella; Alexopoulos, Evangelos; Fragkakis, Ioannis; Jelastopulu, Eleni

2017-06-18

To investigate the disability due to musculoskeletal disorders of the upper extremities in heavy industry workers. The population under study consisted of 802 employees, both white- and blue-collar, working in a shipyard industry in Athens, Greece. Data were collected through the distribution of questionnaires and the recording of individual and job-related characteristics during the period 2006-2009. The questionnaires used were the Quick Disabilities of the Arm, Shoulder and Hand (QD) Outcome Measure, the Work Ability Index (WAI) and the Short-Form-36 (SF-36) Health Survey. The QD was divided into three parameters - movement restrictions in everyday activities, work and sports/music activities - and the SF-36 into two items, physical and emotional. Multiple linear regression analysis was performed by means of the SPSS v.22 for Windows Statistical Package. The answers given by the participants for the QD did not reveal great discomfort regarding the execution of manual tasks, with the majority of the participants scoring under 5%, meaning no disability. After conducting multiple linear regression, age revealed a positive association with the parameter of restrictions in everyday activities (b = 0.64, P = 0.000). Basic education showed a statistically significant association regarding restrictions during leisure activities, with b = 2.140 ( P = 0.029) for compulsory education graduates. WAI's final score displayed negative charging in the regression analysis of all three parameters, with b = -0.142 ( P = 0.0), b = -0.099 ( P = 0.055) and b = -0.376 ( P = 0.001) respectively, while the physical and emotional components of SF-36 associated with movement restrictions only in daily activities and work. The participants' specialty made no statistically significant associations with any of the three parameters of the QD. Increased musculoskeletal disorders of the upper extremity are associated with older age, lower basic education and physical and mental/emotional health and reduced working ability.

SU-F-T-551: Beam Hardening and Attenuation of Photon Beams Using Integral Quality Monitor in Radiotherapy

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

Casar, B; Carot, I Mendez; Peterlin, P

2016-06-15

Purpose: Aim of the multi-centre study was to analyse beam hardening effect of the Integral Quality Monitor (IQM) for high energy photon beams used in radiotherapy with linear accelerators. Generic values for attenuation coefficient k(IQM) of IQM system were additionally investigated. Methods: Beam hardening effect of the IQM system was studied for a set of standard nominal photon energies (6 MV–18 MV) and two flattening filter free (FFF) energies (6 MV FFF and 10 MV FFF). PDD curves were measured and analysed for various square radiation fields, with and without IQM in place. Differences between PDD curves were statistically analysedmore » through comparison of respective PDD-20,10 values. Attenuation coefficients k(IQM) were determined for the same range of photon energies. Results: Statistically significant differences in beam qualities for all evaluated high energy photon beams were found, comparing PDD-20,10 values derived from PDD curves with and without IQM in place. Significance of beam hardening effect was statistically proven with high confidence (p < 0,01) for all analysed photon beams except for 15 MV (p = 0,078), although relative differences in beam qualities were minimal, ranging from 0,1 % to 0,5 %. Attenuation of the IQM system showed negligible dependence on radiation field size. However, clinically important dependence of kIQM versus TPRs20,10 was found: 0,941 for 6 MV photon beams, to 0,959 for 18 MV photon beams, with highest uncertainty below 0,006. k(IQM) versus TPRs were tabulated and polynomial equation for the determination of k(IQM) is suggested for clinical use. Conclusion: There was no clinically relevant beam hardening, when IQM system was on linear accelerators. Consequently, no additional commissioning is needed for the IQM system regarding the determination of beam qualities. Generic values for k(IQM) are proposed and can be used as tray factors for complete range of examined photon beam energies.« less

Control Variate Selection for Multiresponse Simulation.

