Statistical methods for astronomical data with upper limits. II - Correlation and regression

NASA Technical Reports Server (NTRS)

Isobe, T.; Feigelson, E. D.; Nelson, P. I.

1986-01-01

Statistical methods for calculating correlations and regressions in bivariate censored data where the dependent variable can have upper or lower limits are presented. Cox's regression and the generalization of Kendall's rank correlation coefficient provide significant levels of correlations, and the EM algorithm, under the assumption of normally distributed errors, and its nonparametric analog using the Kaplan-Meier estimator, give estimates for the slope of a regression line. Monte Carlo simulations demonstrate that survival analysis is reliable in determining correlations between luminosities at different bands. Survival analysis is applied to CO emission in infrared galaxies, X-ray emission in radio galaxies, H-alpha emission in cooling cluster cores, and radio emission in Seyfert galaxies.

Evaluating Evidence for Conceptually Related Constructs Using Bivariate Correlations

ERIC Educational Resources Information Center

Swank, Jacqueline M.; Mullen, Patrick R.

2017-01-01

The article serves as a guide for researchers in developing evidence of validity using bivariate correlations, specifically construct validity. The authors outline the steps for calculating and interpreting bivariate correlations. Additionally, they provide an illustrative example and discuss the implications.

Detrended fluctuation analysis made flexible to detect range of cross-correlated fluctuations

NASA Astrophysics Data System (ADS)

Kwapień, Jarosław; Oświecimka, Paweł; DroŻdŻ, Stanisław

2015-11-01

The detrended cross-correlation coefficient ρDCCA has recently been proposed to quantify the strength of cross-correlations on different temporal scales in bivariate, nonstationary time series. It is based on the detrended cross-correlation and detrended fluctuation analyses (DCCA and DFA, respectively) and can be viewed as an analog of the Pearson coefficient in the case of the fluctuation analysis. The coefficient ρDCCA works well in many practical situations but by construction its applicability is limited to detection of whether two signals are generally cross-correlated, without the possibility to obtain information on the amplitude of fluctuations that are responsible for those cross-correlations. In order to introduce some related flexibility, here we propose an extension of ρDCCA that exploits the multifractal versions of DFA and DCCA: multifractal detrended fluctuation analysis and multifractal detrended cross-correlation analysis, respectively. The resulting new coefficient ρq not only is able to quantify the strength of correlations but also allows one to identify the range of detrended fluctuation amplitudes that are correlated in two signals under study. We show how the coefficient ρq works in practical situations by applying it to stochastic time series representing processes with long memory: autoregressive and multiplicative ones. Such processes are often used to model signals recorded from complex systems and complex physical phenomena like turbulence, so we are convinced that this new measure can successfully be applied in time-series analysis. In particular, we present an example of such application to highly complex empirical data from financial markets. The present formulation can straightforwardly be extended to multivariate data in terms of the q -dependent counterpart of the correlation matrices and then to the network representation.

Estimation of rank correlation for clustered data.

PubMed

Rosner, Bernard; Glynn, Robert J

2017-06-30

It is well known that the sample correlation coefficient (R xy ) is the maximum likelihood estimator of the Pearson correlation (ρ xy ) for independent and identically distributed (i.i.d.) bivariate normal data. However, this is not true for ophthalmologic data where X (e.g., visual acuity) and Y (e.g., visual field) are available for each eye and there is positive intraclass correlation for both X and Y in fellow eyes. In this paper, we provide a regression-based approach for obtaining the maximum likelihood estimator of ρ xy for clustered data, which can be implemented using standard mixed effects model software. This method is also extended to allow for estimation of partial correlation by controlling both X and Y for a vector U_ of other covariates. In addition, these methods can be extended to allow for estimation of rank correlation for clustered data by (i) converting ranks of both X and Y to the probit scale, (ii) estimating the Pearson correlation between probit scores for X and Y, and (iii) using the relationship between Pearson and rank correlation for bivariate normally distributed data. The validity of the methods in finite-sized samples is supported by simulation studies. Finally, two examples from ophthalmology and analgesic abuse are used to illustrate the methods. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Price-volume multifractal analysis of the Moroccan stock market

NASA Astrophysics Data System (ADS)

El Alaoui, Marwane

2017-11-01

In this paper, we analyzed price-volume multifractal cross-correlations of Moroccan Stock Exchange. We chose the period from January 1st 2000 to January 20th 2017 to investigate the multifractal behavior of price change and volume change series. Then, we used multifractal detrended cross-correlations analysis method (MF-DCCA) and multifractal detrended fluctuation analysis (MF-DFA) to analyze the series. We computed bivariate generalized Hurst exponent, Rényi exponent and spectrum of singularity for each pair of indices to measure quantitatively cross-correlations. Furthermore, we used detrended cross-correlations coefficient (DCCA) and cross-correlation test (Q(m)) to analyze cross-correlation quantitatively and qualitatively. By analyzing results, we found existence of price-volume multifractal cross-correlations. The spectrum width has a strong multifractal cross-correlation. We remarked that volume change series is anti-persistent when we analyzed the generalized Hurst exponent for all moments q. The cross-correlation test showed the presence of a significant cross-correlation. However, DCCA coefficient had a small positive value, which means that the level of correlation is not very significant. Finally, we analyzed sources of multifractality and their degree of contribution in the series.

Lead exposure and the 2010 achievement test scores of children in New York counties

PubMed Central

2012-01-01

Background Lead is toxic to cognitive and behavioral functioning in children even at levels well below those producing physical symptoms. Continuing efforts in the U.S. since about the 1970s to reduce lead exposure in children have dramatically reduced the incidence of elevated blood lead levels (with elevated levels defined by the current U.S. Centers for Disease Control threshold of 10 μg/dl). The current study examines how much lead toxicity continues to impair the academic achievement of children of New York State, using 2010 test data. Methods This study relies on three sets of data published for the 57 New York counties outside New York City: school achievement data from the New York State Department of Education, data on incidence of elevated blood lead levels from the New York State Department of Health, and data on income from the U.S. Census Bureau. We studied third grade and eighth grade test scores in English Language Arts and mathematics. Using the county as the unit of analysis, we computed bivariate correlations and regression coefficients, with percent of children achieving at the lowest reported level as the dependent variable and the percent of preschoolers in the county with elevated blood lead levels as the independent variable. Then we repeated those analyses using partial correlations to control for possible confounding effects of family income, and using multiple regressions with income included. Results The bivariate correlations between incidence of elevated lead and number of children in the lowest achievement group ranged between 0.38 and 0.47. The partial correlations ranged from 0.29 to 0.40. The regression coefficients, both bivariate and partial (both estimating the increase in percent of children in the lowest achievement group for every percent increase in the children with elevated blood lead levels), ranged from 0.52 to 1.31. All regression coefficients, when rounded to the nearest integer, were approximately 1. Thus, when the percent of children showing elevated lead increases by one percent, the percent of children in the lowest achievement group, according to the regression equations generated, also increases by about one percent. All associations were significant at the 0.05 level. Conclusion Despite public health advances, and despite the imprecision of measures, an association between the incidence of elevated blood lead and achievement in New York counties is still apparent, not attributable to confounding by income. Efforts to reduce lead exposure should persist with vigor. PMID:22269775

Multifractal detrended cross-correlation analysis in the MENA area

NASA Astrophysics Data System (ADS)

El Alaoui, Marwane; Benbachir, Saâd

2013-12-01

In this paper, we investigated multifractal cross-correlations qualitatively and quantitatively using a cross-correlation test and the Multifractal detrended cross-correlation analysis method (MF-DCCA) for markets in the MENA area. We used cross-correlation coefficients to measure the level of this correlation. The analysis concerns four stock market indices of Morocco, Tunisia, Egypt and Jordan. The countries chosen are signatory of the Agadir agreement concerning the establishment of a free trade area comprising Arab Mediterranean countries. We computed the bivariate generalized Hurst exponent, Rényi exponent and spectrum of singularity for each pair of indices to measure quantitatively the cross-correlations. By analyzing the results, we found the existence of multifractal cross-correlations between all of these markets. We compared the spectrum width of these indices; we also found which pair of indices has a strong multifractal cross-correlation.