DTIC Science & Technology

1987-05-01

M. H. Knuter, Applied Linear Regression Mfodels, Richard D. Erwin, Inc., Homewood, Illinois, 1983. Neuts, Marcel F., Probability, Allyn and Bacon...1982. Neter, J., V. Wasserman, and M. H. Knuter, Applied Linear Regression .fodels, Richard D. Erwin, Inc., Homewood, Illinois, 1983. Neuts, Marcel F...Aspects of J%,ultivariate Statistical Theory, John Wiley and Sons, New York, New York, 1982. dY Neter, J., W. Wasserman, and M. H. Knuter, Applied Linear Regression Mfodels

An Investigation of the Fit of Linear Regression Models to Data from an SAT[R] Validity Study. Research Report 2011-3

ERIC Educational Resources Information Center

Kobrin, Jennifer L.; Sinharay, Sandip; Haberman, Shelby J.; Chajewski, Michael

2011-01-01

This study examined the adequacy of a multiple linear regression model for predicting first-year college grade point average (FYGPA) using SAT[R] scores and high school grade point average (HSGPA). A variety of techniques, both graphical and statistical, were used to examine if it is possible to improve on the linear regression model. The results…

Central Limit Theorems for Linear Statistics of Heavy Tailed Random Matrices

NASA Astrophysics Data System (ADS)

Benaych-Georges, Florent; Guionnet, Alice; Male, Camille

2014-07-01

We show central limit theorems (CLT) for the linear statistics of symmetric matrices with independent heavy tailed entries, including entries in the domain of attraction of α-stable laws and entries with moments exploding with the dimension, as in the adjacency matrices of Erdös-Rényi graphs. For the second model, we also prove a central limit theorem of the moments of its empirical eigenvalues distribution. The limit laws are Gaussian, but unlike the case of standard Wigner matrices, the normalization is the one of the classical CLT for independent random variables.

Characterisation of turbulence downstream of a linear compressor cascade

NASA Astrophysics Data System (ADS)

di Mare, Luca; Jelly, Thomas; Day, Ivor

2014-11-01

Characterisation of turbulence in turbomachinery remains one of the most complex tasks in fluid mechanics. In addition, current closure models required for Reynolds-averaged Navier-Stokes computations do not accurately represent the action of turbulent forces against the mean flow. Therefore, the statistical properties of turbulence in turbomachinery are of significant interest. In the current work, single- and two-point hot-wire measurements have been acquired downstream of a linear compressor cascade in order to examine the properties of large-scale turbulent structures and to assess how they affect turbulent momentum and energy transfer in compressor passages. The cascade has seven controlled diffusion which are representative of high-pressure stator blades found in turbofan engines. Blade chord, thickness and camber are 0.1515 m, 9.3% and 42 degrees, respectively. Measurements were acquired at a chord Reynolds number of 6 . 92 ×105 . Single-point statistics highlight differences in turbulence structure when comparing mid-span and end-wall regions. Evaluation of two-point correlations and their corresponding spectra reveal the length-scales of the energy-bearing eddies in the cascade. Ultimately, these measurements can be used to calibrate future computational models. The authors gratefully acknowledge Rolls-Royce plc for funding this work and granting permission for its publication.

Ensemble survival tree models to reveal pairwise interactions of variables with time-to-events outcomes in low-dimensional setting

PubMed Central

Dazard, Jean-Eudes; Ishwaran, Hemant; Mehlotra, Rajeev; Weinberg, Aaron; Zimmerman, Peter

2018-01-01

Unraveling interactions among variables such as genetic, clinical, demographic and environmental factors is essential to understand the development of common and complex diseases. To increase the power to detect such variables interactions associated with clinical time-to-events outcomes, we borrowed established concepts from random survival forest (RSF) models. We introduce a novel RSF-based pairwise interaction estimator and derive a randomization method with bootstrap confidence intervals for inferring interaction significance. Using various linear and nonlinear time-to-events survival models in simulation studies, we first show the efficiency of our approach: true pairwise interaction-effects between variables are uncovered, while they may not be accompanied with their corresponding main-effects, and may not be detected by standard semi-parametric regression modeling and test statistics used in survival analysis. Moreover, using a RSF-based cross-validation scheme for generating prediction estimators, we show that informative predictors may be inferred. We applied our approach to an HIV cohort study recording key host gene polymorphisms and their association with HIV change of tropism or AIDS progression. Altogether, this shows how linear or nonlinear pairwise statistical interactions of variables may be efficiently detected with a predictive value in observational studies with time-to-event outcomes. PMID:29453930

Internet gaming disorder in early adolescence: Associations with parental and adolescent mental health.

PubMed

Wartberg, L; Kriston, L; Kramer, M; Schwedler, A; Lincoln, T M; Kammerl, R

2017-06-01

Internet gaming disorder (IGD) has been included in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Currently, associations between IGD in early adolescence and mental health are largely unexplained. In the present study, the relation of IGD with adolescent and parental mental health was investigated for the first time. We surveyed 1095 family dyads (an adolescent aged 12-14 years and a related parent) with a standardized questionnaire for IGD as well as for adolescent and parental mental health. We conducted linear (dimensional approach) and logistic (categorical approach) regression analyses. Both with dimensional and categorical approaches, we observed statistically significant associations between IGD and male gender, a higher degree of adolescent antisocial behavior, anger control problems, emotional distress, self-esteem problems, hyperactivity/inattention and parental anxiety (linear regression model: corrected R 2 =0.41, logistic regression model: Nagelkerke's R 2 =0.41). IGD appears to be associated with internalizing and externalizing problems in adolescents. Moreover, the findings of the present study provide first evidence that not only adolescent but also parental mental health is relevant to IGD in early adolescence. Adolescent and parental mental health should be considered in prevention and intervention programs for IGD in adolescence. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Latitudinal migration of sunspots based on the ESAI database

NASA Astrophysics Data System (ADS)

Zhang, Juan; Li, Fu-Yu; Feng, Wen

2018-01-01

The latitudinal migration of sunspots toward the equator, which implies there is propagation of the toroidal magnetic flux wave at the base of the solar convection zone, is one of the crucial observational bases for the solar dynamo to generate a magnetic field by shearing of the pre-existing poloidal magnetic field through differential rotation. The Extended time series of Solar Activity Indices (ESAI) elongated the Greenwich observation record of sunspots by several decades in the past. In this study, ESAI’s yearly mean latitude of sunspots in the northern and southern hemispheres during the years 1854 to 1985 is utilized to statistically test whether hemispherical latitudinal migration of sunspots in a solar cycle is linear or nonlinear. It is found that a quadratic function is statistically significantly better at describing hemispherical latitudinal migration of sunspots in a solar cycle than a linear function. In addition, the latitude migration velocity of sunspots in a solar cycle decreases as the cycle progresses, providing a particular constraint for solar dynamo models. Indeed, the butterfly wing pattern with a faster latitudinal migration rate should present stronger solar activity with a shorter cycle period, and it is located at higher latitudinal position, giving evidence to support the Babcock-Leighton dynamo mechanism.

Ensemble survival tree models to reveal pairwise interactions of variables with time-to-events outcomes in low-dimensional setting.

PubMed

Dazard, Jean-Eudes; Ishwaran, Hemant; Mehlotra, Rajeev; Weinberg, Aaron; Zimmerman, Peter

2018-02-17

Unraveling interactions among variables such as genetic, clinical, demographic and environmental factors is essential to understand the development of common and complex diseases. To increase the power to detect such variables interactions associated with clinical time-to-events outcomes, we borrowed established concepts from random survival forest (RSF) models. We introduce a novel RSF-based pairwise interaction estimator and derive a randomization method with bootstrap confidence intervals for inferring interaction significance. Using various linear and nonlinear time-to-events survival models in simulation studies, we first show the efficiency of our approach: true pairwise interaction-effects between variables are uncovered, while they may not be accompanied with their corresponding main-effects, and may not be detected by standard semi-parametric regression modeling and test statistics used in survival analysis. Moreover, using a RSF-based cross-validation scheme for generating prediction estimators, we show that informative predictors may be inferred. We applied our approach to an HIV cohort study recording key host gene polymorphisms and their association with HIV change of tropism or AIDS progression. Altogether, this shows how linear or nonlinear pairwise statistical interactions of variables may be efficiently detected with a predictive value in observational studies with time-to-event outcomes.

Age-related motor unit remodeling in the Tibialis Anterior.