Spanking, corporal punishment and negative long-term outcomes: a meta-analytic review of longitudinal studies.

PubMed

Ferguson, Christopher J

2013-02-01

Social scientists continue to debate the impact of spanking and corporal punishment (CP) on negative child outcomes including externalizing and internalizing behavior problems and cognitive performance. Previous meta-analytic reviews have mixed long- and short-term studies and relied on bivariate r, which may inflate effect sizes. The current meta-analysis focused on longitudinal studies, and compared effects using bivariate r and better controlled partial r coefficients controlling for time-1 outcome variables. Consistent with previous findings, results based on bivariate r found small but non-trivial long-term relationships between spanking/CP use and negative outcomes. Spanking and CP correlated .14 and .18 respectively with externalizing problems, .12 and .21 with internalizing problems and -.09 and -.18 with cognitive performance. However, when better controlled partial r coefficients (pr) were examined, results were statistically significant but trivial (at or below pr = .10) for externalizing (.07 for spanking, .08 for CP) and internalizing behaviors (.10 for spanking, insufficient studies for CP) and near the threshold of trivial for cognitive performance (-.11 for CP, insufficient studies for spanking). It is concluded that the impact of spanking and CP on the negative outcomes evaluated here (externalizing, internalizing behaviors and low cognitive performance) are minimal. It is advised that psychologists take a more nuanced approach in discussing the effects of spanking/CP with the general public, consistent with the size as well as the significance of their longitudinal associations with adverse outcomes.

Bayesian hierarchical models for cost-effectiveness analyses that use data from cluster randomized trials.

PubMed

Grieve, Richard; Nixon, Richard; Thompson, Simon G

2010-01-01

Cost-effectiveness analyses (CEA) may be undertaken alongside cluster randomized trials (CRTs) where randomization is at the level of the cluster (for example, the hospital or primary care provider) rather than the individual. Costs (and outcomes) within clusters may be correlated so that the assumption made by standard bivariate regression models, that observations are independent, is incorrect. This study develops a flexible modeling framework to acknowledge the clustering in CEA that use CRTs. The authors extend previous Bayesian bivariate models for CEA of multicenter trials to recognize the specific form of clustering in CRTs. They develop new Bayesian hierarchical models (BHMs) that allow mean costs and outcomes, and also variances, to differ across clusters. They illustrate how each model can be applied using data from a large (1732 cases, 70 primary care providers) CRT evaluating alternative interventions for reducing postnatal depression. The analyses compare cost-effectiveness estimates from BHMs with standard bivariate regression models that ignore the data hierarchy. The BHMs show high levels of cost heterogeneity across clusters (intracluster correlation coefficient, 0.17). Compared with standard regression models, the BHMs yield substantially increased uncertainty surrounding the cost-effectiveness estimates, and altered point estimates. The authors conclude that ignoring clustering can lead to incorrect inferences. The BHMs that they present offer a flexible modeling framework that can be applied more generally to CEA that use CRTs.

Measuring agreement of multivariate discrete survival times using a modified weighted kappa coefficient.

PubMed

Guo, Ying; Manatunga, Amita K

2009-03-01

Assessing agreement is often of interest in clinical studies to evaluate the similarity of measurements produced by different raters or methods on the same subjects. We present a modified weighted kappa coefficient to measure agreement between bivariate discrete survival times. The proposed kappa coefficient accommodates censoring by redistributing the mass of censored observations within the grid where the unobserved events may potentially happen. A generalized modified weighted kappa is proposed for multivariate discrete survival times. We estimate the modified kappa coefficients nonparametrically through a multivariate survival function estimator. The asymptotic properties of the kappa estimators are established and the performance of the estimators are examined through simulation studies of bivariate and trivariate survival times. We illustrate the application of the modified kappa coefficient in the presence of censored observations with data from a prostate cancer study.

Anthropometric Survey of US Army Personnel (1988): Correlation Coefficients and Regression Equations. Part 4. Bivariate Regression Tables

DTIC Science & Technology

1990-05-01

THUMBBR THUMB BREADTH NO. VARIABLE CONSTANT REGRESS. COEF. ST.ERROR ADJUQTED (.ERR OF ESTIMATE E4 58 HANDBRTH 7.623 0.183 ( 0.006) 1.124 .319 59 HANDCIRC...945, 956, 965 TRAGION TO TOP OF HEAD (TRAGT, 255) 39,51, 718, 851, 899, 945, 956, 965 Trapezius Post 23 Trochanter 23 TROCHArNTERION HEIGHT (TROQINT...THGHCLR, 105) 33, 40, 673, M08 881,927, 955, 964 Thigh Poia 23 THUMB BREADTH (THUMBBR, 106) 34, 49, 674,88 882,94955, 964 ThumlAip 23 THUMBTIP REACH

In vitro burn model illustrating heat conduction patterns using compressed thermal papers.

PubMed

Lee, Jun Yong; Jung, Sung-No; Kwon, Ho

2015-01-01

To date, heat conduction from heat sources to tissue has been estimated by complex mathematical modeling. In the present study, we developed an intuitive in vitro skin burn model that illustrates heat conduction patterns inside the skin. This was composed of tightly compressed thermal papers with compression frames. Heat flow through the model left a trace by changing the color of thermal papers. These were digitized and three-dimensionally reconstituted to reproduce the heat conduction patterns in the skin. For standardization, we validated K91HG-CE thermal paper using a printout test and bivariate correlation analysis. We measured the papers' physical properties and calculated the estimated depth of heat conduction using Fourier's equation. Through contact burns of 5, 10, 15, 20, and 30 seconds on porcine skin and our burn model using a heated brass comb, and comparing the burn wound and heat conduction trace, we validated our model. The heat conduction pattern correlation analysis (intraclass correlation coefficient: 0.846, p < 0.001) and the heat conduction depth correlation analysis (intraclass correlation coefficient: 0.93, p < 0.001) showed statistically significant high correlations between the porcine burn wound and our model. Our model showed good correlation with porcine skin burn injury and replicated its heat conduction patterns. © 2014 by the Wound Healing Society.

To Identify the Important Soil Properties Affecting Dinoseb Adsorption with Statistical Analysis

PubMed Central

Guan, Yiqing; Wei, Jianhui; Zhang, Danrong; Zu, Mingjuan; Zhang, Liru

2013-01-01

Investigating the influences of soil characteristic factors on dinoseb adsorption parameter with different statistical methods would be valuable to explicitly figure out the extent of these influences. The correlation coefficients and the direct, indirect effects of soil characteristic factors on dinoseb adsorption parameter were analyzed through bivariate correlation analysis, and path analysis. With stepwise regression analysis the factors which had little influence on the adsorption parameter were excluded. Results indicate that pH and CEC had moderate relationship and lower direct effect on dinoseb adsorption parameter due to the multicollinearity with other soil factors, and organic carbon and clay contents were found to be the most significant soil factors which affect the dinoseb adsorption process. A regression is thereby set up to explore the relationship between the dinoseb adsorption parameter and the two soil factors: the soil organic carbon and clay contents. A 92% of the variation of dinoseb sorption coefficient could be attributed to the variation of the soil organic carbon and clay contents. PMID:23737715

Bivariate drought frequency analysis using the copula method

NASA Astrophysics Data System (ADS)

Mirabbasi, Rasoul; Fakheri-Fard, Ahmad; Dinpashoh, Yagob

2012-04-01

Droughts are major natural hazards with significant environmental and economic impacts. In this study, two-dimensional copulas were applied to the analysis of the meteorological drought characteristics of the Sharafkhaneh gauge station, located in the northwest of Iran. Two major drought characteristics, duration and severity, as defined by the standardized precipitation index, were abstracted from observed drought events. Since drought duration and severity exhibited a significant correlation and since they were modeled using different distributions, copulas were used to construct the joint distribution function of the drought characteristics. The parameter of copulas was estimated using the method of the Inference Function for Margins. Several copulas were tested in order to determine the best data fit. According to the error analysis and the tail dependence coefficient, the Galambos copula provided the best fit for the observed drought data. Some bivariate probabilistic properties of droughts, based on the derived copula-based joint distribution, were also investigated. These probabilistic properties can provide useful information for water resource planning and management.