PubMed

Siddiqi, Ariba; Kumar, Dinesh; Arjunan, Sridhar

2015-01-01

Limited studies exist on the use of surface electromyogram (EMG) signal features to detect age-related motor unit remodeling in the Tibialis Anterior. Motor unit remodeling leads to declined muscle strength and force steadiness during submaximal contractions which are factors for risk of falls in the elderly. This study investigated the remodeling phenomena in the Tibialis Anterior using sample entropy and higher order statistics. Eighteen young (26.1 ± 2.9 years) and twelve elderly (68.7 ± 9.0 years) participants performed isometric dorsiflexion of the ankle at 20% maximal voluntary contraction (MVC) and their Tibialis Anterior (TA) EMG was recorded. Sample entropy, Gaussianity and Linearity Test statistics were calculated from the recorded EMG for each MVC. Shapiro-Wilk test was used to determine normality, and either a two-tail student t-test or Wilcoxon rank sum test was performed to determine significant difference in the EMG features between the young and old cohorts. Results show age-related motor unit remodeling to be depicted by decreased sample entropy (p <; 0.1), increased non-Gaussianity (p <; 0.05) and lesser degree of linearity in the elderly. This is due to the increased sparsity of the MUAPs as a result of the denervation-reinnervation process, and the decrease in total number of motor units.

Applications of statistics to medical science, III. Correlation and regression.

PubMed

Watanabe, Hiroshi

2012-01-01

In this third part of a series surveying medical statistics, the concepts of correlation and regression are reviewed. In particular, methods of linear regression and logistic regression are discussed. Arguments related to survival analysis will be made in a subsequent paper.

Enrichment of statistical power for genome-wide association studies

USDA-ARS?s Scientific Manuscript database

The inheritance of most human diseases and agriculturally important traits is controlled by many genes with small effects. Identifying these genes, while simultaneously controlling false positives, is challenging. Among available statistical methods, the mixed linear model (MLM) has been the most fl...

Linear indices of the "molecular pseudograph's atom adjacency matrix": definition, significance-interpretation, and application to QSAR analysis of flavone derivatives as HIV-1 integrase inhibitors.

PubMed

Marrero-Ponce, Yovani

2004-01-01

This report describes a new set of molecular descriptors of relevance to QSAR/QSPR studies and drug design, atom linear indices fk(xi). These atomic level chemical descriptors are based on the calculation of linear maps on Rn[fk(xi): Rn--> Rn] in canonical basis. In this context, the kth power of the molecular pseudograph's atom adjacency matrix [Mk(G)] denotes the matrix of fk(xi) with respect to the canonical basis. In addition, a local-fragment (atom-type) formalism was developed. The kth atom-type linear indices are calculated by summing the kth atom linear indices of all atoms of the same atom type in the molecules. Moreover, total (whole-molecule) linear indices are also proposed. This descriptor is a linear functional (linear form) on Rn. That is, the kth total linear indices is a linear map from Rn to the scalar R[ fk(x): Rn --> R]. Thus, the kth total linear indices are calculated by summing the atom linear indices of all atoms in the molecule. The features of the kth total and local linear indices are illustrated by examples of various types of molecular structures, including chain-lengthening, branching, heteroatoms-content, and multiple bonds. Additionally, the linear independence of the local linear indices to other 0D, 1D, 2D, and 3D molecular descriptors is demonstrated by using principal component analysis for 42 very heterogeneous molecules. Much redundancy and overlapping was found among total linear indices and most of the other structural indices presently in use in the QSPR/QSAR practice. On the contrary, the information carried by atom-type linear indices was strikingly different from that codified in most of the 229 0D-3D molecular descriptors used in this study. It is concluded that the local linear indices are an independent indices containing important structural information to be used in QSPR/QSAR and drug design studies. In this sense, atom, atom-type, and total linear indices were used for the prediction of pIC50 values for the cleavage process of a set of flavone derivatives inhibitors of HIV-1 integrase. Quantitative models found are significant from a statistical point of view (R of 0.965, 0.902, and 0.927, respectively) and permit a clear interpretation of the studied properties in terms of the structural features of molecules. A LOO cross-validation procedure revealed that the regression models had a fairly good predictability (q2 of 0.679, 0.543, and 0.721, respectively). The comparison with other approaches reveals good behavior of the method proposed. The approach described in this paper appears to be an excellent alternative or guides for discovery and optimization of new lead compounds.