Identifying and Validating Selection Tools for Predicting Officer Performance and Retention

DTIC Science & Technology

2017-05-01

Performance composite. Findings: Simple bivariate correlations indicated that the RBI Fitness Motivation scale was the strongest predictor of...Scored Job Knowledge Tests (JKTs) ............................................................ 14 Self-Report: Career History Survey (CHS...36 Bivariate Correlations

Are Self-Reported Medication Allergies Associated With Worse Hip Outcome Scores Prior to Hip Arthroscopy?

PubMed

Sochacki, Kyle R; Jack, Robert A; Bekhradi, Arya; Delgado, Domenica; McCulloch, Patrick C; Harris, Joshua D

2018-06-01

To determine if there are significant differences in preoperative patient-reported outcome (PRO) scores in patients with and without self-reported medication allergies undergoing hip arthroscopy. Consecutive subjects undergoing hip arthroscopy for femoroacetabular impingement (FAI) syndrome by a single surgeon were retrospectively reviewed. PROs were collected within 6 weeks of the date of surgery. PROs included International Hip Outcome Tool (iHOT-12), Hip Outcome Score (HOS), and Short-Form (SF-12) scores. Allergies to medications were self-reported preoperatively within 6 weeks of the date of surgery. Patient demographics were recorded. Bivariate correlations and multivariate regression models were calculated to identify associations with baseline hip outcome scores. Two hundred twelve subjects were analyzed (56% female, mean age 35.1 ± 13.2 years). Seventy-two subjects (34%) self-reported allergies (range 1-10; 41 subjects had 1 allergy; 14 subjects had 2; 8 subjects had 3; 2 subjects had 4; 7 subjects had 5 or more). The most commonly reported allergies included penicillin (18), sulfa (13), and codeine (11). Female gender was significantly correlated with number of allergies (Pearson correlation coefficient, 0.188; P < .001). SF-12 Mental Component Score (MCS) was significantly correlated with HOS-ADL (Pearson correlation coefficient, 0.389; P < .001), HOS-SSS (Pearson correlation coefficient, 0.251; P < .001), and iHOT-12 (Pearson correlation coefficient, 0.385; P < .001). There was no significant correlation between number of allergies and all hip PROs. In all multivariate models, the SF-12 MCS had the strongest association with HOS-ADL, HOS-SSS, and iHOT-12 (P < .001 for all). Allergies were not significantly associated with any hip PROs. In patients undergoing hip arthroscopy for FAI syndrome, self-reported medication allergies are not significantly associated with preoperative patient-reported hip outcome scores. Level III, retrospective comparative case series. Copyright © 2018 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.

Statistical Development of Flood Frequency and Magnitude Equations for the Cosumnes and Mokelumne River Drainage Basins, Sierra Nevada, California

NASA Astrophysics Data System (ADS)

Burns, R. G.; Meyer, R. W.; Cornwell, K.

2003-12-01

In-basin statistical relations allow for development of regional flood frequency and magnitude equations in the Cosumnes River and Mokelumne River drainage basins. Current equations were derived from data collected through 1975, and do not reflect newer data with some significant flooding. Physical basin characteristics (area, mean basin elevation, slope of longest reach, and mean annual precipitation) were correlated against predicted flood discharges for each of the 5, 10, 25, 50, 100, 200, and 500-year recurrence intervals in a multivariate analysis. Predicted maximum instantaneous flood discharges were determined using the PEAKFQ program with default settings, for 24 stream gages within the study area presumed not affected by flow management practices. For numerical comparisons, GIS-based methods using Spatial Analyst and the Arc Hydro Tools extension were applied to derive physical basin characteristics as predictor variables from a 30m digital elevation model (DEM) and a mean annual precipitation raster (PRISM). In a bivariate analysis, examination of Pearson correlation coefficients, F-statistic, and t & p thresholds show good correlation between area and flood discharges. Similar analyses show poor correlation for mean basin elevation, slope and precipitation, with flood discharge. Bivariate analysis suggests slope may not be an appropriate predictor term for use in the multivariate analysis. Precipitation and elevation correlate very well, demonstrating possible orographic effects. From the multivariate analysis, less than 6% of the variability in the correlation is not explained for flood recurrences up to 25 years. Longer term predictions up to 500 years accrue greater uncertainty with as much as 15% of the variability in the correlation left unexplained.

Predicting the Size of Sunspot Cycle 24 on the Basis of Single- and Bi-Variate Geomagnetic Precursor Methods

NASA Technical Reports Server (NTRS)

Wilson, Robert M.; Hathaway, David H.

2009-01-01

Examined are single- and bi-variate geomagnetic precursors for predicting the maximum amplitude (RM) of a sunspot cycle several years in advance. The best single-variate fit is one based on the average of the ap index 36 mo prior to cycle minimum occurrence (E(Rm)), having a coefficient of correlation (r) equal to 0.97 and a standard error of estimate (se) equal to 9.3. Presuming cycle 24 not to be a statistical outlier and its minimum in March 2008, the fit suggests cycle 24 s RM to be about 69 +/- 20 (the 90% prediction interval). The weighted mean prediction of 11 statistically important single-variate fits is 116 +/- 34. The best bi-variate fit is one based on the maximum and minimum values of the 12-mma of the ap index; i.e., APM# and APm*, where # means the value post-E(RM) for the preceding cycle and * means the value in the vicinity of cycle minimum, having r = 0.98 and se = 8.2. It predicts cycle 24 s RM to be about 92 +/- 27. The weighted mean prediction of 22 statistically important bi-variate fits is 112 32. Thus, cycle 24's RM is expected to lie somewhere within the range of about 82 to 144. Also examined are the late-cycle 23 behaviors of geomagnetic indices and solar wind velocity in comparison to the mean behaviors of cycles 2023 and the geomagnetic indices of cycle 14 (RM = 64.2), the weakest sunspot cycle of the modern era.

Structure and Function of Task-Oriented Social Networks

DTIC Science & Technology

2015-01-05

sizes can cause instability in correlation measures. A recently developed bivariate measure of  association, Maximal Information Coefficient ( MIC ...promises to simultaneously discover if two  variables have: a) any association, b) a functional relationship, and c) a non­linear  relationship. The  MIC ...problems with the values reported by standard and rank  correlation measures. In our first study [15], we illustrated the use of  MIC  using a variety of

Optical Coherence Tomography Noise Reduction Using Anisotropic Local Bivariate Gaussian Mixture Prior in 3D Complex Wavelet Domain.

PubMed

Rabbani, Hossein; Sonka, Milan; Abramoff, Michael D

2013-01-01

In this paper, MMSE estimator is employed for noise-free 3D OCT data recovery in 3D complex wavelet domain. Since the proposed distribution for noise-free data plays a key role in the performance of MMSE estimator, a priori distribution for the pdf of noise-free 3D complex wavelet coefficients is proposed which is able to model the main statistical properties of wavelets. We model the coefficients with a mixture of two bivariate Gaussian pdfs with local parameters which are able to capture the heavy-tailed property and inter- and intrascale dependencies of coefficients. In addition, based on the special structure of OCT images, we use an anisotropic windowing procedure for local parameters estimation that results in visual quality improvement. On this base, several OCT despeckling algorithms are obtained based on using Gaussian/two-sided Rayleigh noise distribution and homomorphic/nonhomomorphic model. In order to evaluate the performance of the proposed algorithm, we use 156 selected ROIs from 650 × 512 × 128 OCT dataset in the presence of wet AMD pathology. Our simulations show that the best MMSE estimator using local bivariate mixture prior is for the nonhomomorphic model in the presence of Gaussian noise which results in an improvement of 7.8 ± 1.7 in CNR.

Test-retest reliability of the safe driving behavior measure for community-dwelling elderly drivers.

PubMed

Song, Chiang-Soon; Lee, Joo-Hyun; Han, Sang-Woo

2016-06-01

[Purpose] The Safe Driving Behavior Measure (SDBM) is a self-report measurement tools that assesses the safe-driving behaviors of the elderly. The purpose of this study was to evaluate the test-retest reliability of the SDBM among community-dwelling elderly drivers. [Subjects and Methods] A total of sixty-one community-dwelling elderly were enrolled to investigate the reliability of the SDBM. The SDBM was assessed in two sessions that were conducted three days apart in a quiet and well-organized assessment room. That test-retest reliability of overall scores and three domain scores of the SDBM were statistically evaluated using intraclass correlation coefficients [ICC (2.1)]. Pearson correlation coefficients were used to quantify bivariate associations among the three domains of the SDBM. [Results] The SDBM demonstrated excellent rest-retest reliability for community-dwelling elderly drivers. The Cronbach alpha coefficients of the three domains of person-vehicle (0.979), person-environment (0.944), and person-vehicle-environment (0.971) of the SDBM indicate high internal consistency. [Conclusion] The results of this study suggest that the SDBM is a reliable measure for evaluating the safe- driving of automobiles by community-dwelling elderly, and is adequate for detecting changes in scores in clinical settings.

Multifractal detrended cross-correlation analysis on gold, crude oil and foreign exchange rate time series

NASA Astrophysics Data System (ADS)

Pal, Mayukha; Madhusudana Rao, P.; Manimaran, P.

2014-12-01

We apply the recently developed multifractal detrended cross-correlation analysis method to investigate the cross-correlation behavior and fractal nature between two non-stationary time series. We analyze the daily return price of gold, West Texas Intermediate and Brent crude oil, foreign exchange rate data, over a period of 18 years. The cross correlation has been measured from the Hurst scaling exponents and the singularity spectrum quantitatively. From the results, the existence of multifractal cross-correlation between all of these time series is found. We also found that the cross correlation between gold and oil prices possess uncorrelated behavior and the remaining bivariate time series possess persistent behavior. It was observed for five bivariate series that the cross-correlation exponents are less than the calculated average generalized Hurst exponents (GHE) for q<0 and greater than GHE when q>0 and for one bivariate series the cross-correlation exponent is greater than GHE for all q values.

Sequential deconvolution from wave-front sensing using bivariate simplex splines

NASA Astrophysics Data System (ADS)

Guo, Shiping; Zhang, Rongzhi; Li, Jisheng; Zou, Jianhua; Xu, Rong; Liu, Changhai

2015-05-01

Deconvolution from wave-front sensing (DWFS) is an imaging compensation technique for turbulence degraded images based on simultaneous recording of short exposure images and wave-front sensor data. This paper employs the multivariate splines method for the sequential DWFS: a bivariate simplex splines based average slopes measurement model is built firstly for Shack-Hartmann wave-front sensor; next, a well-conditioned least squares estimator for the spline coefficients is constructed using multiple Shack-Hartmann measurements; then, the distorted wave-front is uniquely determined by the estimated spline coefficients; the object image is finally obtained by non-blind deconvolution processing. Simulated experiments in different turbulence strength show that our method performs superior image restoration results and noise rejection capability especially when extracting the multidirectional phase derivatives.

A survey of variable selection methods in two Chinese epidemiology journals

PubMed Central

2010-01-01

Background Although much has been written on developing better procedures for variable selection, there is little research on how it is practiced in actual studies. This review surveys the variable selection methods reported in two high-ranking Chinese epidemiology journals. Methods Articles published in 2004, 2006, and 2008 in the Chinese Journal of Epidemiology and the Chinese Journal of Preventive Medicine were reviewed. Five categories of methods were identified whereby variables were selected using: A - bivariate analyses; B - multivariable analysis; e.g. stepwise or individual significance testing of model coefficients; C - first bivariate analyses, followed by multivariable analysis; D - bivariate analyses or multivariable analysis; and E - other criteria like prior knowledge or personal judgment. Results Among the 287 articles that reported using variable selection methods, 6%, 26%, 30%, 21%, and 17% were in categories A through E, respectively. One hundred sixty-three studies selected variables using bivariate analyses, 80% (130/163) via multiple significance testing at the 5% alpha-level. Of the 219 multivariable analyses, 97 (44%) used stepwise procedures, 89 (41%) tested individual regression coefficients, but 33 (15%) did not mention how variables were selected. Sixty percent (58/97) of the stepwise routines also did not specify the algorithm and/or significance levels. Conclusions The variable selection methods reported in the two journals were limited in variety, and details were often missing. Many studies still relied on problematic techniques like stepwise procedures and/or multiple testing of bivariate associations at the 0.05 alpha-level. These deficiencies should be rectified to safeguard the scientific validity of articles published in Chinese epidemiology journals. PMID:20920252

Optical Coherence Tomography Noise Reduction Using Anisotropic Local Bivariate Gaussian Mixture Prior in 3D Complex Wavelet Domain

PubMed Central

Sonka, Milan; Abramoff, Michael D.

2013-01-01

In this paper, MMSE estimator is employed for noise-free 3D OCT data recovery in 3D complex wavelet domain. Since the proposed distribution for noise-free data plays a key role in the performance of MMSE estimator, a priori distribution for the pdf of noise-free 3D complex wavelet coefficients is proposed which is able to model the main statistical properties of wavelets. We model the coefficients with a mixture of two bivariate Gaussian pdfs with local parameters which are able to capture the heavy-tailed property and inter- and intrascale dependencies of coefficients. In addition, based on the special structure of OCT images, we use an anisotropic windowing procedure for local parameters estimation that results in visual quality improvement. On this base, several OCT despeckling algorithms are obtained based on using Gaussian/two-sided Rayleigh noise distribution and homomorphic/nonhomomorphic model. In order to evaluate the performance of the proposed algorithm, we use 156 selected ROIs from 650 × 512 × 128 OCT dataset in the presence of wet AMD pathology. Our simulations show that the best MMSE estimator using local bivariate mixture prior is for the nonhomomorphic model in the presence of Gaussian noise which results in an improvement of 7.8 ± 1.7 in CNR. PMID:24222760

Psychometric Testing of the Greek Version of the Clinical Learning Environment-Teacher (CLES+T).