Increased skills usage statistically mediates symptom reduction in self-guided internet-delivered cognitive-behavioural therapy for depression and anxiety: a randomised controlled trial.

PubMed

Terides, Matthew D; Dear, Blake F; Fogliati, Vincent J; Gandy, Milena; Karin, Eyal; Jones, Michael P; Titov, Nickolai

2018-01-01

Cognitive-behavioural therapy (CBT) is an effective treatment for clinical and subclinical symptoms of depression and general anxiety, and increases life satisfaction. Patients' usage of CBT skills is a core aspect of treatment but there is insufficient empirical evidence suggesting that skills usage behaviours are a mechanism of clinical change. This study investigated if an internet-delivered CBT (iCBT) intervention increased the frequency of CBT skills usage behaviours and if this statistically mediated reductions in symptoms and increased life satisfaction. A two-group randomised controlled trial was conducted comparing internet-delivered CBT (n = 65) with a waitlist control group (n = 75). Participants were individuals experiencing clinically significant symptoms of depression or general anxiety. Mixed-linear models analyses revealed that the treatment group reported a significantly higher frequency of skills usage, lower symptoms, and higher life satisfaction by the end of treatment compared with the control group. Results from bootstrapping mediation analyses revealed that the increased skills usage behaviours statistically mediated symptom reductions and increased life satisfaction. Although skills usage and symptom outcomes were assessed concurrently, these findings support the notion that iCBT increases the frequency of skills usage behaviours and suggest that this may be an important mechanism of change.

Estimation of Surface Air Temperature from MODIS 1km Resolution Land Surface Temperature Over Northern China

NASA Technical Reports Server (NTRS)

Shen, Suhung; Leptoukh, Gregory G.; Gerasimov, Irina

2010-01-01

Surface air temperature is a critical variable to describe the energy and water cycle of the Earth-atmosphere system and is a key input element for hydrology and land surface models. It is a very important variable in agricultural applications and climate change studies. This is a preliminary study to examine statistical relationships between ground meteorological station measured surface daily maximum/minimum air temperature and satellite remotely sensed land surface temperature from MODIS over the dry and semiarid regions of northern China. Studies were conducted for both MODIS-Terra and MODIS-Aqua by using year 2009 data. Results indicate that the relationships between surface air temperature and remotely sensed land surface temperature are statistically significant. The relationships between the maximum air temperature and daytime land surface temperature depends significantly on land surface types and vegetation index, but the minimum air temperature and nighttime land surface temperature has little dependence on the surface conditions. Based on linear regression relationship between surface air temperature and MODIS land surface temperature, surface maximum and minimum air temperatures are estimated from 1km MODIS land surface temperature under clear sky conditions. The statistical errors (sigma) of the estimated daily maximum (minimum) air temperature is about 3.8 C(3.7 C).

On the linearity of tracer bias around voids

NASA Astrophysics Data System (ADS)

Pollina, Giorgia; Hamaus, Nico; Dolag, Klaus; Weller, Jochen; Baldi, Marco; Moscardini, Lauro

2017-07-01

The large-scale structure of the Universe can be observed only via luminous tracers of the dark matter. However, the clustering statistics of tracers are biased and depend on various properties, such as their host-halo mass and assembly history. On very large scales, this tracer bias results in a constant offset in the clustering amplitude, known as linear bias. Towards smaller non-linear scales, this is no longer the case and tracer bias becomes a complicated function of scale and time. We focus on tracer bias centred on cosmic voids, I.e. depressions of the density field that spatially dominate the Universe. We consider three types of tracers: galaxies, galaxy clusters and active galactic nuclei, extracted from the hydrodynamical simulation Magneticum Pathfinder. In contrast to common clustering statistics that focus on auto-correlations of tracers, we find that void-tracer cross-correlations are successfully described by a linear bias relation. The tracer-density profile of voids can thus be related to their matter-density profile by a single number. We show that it coincides with the linear tracer bias extracted from the large-scale auto-correlation function and expectations from theory, if sufficiently large voids are considered. For smaller voids we observe a shift towards higher values. This has important consequences on cosmological parameter inference, as the problem of unknown tracer bias is alleviated up to a constant number. The smallest scales in existing data sets become accessible to simpler models, providing numerous modes of the density field that have been disregarded so far, but may help to further reduce statistical errors in constraining cosmology.