PubMed

Papastavrou, Evridiki; Dimitriadou, Maria; Tsangari, Haritini

2015-09-01

Clinical practice is an important part of nursing education, and robust instruments are required to evaluate the effectiveness of the hospital setting as a learning environment. The study aim is the psychometric test of the Clinical Learning Environment+Teacher (CLES+T) scale-Greek version. 463 students practicing in acute care hospitals participated in the study. The reliability of the instrument was estimated with Cronbach's alpha coefficients. The construct validity was evaluated using exploratory factor analysis (EFA) with Varimax rotation. Convergent validity was examined by measuring the bivariate correlations between the scale/subscales. Content, validity and semantic equivalence were examined through reviews by a panel of experts. The total scale showed high internal consistency (α=0.95). EFA was identical to the original scale, had eigen values larger than one and explained a total of 67.4% of the variance. The factor with the highest eigen value and the largest percentage of variance explained was "supervisory relationship", with an original eigenvalue of 13.1 (6.8 after Varimax rotation) and an explanation of around 38% of the variance (or 20% after rotation). Convergent validity was examined by measuring the bivariate correlations between the scale and a question that measured the general satisfaction. The Greek version of the CLES+T is a valid and reliable instrument that can be used to examine students' perceptions of the clinical learning environment.

A comparison of bivariate, multivariate random-effects, and Poisson correlated gamma-frailty models to meta-analyze individual patient data of ordinal scale diagnostic tests.

PubMed

Simoneau, Gabrielle; Levis, Brooke; Cuijpers, Pim; Ioannidis, John P A; Patten, Scott B; Shrier, Ian; Bombardier, Charles H; de Lima Osório, Flavia; Fann, Jesse R; Gjerdingen, Dwenda; Lamers, Femke; Lotrakul, Manote; Löwe, Bernd; Shaaban, Juwita; Stafford, Lesley; van Weert, Henk C P M; Whooley, Mary A; Wittkampf, Karin A; Yeung, Albert S; Thombs, Brett D; Benedetti, Andrea

2017-11-01

Individual patient data (IPD) meta-analyses are increasingly common in the literature. In the context of estimating the diagnostic accuracy of ordinal or semi-continuous scale tests, sensitivity and specificity are often reported for a given threshold or a small set of thresholds, and a meta-analysis is conducted via a bivariate approach to account for their correlation. When IPD are available, sensitivity and specificity can be pooled for every possible threshold. Our objective was to compare the bivariate approach, which can be applied separately at every threshold, to two multivariate methods: the ordinal multivariate random-effects model and the Poisson correlated gamma-frailty model. Our comparison was empirical, using IPD from 13 studies that evaluated the diagnostic accuracy of the 9-item Patient Health Questionnaire depression screening tool, and included simulations. The empirical comparison showed that the implementation of the two multivariate methods is more laborious in terms of computational time and sensitivity to user-supplied values compared to the bivariate approach. Simulations showed that ignoring the within-study correlation of sensitivity and specificity across thresholds did not worsen inferences with the bivariate approach compared to the Poisson model. The ordinal approach was not suitable for simulations because the model was highly sensitive to user-supplied starting values. We tentatively recommend the bivariate approach rather than more complex multivariate methods for IPD diagnostic accuracy meta-analyses of ordinal scale tests, although the limited type of diagnostic data considered in the simulation study restricts the generalization of our findings. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Sexual Harassment Retaliation Climate DEOCS 4.1 Construct Validity Summary

DTIC Science & Technology

2017-08-01

exploratory factor analysis, and bivariate correlations (sample 1) 2) To determine the factor structure of the remaining (final) questions via...statistics, reliability analysis, exploratory factor analysis, and bivariate correlations of the prospective Sexual Harassment Retaliation Climate...reported by the survey requester). For information regarding the composition of sample, refer to Table 1. Table 1. Sample 1 Demographics n

A bivariate model for analyzing recurrent multi-type automobile failures

NASA Astrophysics Data System (ADS)

Sunethra, A. A.; Sooriyarachchi, M. R.

2017-09-01

The failure mechanism in an automobile can be defined as a system of multi-type recurrent failures where failures can occur due to various multi-type failure modes and these failures are repetitive such that more than one failure can occur from each failure mode. In analysing such automobile failures, both the time and type of the failure serve as response variables. However, these two response variables are highly correlated with each other since the timing of failures has an association with the mode of the failure. When there are more than one correlated response variables, the fitting of a multivariate model is more preferable than separate univariate models. Therefore, a bivariate model of time and type of failure becomes appealing for such automobile failure data. When there are multiple failure observations pertaining to a single automobile, such data cannot be treated as independent data because failure instances of a single automobile are correlated with each other while failures among different automobiles can be treated as independent. Therefore, this study proposes a bivariate model consisting time and type of failure as responses adjusted for correlated data. The proposed model was formulated following the approaches of shared parameter models and random effects models for joining the responses and for representing the correlated data respectively. The proposed model is applied to a sample of automobile failures with three types of failure modes and up to five failure recurrences. The parametric distributions that were suitable for the two responses of time to failure and type of failure were Weibull distribution and multinomial distribution respectively. The proposed bivariate model was programmed in SAS Procedure Proc NLMIXED by user programming appropriate likelihood functions. The performance of the bivariate model was compared with separate univariate models fitted for the two responses and it was identified that better performance is secured by the bivariate model. The proposed model can be used to determine the time and type of failure that would occur in the automobiles considered here.

Gender empowerment and female-to-male smoking prevalence ratios

PubMed Central

Fong, Geoffrey T

2011-01-01

Abstract Objective To determine whether in countries with high gender empowerment the female-to-male smoking prevalence ratio is also higher. Methods Bivariate and multiple regression analyses were performed to explore the relation between the United Nations Development Programme’s gender empowerment measure (GEM) and the female-to-male smoking prevalence ratio (calculated from the 2008 WHO global tobacco control report). Because a country’s progression through the various stages of the tobacco epidemic and its gender smoking ratio (GSR) are thought to be influenced by its level of development, we explored this correlation as well, with economic development defined in terms of gross national income (GNI) per capita and income inequality (Gini coefficient). Findings The GSR was significantly and positively correlated with the GEM (r = 0.680; P < 0.001). In addition, the GEM was the strongest predictor of the GSR (β, adjusted: 0.47; P < 0.0001) after controlling for GNI per capita and for Gini coefficient. Conclusion Whether progress towards gender empowerment can take place without a corresponding increase in smoking among women remains to be seen. Strong tobacco control measures are needed in countries where women are being increasingly empowered. PMID:21379415

Statistical modeling of space shuttle environmental data

NASA Technical Reports Server (NTRS)

Tubbs, J. D.; Brewer, D. W.

1983-01-01

Statistical models which use a class of bivariate gamma distribution are examined. Topics discussed include: (1) the ratio of positively correlated gamma varieties; (2) a method to determine if unequal shape parameters are necessary in bivariate gamma distribution; (3) differential equations for modal location of a family of bivariate gamma distribution; and (4) analysis of some wind gust data using the analytical results developed for modeling application.

An integrated, ethically driven environmental model of clinical decision making in emergency settings.

PubMed

Wolf, Lisa

2013-02-01

To explore the relationship between multiple variables within a model of critical thinking and moral reasoning. A quantitative descriptive correlational design using a purposive sample of 200 emergency nurses. Measured variables were accuracy in clinical decision-making, moral reasoning, perceived care environment, and demographics. Analysis was by bivariate correlation using Pearson's product-moment correlation coefficients, chi square and multiple linear regression analysis. The elements as identified in the integrated ethically-driven environmental model of clinical decision-making (IEDEM-CD) corrected depict moral reasoning and environment of care as factors significantly affecting accuracy in decision-making. The integrated, ethically driven environmental model of clinical decision making is a framework useful for predicting clinical decision making accuracy for emergency nurses in practice, with further implications in education, research and policy. A diagnostic and therapeutic framework for identifying and remediating individual and environmental challenges to accurate clinical decision making. © 2012, The Author. International Journal of Nursing Knowledge © 2012, NANDA International.

Social acceptance among tuberculosis patients at Puskesmas Amplas Medan, Indonesia

NASA Astrophysics Data System (ADS)

Eyanoer, P. C.

2018-03-01

Social acceptance is a confession, compilation, and appreciation for an individual which come from other individual or social groups in their entirety which makes individual feels safe, comfortable, and their existence is appreciated. A cross-sectional study consisted of 42 pulmonary TB patients registered at Puskesmas Amplas was done to analyze their social acceptance in the society. Data was collected by direct interview using structured questionnaire. The result showed that majority had either high and very high social acceptance with 45.20% and 31.0% respectively with high family support and high self-confidence (73.8%). Bivariate analysis showed a significant association between family support and self confidence with social acceptance (p value<0.05). The correlation coefficient (r) of self confidenceis 0.629 while family support were is 0.455 (p-value<0.05). This study concludes that both family support and self-confidence have a significant correlation with social acceptance.

Multifractal detrending moving-average cross-correlation analysis

NASA Astrophysics Data System (ADS)

Jiang, Zhi-Qiang; Zhou, Wei-Xing

2011-07-01

There are a number of situations in which several signals are simultaneously recorded in complex systems, which exhibit long-term power-law cross correlations. The multifractal detrended cross-correlation analysis (MFDCCA) approaches can be used to quantify such cross correlations, such as the MFDCCA based on the detrended fluctuation analysis (MFXDFA) method. We develop in this work a class of MFDCCA algorithms based on the detrending moving-average analysis, called MFXDMA. The performances of the proposed MFXDMA algorithms are compared with the MFXDFA method by extensive numerical experiments on pairs of time series generated from bivariate fractional Brownian motions, two-component autoregressive fractionally integrated moving-average processes, and binomial measures, which have theoretical expressions of the multifractal nature. In all cases, the scaling exponents hxy extracted from the MFXDMA and MFXDFA algorithms are very close to the theoretical values. For bivariate fractional Brownian motions, the scaling exponent of the cross correlation is independent of the cross-correlation coefficient between two time series, and the MFXDFA and centered MFXDMA algorithms have comparative performances, which outperform the forward and backward MFXDMA algorithms. For two-component autoregressive fractionally integrated moving-average processes, we also find that the MFXDFA and centered MFXDMA algorithms have comparative performances, while the forward and backward MFXDMA algorithms perform slightly worse. For binomial measures, the forward MFXDMA algorithm exhibits the best performance, the centered MFXDMA algorithms performs worst, and the backward MFXDMA algorithm outperforms the MFXDFA algorithm when the moment order q<0 and underperforms when q>0. We apply these algorithms to the return time series of two stock market indexes and to their volatilities. For the returns, the centered MFXDMA algorithm gives the best estimates of hxy(q) since its hxy(2) is closest to 0.5, as expected, and the MFXDFA algorithm has the second best performance. For the volatilities, the forward and backward MFXDMA algorithms give similar results, while the centered MFXDMA and the MFXDFA algorithms fail to extract rational multifractal nature.

Bivariate categorical data analysis using normal linear conditional multinomial probability model.

PubMed

Sun, Bingrui; Sutradhar, Brajendra

2015-02-10

Bivariate multinomial data such as the left and right eyes retinopathy status data are analyzed either by using a joint bivariate probability model or by exploiting certain odds ratio-based association models. However, the joint bivariate probability model yields marginal probabilities, which are complicated functions of marginal and association parameters for both variables, and the odds ratio-based association model treats the odds ratios involved in the joint probabilities as 'working' parameters, which are consequently estimated through certain arbitrary 'working' regression models. Also, this later odds ratio-based model does not provide any easy interpretations of the correlations between two categorical variables. On the basis of pre-specified marginal probabilities, in this paper, we develop a bivariate normal type linear conditional multinomial probability model to understand the correlations between two categorical variables. The parameters involved in the model are consistently estimated using the optimal likelihood and generalized quasi-likelihood approaches. The proposed model and the inferences are illustrated through an intensive simulation study as well as an analysis of the well-known Wisconsin Diabetic Retinopathy status data. Copyright © 2014 John Wiley & Sons, Ltd.

Texture analysis of apparent diffusion coefficient maps for treatment response assessment in prostate cancer bone metastases-A pilot study.

PubMed

Reischauer, Carolin; Patzwahl, René; Koh, Dow-Mu; Froehlich, Johannes M; Gutzeit, Andreas

2018-04-01

To evaluate whole-lesion volumetric texture analysis of apparent diffusion coefficient (ADC) maps for assessing treatment response in prostate cancer bone metastases. Texture analysis is performed in 12 treatment-naïve patients with 34 metastases before treatment and at one, two, and three months after the initiation of androgen deprivation therapy. Four first-order and 19 second-order statistical texture features are computed on the ADC maps in each lesion at every time point. Repeatability, inter-patient variability, and changes in the feature values under therapy are investigated. Spearman rank's correlation coefficients are calculated across time to demonstrate the relationship between the texture features and the serum prostate specific antigen (PSA) levels. With few exceptions, the texture features exhibited moderate to high precision. At the same time, Friedman's tests revealed that all first-order and second-order statistical texture features changed significantly in response to therapy. Thereby, the majority of texture features showed significant changes in their values at all post-treatment time points relative to baseline. Bivariate analysis detected significant correlations between the great majority of texture features and the serum PSA levels. Thereby, three first-order and six second-order statistical features showed strong correlations with the serum PSA levels across time. The findings in the present work indicate that whole-tumor volumetric texture analysis may be utilized for response assessment in prostate cancer bone metastases. The approach may be used as a complementary measure for treatment monitoring in conjunction with averaged ADC values. Copyright © 2018 Elsevier B.V. All rights reserved.

Correlation of spatial climate/weather maps and the advantages of using the Mahalanobis metric in predictions

NASA Astrophysics Data System (ADS)

Stephenson, D. B.

1997-10-01

The skill in predicting spatially varying weather/climate maps depends on the definition of the measure of similarity between the maps. Under the justifiable approximation that the anomaly maps are distributed multinormally, it is shown analytically that the choice of weighting metric, used in defining the anomaly correlation between spatial maps, can change the resulting probability distribution of the correlation coefficient. The estimate of the numbers of degrees of freedom based on the variance of the correlation distribution can vary from unity up to the number of grid points depending on the choice of weighting metric. The (pseudo-) inverse of the sample covariance matrix acts as a special choice for the metric in that it gives a correlation distribution which has minimal kurtosis and maximum dimension. Minimal kurtosis suggests that the average predictive skill might be improved due to the rarer occurrence of troublesome outlier patterns far from the mean state. Maximum dimension has a disadvantage for analogue prediction schemes in that it gives the minimum number of analogue states. This metric also has an advantage in that it allows one to powerfully test the null hypothesis of multinormality by examining the second and third moments of the correlation coefficient which were introduced by Mardia as invariant measures of multivariate kurtosis and skewness. For these reasons, it is suggested that this metric could be usefully employed in the prediction of weather/climate and in fingerprinting anthropogenic climate change. The ideas are illustrated using the bivariate example of the observed monthly mean sea-level pressures at Darwin and Tahitifrom 1866 1995.

Some properties of a 5-parameter bivariate probability distribution

NASA Technical Reports Server (NTRS)

Tubbs, J. D.; Brewer, D. W.; Smith, O. E.

1983-01-01

A five-parameter bivariate gamma distribution having two shape parameters, two location parameters and a correlation parameter was developed. This more general bivariate gamma distribution reduces to the known four-parameter distribution. The five-parameter distribution gives a better fit to the gust data. The statistical properties of this general bivariate gamma distribution and a hypothesis test were investigated. Although these developments have come too late in the Shuttle program to be used directly as design criteria for ascent wind gust loads, the new wind gust model has helped to explain the wind profile conditions which cause large dynamic loads. Other potential applications of the newly developed five-parameter bivariate gamma distribution are in the areas of reliability theory, signal noise, and vibration mechanics.