A Systematic Comparison of Linear Regression-Based Statistical Methods to Assess Exposome-Health Associations.

PubMed

Agier, Lydiane; Portengen, Lützen; Chadeau-Hyam, Marc; Basagaña, Xavier; Giorgis-Allemand, Lise; Siroux, Valérie; Robinson, Oliver; Vlaanderen, Jelle; González, Juan R; Nieuwenhuijsen, Mark J; Vineis, Paolo; Vrijheid, Martine; Slama, Rémy; Vermeulen, Roel

2016-12-01

The exposome constitutes a promising framework to improve understanding of the effects of environmental exposures on health by explicitly considering multiple testing and avoiding selective reporting. However, exposome studies are challenged by the simultaneous consideration of many correlated exposures. We compared the performances of linear regression-based statistical methods in assessing exposome-health associations. In a simulation study, we generated 237 exposure covariates with a realistic correlation structure and with a health outcome linearly related to 0 to 25 of these covariates. Statistical methods were compared primarily in terms of false discovery proportion (FDP) and sensitivity. On average over all simulation settings, the elastic net and sparse partial least-squares regression showed a sensitivity of 76% and an FDP of 44%; Graphical Unit Evolutionary Stochastic Search (GUESS) and the deletion/substitution/addition (DSA) algorithm revealed a sensitivity of 81% and an FDP of 34%. The environment-wide association study (EWAS) underperformed these methods in terms of FDP (average FDP, 86%) despite a higher sensitivity. Performances decreased considerably when assuming an exposome exposure matrix with high levels of correlation between covariates. Correlation between exposures is a challenge for exposome research, and the statistical methods investigated in this study were limited in their ability to efficiently differentiate true predictors from correlated covariates in a realistic exposome context. Although GUESS and DSA provided a marginally better balance between sensitivity and FDP, they did not outperform the other multivariate methods across all scenarios and properties examined, and computational complexity and flexibility should also be considered when choosing between these methods. Citation: Agier L, Portengen L, Chadeau-Hyam M, Basagaña X, Giorgis-Allemand L, Siroux V, Robinson O, Vlaanderen J, González JR, Nieuwenhuijsen MJ, Vineis P, Vrijheid M, Slama R, Vermeulen R. 2016. A systematic comparison of linear regression-based statistical methods to assess exposome-health associations. Environ Health Perspect 124:1848-1856; http://dx.doi.org/10.1289/EHP172.

GLOBAL SOLUTIONS TO FOLDED CONCAVE PENALIZED NONCONVEX LEARNING

PubMed Central

Liu, Hongcheng; Yao, Tao; Li, Runze

2015-01-01

This paper is concerned with solving nonconvex learning problems with folded concave penalty. Despite that their global solutions entail desirable statistical properties, there lack optimization techniques that guarantee global optimality in a general setting. In this paper, we show that a class of nonconvex learning problems are equivalent to general quadratic programs. This equivalence facilitates us in developing mixed integer linear programming reformulations, which admit finite algorithms that find a provably global optimal solution. We refer to this reformulation-based technique as the mixed integer programming-based global optimization (MIPGO). To our knowledge, this is the first global optimization scheme with a theoretical guarantee for folded concave penalized nonconvex learning with the SCAD penalty (Fan and Li, 2001) and the MCP penalty (Zhang, 2010). Numerical results indicate a significant outperformance of MIPGO over the state-of-the-art solution scheme, local linear approximation, and other alternative solution techniques in literature in terms of solution quality. PMID:27141126

Gross Morphometric Studies on the Tongue, Buccal Cavity and Hard Palate of the Fruit Bat (Eidolon helvum).