A test of the hypothesis that correlational selection generates genetic correlations.

PubMed

Roff, Derek A; Fairbairn, Daphne J

2012-09-01

Theory predicts that correlational selection on two traits will cause the major axis of the bivariate G matrix to orient itself in the same direction as the correlational selection gradient. Two testable predictions follow from this: for a given pair of traits, (1) the sign of correlational selection gradient should be the same as that of the genetic correlation, and (2) the correlational selection gradient should be positively correlated with the value of the genetic correlation. We test this hypothesis with a meta-analysis utilizing empirical estimates of correlational selection gradients and measures of the correlation between the two focal traits. Our results are consistent with both predictions and hence support the underlying hypothesis that correlational selection generates a genetic correlation between the two traits and hence orients the bivariate G matrix. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.

Hyperbolic Cross Truncations for Stochastic Fourier Cosine Series

PubMed Central

Zhang, Zhihua

2014-01-01

Based on our decomposition of stochastic processes and our asymptotic representations of Fourier cosine coefficients, we deduce an asymptotic formula of approximation errors of hyperbolic cross truncations for bivariate stochastic Fourier cosine series. Moreover we propose a kind of Fourier cosine expansions with polynomials factors such that the corresponding Fourier cosine coefficients decay very fast. Although our research is in the setting of stochastic processes, our results are also new for deterministic functions. PMID:25147842

[Association between health anthropometric indexes with physical fitness in physically active elderly women].

PubMed

Valdés-Badilla, Pablo; Godoy-Cumillaf, Andrés; Ortega-Spuler, Jenny; Herrera-Valenzuela, Tomás; Durán-Agüero, Samuel; Zapata-Bastias, José; Vargas-Vitoria, Rodrigo; Guzmán-Muñoz, Eduardo; López-Fuenzalida, Antonio

2017-01-01

To associate health anthropometric indexes with physical fitness of elderly women (EW) who participate in physical exercise workshops. 272 Chilean women over 60 years took part in the study. The variables studied were BMI, waist circumference (WC), waist-height index (WHI) and physical fitness (PF). Correlations were made through the Pearson or Spearman coefficient, and bivariate associations using Pearson's Chi-square and the Fisher's exact test, considering p<0.05. 70.8% of the EW were overweight or obese; 68.8% and 96% were at cardiometabolic risk due to their WC and WHI, respectively. Their PF showed equal performance (53.5%) or higher (33.8%) according to their age and gender. Inverse correlations were found between nutritional status and cardiometabolic risk with PF tests (except for agility and dynamic balance [direct]), and direct association with back scratch test. Excess weight in physically active EW would not affect their physical-functional performance; however, cardiometabolic risk would be inversely associated with motor function.

Biomechanical factors associated with time to complete a change of direction cutting maneuver.

PubMed

Marshall, Brendan M; Franklyn-Miller, Andrew D; King, Enda A; Moran, Kieran A; Strike, Siobhán C; Falvey, Éanna C

2014-10-01

Cutting ability is an important aspect of many team sports, however, the biomechanical determinants of cutting performance are not well understood. This study aimed to address this issue by identifying the kinetic and kinematic factors correlated with the time to complete a cutting maneuver. In addition, an analysis of the test-retest reliability of all biomechanical measures was performed. Fifteen (n = 15) elite multidirectional sports players (Gaelic hurling) were recruited, and a 3-dimensional motion capture analysis of a 75° cut was undertaken. The factors associated with cutting time were determined using bivariate Pearson's correlations. Intraclass correlation coefficients (ICCs) were used to examine the test-retest reliability of biomechanical measures. Five biomechanical factors were associated with cutting time (2.28 ± 0.11 seconds): peak ankle power (r = 0.77), peak ankle plantar flexor moment (r = 0.65), range of pelvis lateral tilt (r = -0.54), maximum thorax lateral rotation angle (r = 0.51), and total ground contact time (r = -0.48). Intraclass correlation coefficient scores for these 5 factors, and indeed for the majority of the other biomechanical measures, ranged from good to excellent (ICC >0.60). Explosive force production about the ankle, pelvic control during single-limb support, and torso rotation toward the desired direction of travel were all key factors associated with cutting time. These findings should assist in the development of more effective training programs aimed at improving similar cutting performances. In addition, test-retest reliability scores were generally strong, therefore, motion capture techniques seem well placed to further investigate the determinants of cutting ability.

Multifractal detrended cross-correlation analysis on air pollutants of University of Hyderabad Campus, India

NASA Astrophysics Data System (ADS)

Manimaran, P.; Narayana, A. C.

2018-07-01

In this paper, we study the multifractal characteristics and cross-correlation behaviour of Air Pollution Index (API) time series data through multifractal detrended cross-correlation analysis method. We analyse the daily API records of nine air pollutants of the university of Hyderabad campus for a period of three years (2013-2016). The cross-correlation behaviour has been measured from the Hurst scaling exponents and the singularity spectrum quantitatively. From the results, it is found that the cross-correlation analysis shows anti-correlation behaviour for all possible 36 bivariate time series. We also observe the existence of multifractal nature in all the bivariate time series in which many of them show strong multifractal behaviour. In particular, the hazardous particulate matter PM2.5 and inhalable particulate matter PM10 shows anti-correlated behaviour with all air pollutants.

Size ratio performance in detecting cerebral aneurysm rupture status is insensitive to small vessel removal.

PubMed

Lauric, Alexandra; Baharoglu, Merih I; Malek, Adel M

2013-04-01

The variable definition of size ratio (SR) for sidewall (SW) vs bifurcation (BIF) aneurysms raises confusion for lesions harboring small branches, such as carotid ophthalmic or posterior communicating locations. These aneurysms are considered SW by many clinicians, but SR methodology classifies them as BIF. To evaluate the effect of ignoring small vessels and SW vs stringent BIF labeling on SR ruptured aneurysm detection performance in borderline aneurysms with small branches, and to reconcile SR-based labeling with clinical SW/BIF classification. Catheter rotational angiographic datasets of 134 consecutive aneurysms (60 ruptured) were automatically measured in 3-dimensional. Stringent BIF labeling was applied to clinically labeled aneurysms, with 21 aneurysms switching label from SW to BIF. Parent vessel size was evaluated both taking into account, and ignoring, small vessels. SR was defined accordingly as the ratio between aneurysm and parent vessel sizes. Univariate and multivariate statistics identified significant features. The square of the correlation coefficient (R(2)) was reported for bivariate analysis of alternative SR calculations. Regardless of SW/BIF labeling method, SR was equally significant in discriminating aneurysm ruptured status (P < .001). Bivariate analysis of alternative SR had a high correlation of R(2) = 0.94 on the whole dataset, and R = 0.98 on the 21 borderline aneurysms. Ignoring small branches from SR calculation maintains rupture status detection performance, while reducing postprocessing complexity and removing labeling ambiguity. Aneurysms adjacent to these vessels can be considered SW for morphometric analysis. It is reasonable to use the clinical SW/BIF labeling when using SR for rupture risk evaluation.

Assessment of the pollution and ecological risk of lead and cadmium in soils.