PubMed

Igado, O O; Omobowale, T O; Ajadi, R A; Nottidge, H O

2015-08-01

This study was designed to assess the gross morphometric studies of the tongue, hard palate and buccal cavity of the fruit bat (Eidolon helvum). Sixty bats of both sexes were used for this study. The tongue was excised, and the weight and various linear measurements were determined. Linear measurements were also determined on the hard palate. The gross distribution of the lingual papillae was observed to be the same in both sexes; values obtained for the weight and length of the tongue were higher in the females, although no statistically significant differences were observed (P > 0.05). The number of ridges on the hard palate displayed sexual dimorphism. Results obtained from this study may find application in the field of comparative and clinical anatomy of wildlife and also in feeding physiology. © 2014 Blackwell Verlag GmbH.

Establishing linear solvation energy relationships between VOCs and monolayer-protected gold nanoclusters using quartz crystal microbalance.

PubMed

Li, Chi-Lin; Lu, Chia-Jung

2009-08-15

Linear solvation energy relationships (LSERs) have been recognized as a useful model for investigating the chemical forces behind the partition coefficients between vapor molecules and absorbents. This study is the first to determine the solvation properties of monolayer-protected gold nanoclusters (MPCs) with different surface ligands. The ratio of partition coefficients/MPC density (K/rho) of 18 volatile organic compounds (VOCs) for four different MPCs obtained through quartz crystal microbalance (QCM) experiments were used for the LSER model calculations. LSER modeling results indicate that all MPC surfaces showed a statistically significant (p<0.05) preference to hydrogen-bond acidic molecules. Through dipole-dipole attraction, 4-methoxythiophenol-capped MPCs can also interact with polar organics (s=1.04). Showing a unique preference for the hydrogen bond basicity of vapors (b=1.11), 2-benzothiazolethiol-capped MPCs provide evidence of an intra-molecular, proton-shift mechanism on surface of nano-gold.

Prediction of clinical depression scores and detection of changes in whole-brain using resting-state functional MRI data with partial least squares regression

PubMed Central

Shimizu, Yu; Yoshimoto, Junichiro; Takamura, Masahiro; Okada, Go; Okamoto, Yasumasa; Yamawaki, Shigeto; Doya, Kenji

2017-01-01

In diagnostic applications of statistical machine learning methods to brain imaging data, common problems include data high-dimensionality and co-linearity, which often cause over-fitting and instability. To overcome these problems, we applied partial least squares (PLS) regression to resting-state functional magnetic resonance imaging (rs-fMRI) data, creating a low-dimensional representation that relates symptoms to brain activity and that predicts clinical measures. Our experimental results, based upon data from clinically depressed patients and healthy controls, demonstrated that PLS and its kernel variants provided significantly better prediction of clinical measures than ordinary linear regression. Subsequent classification using predicted clinical scores distinguished depressed patients from healthy controls with 80% accuracy. Moreover, loading vectors for latent variables enabled us to identify brain regions relevant to depression, including the default mode network, the right superior frontal gyrus, and the superior motor area. PMID:28700672

An exploratory analysis of treatment completion and client and organizational factors using hierarchical linear modeling.

PubMed

Woodward, Albert; Das, Abhik; Raskin, Ira E; Morgan-Lopez, Antonio A

2006-11-01

Data from the Alcohol and Drug Services Study (ADSS) are used to analyze the structure and operation of the substance abuse treatment industry in the United States. Published literature contains little systematic empirical analysis of the interaction between organizational characteristics and treatment outcomes. This paper addresses that deficit. It develops and tests a hierarchical linear model (HLM) to address questions about the empirical relationship between treatment inputs (industry costs, types and use of counseling and medical personnel, diagnosis mix, patient demographics, and the nature and level of services used in substance abuse treatment), and patient outcomes (retention and treatment completion rates). The paper adds to the literature by demonstrating a direct and statistically significant link between treatment completion and the organizational and staffing structure of the treatment setting. Related reimbursement issues, questions for future analysis, and limitations of the ADSS for this analysis are discussed.