PubMed

Wieczorek, Jerzy; Baran, Agnieszka; Urbański, Krzysztof; Mazurek, Ryszard; Klimowicz-Pawlas, Agnieszka

2018-03-27

The aim of the study was to assess the content, distribution, soil binding capacity, and ecological risk of cadmium and lead in the soils of Malopolska (South Poland). The investigation of 320 soil samples from differently used land (grassland, arable land, forest, wasteland) revealed a very high variation in the metal content in the soils. The pollution of soils with cadmium and lead is moderate. Generally, a point source of lead and cadmium pollution was noted in the study area. The highest content of cadmium and lead was found in the northwestern part of the area-the industrial zones (mining and metallurgical activity). These findings are confirmed by the arrangement of semivariogram surfaces and bivariate Moran's correlation coefficients. Among the different types of land use, forest soils had by far the highest mean content of bioavailable forms of both metals. The results showed a higher soil binding capacity for lead than for cadmium. However, for both metals, extremely high (class 5) accumulation capacities were dominant. Based on the results, the investigated soils had a low (Pb) and moderate (Cd) ecological risk on living components. Soil properties, such as organic C, pH, sand, silt, and clay content, correlated with the content of total and bioavailable forms of metals in the soils. The correlations, despite being statistically significant, were characterized by very low values of correlation coefficient (r = 0.12-0.20, at p ≤ 0.05). Therefore, the obtained data do not allow to define any conclusions as to the relationships between these soil properties. However, it must be highlighted that there was a very strong positive correlation between the total content of cadmium and lead and their bioavailable forms in the soils.

Estimating correlation between multivariate longitudinal data in the presence of heterogeneity.

PubMed

Gao, Feng; Philip Miller, J; Xiong, Chengjie; Luo, Jingqin; Beiser, Julia A; Chen, Ling; Gordon, Mae O

2017-08-17

Estimating correlation coefficients among outcomes is one of the most important analytical tasks in epidemiological and clinical research. Availability of multivariate longitudinal data presents a unique opportunity to assess joint evolution of outcomes over time. Bivariate linear mixed model (BLMM) provides a versatile tool with regard to assessing correlation. However, BLMMs often assume that all individuals are drawn from a single homogenous population where the individual trajectories are distributed smoothly around population average. Using longitudinal mean deviation (MD) and visual acuity (VA) from the Ocular Hypertension Treatment Study (OHTS), we demonstrated strategies to better understand the correlation between multivariate longitudinal data in the presence of potential heterogeneity. Conditional correlation (i.e., marginal correlation given random effects) was calculated to describe how the association between longitudinal outcomes evolved over time within specific subpopulation. The impact of heterogeneity on correlation was also assessed by simulated data. There was a significant positive correlation in both random intercepts (ρ = 0.278, 95% CI: 0.121-0.420) and random slopes (ρ = 0.579, 95% CI: 0.349-0.810) between longitudinal MD and VA, and the strength of correlation constantly increased over time. However, conditional correlation and simulation studies revealed that the correlation was induced primarily by participants with rapid deteriorating MD who only accounted for a small fraction of total samples. Conditional correlation given random effects provides a robust estimate to describe the correlation between multivariate longitudinal data in the presence of unobserved heterogeneity (NCT00000125).

Meta-analysis of studies with bivariate binary outcomes: a marginal beta-binomial model approach

PubMed Central

Chen, Yong; Hong, Chuan; Ning, Yang; Su, Xiao

2018-01-01

When conducting a meta-analysis of studies with bivariate binary outcomes, challenges arise when the within-study correlation and between-study heterogeneity should be taken into account. In this paper, we propose a marginal beta-binomial model for the meta-analysis of studies with binary outcomes. This model is based on the composite likelihood approach, and has several attractive features compared to the existing models such as bivariate generalized linear mixed model (Chu and Cole, 2006) and Sarmanov beta-binomial model (Chen et al., 2012). The advantages of the proposed marginal model include modeling the probabilities in the original scale, not requiring any transformation of probabilities or any link function, having closed-form expression of likelihood function, and no constraints on the correlation parameter. More importantly, since the marginal beta-binomial model is only based on the marginal distributions, it does not suffer from potential misspecification of the joint distribution of bivariate study-specific probabilities. Such misspecification is difficult to detect and can lead to biased inference using currents methods. We compare the performance of the marginal beta-binomial model with the bivariate generalized linear mixed model and the Sarmanov beta-binomial model by simulation studies. Interestingly, the results show that the marginal beta-binomial model performs better than the Sarmanov beta-binomial model, whether or not the true model is Sarmanov beta-binomial, and the marginal beta-binomial model is more robust than the bivariate generalized linear mixed model under model misspecifications. Two meta-analyses of diagnostic accuracy studies and a meta-analysis of case-control studies are conducted for illustration. PMID:26303591

Evidence for bivariate linkage of obesity and HDL-C levels in the Framingham Heart Study.

PubMed

Arya, Rector; Lehman, Donna; Hunt, Kelly J; Schneider, Jennifer; Almasy, Laura; Blangero, John; Stern, Michael P; Duggirala, Ravindranath

2003-12-31

Epidemiological studies have indicated that obesity and low high-density lipoprotein (HDL) levels are strong cardiovascular risk factors, and that these traits are inversely correlated. Despite the belief that these traits are correlated in part due to pleiotropy, knowledge on specific genes commonly affecting obesity and dyslipidemia is very limited. To address this issue, we first conducted univariate multipoint linkage analysis for body mass index (BMI) and HDL-C to identify loci influencing variation in these phenotypes using Framingham Heart Study data relating to 1702 subjects distributed across 330 pedigrees. Subsequently, we performed bivariate multipoint linkage analysis to detect common loci influencing covariation between these two traits. We scanned the genome and identified a major locus near marker D6S1009 influencing variation in BMI (LOD = 3.9) using the program SOLAR. We also identified a major locus for HDL-C near marker D2S1334 on chromosome 2 (LOD = 3.5) and another region near marker D6S1009 on chromosome 6 with suggestive evidence for linkage (LOD = 2.7). Since these two phenotypes have been independently mapped to the same region on chromosome 6q, we used the bivariate multipoint linkage approach using SOLAR. The bivariate linkage analysis of BMI and HDL-C implicated the genetic region near marker D6S1009 as harboring a major gene commonly influencing these phenotypes (bivariate LOD = 6.2; LODeq = 5.5) and appears to improve power to map the correlated traits to a region, precisely. We found substantial evidence for a quantitative trait locus with pleiotropic effects, which appears to influence both BMI and HDL-C phenotypes in the Framingham data.

Heritability of carotid intima-media thickness: a twin study.

PubMed

Zhao, Jinying; Cheema, Faiz A; Bremner, J Douglas; Goldberg, Jack; Su, Shaoyong; Snieder, Harold; Maisano, Carisa; Jones, Linda; Javed, Farhan; Murrah, Nancy; Le, Ngoc-Anh; Vaccarino, Viola

2008-04-01

To estimate the heritability of carotid intima-media thickness (IMT), a surrogate marker for atherosclerosis, independent of traditional coronary risk factors. We performed a classical twin study of carotid IMT using 98 middle-aged male twin pairs, 58 monozygotic (MZ) and 40 dizygotic (DZ) pairs, from the Vietnam Era Twin Registry. All twins were free of overt cardiovascular disease. Carotid IMT was measured by ultrasound. Bivariate and multivariate analyses were used to determine the association between traditional cardiovascular risk factors and carotid IMT. Intraclass correlation coefficients and genetic modeling techniques were used to determine the relative contributions of genes and environment to the variation in carotid IMT. In our sample, the mean of the maximum carotid IMT was 0.75+/-0.11. Age, systolic blood pressure and HDL were significantly associated with carotid IMT. The intraclass correlation coefficient for carotid IMT was larger in MZ (0.66; 95% confidence interval [CI], 0.62-0.69) than in DZ twins (0.37; 95% CI, 0.29-0.44), and the unadjusted heritability was 0.69 (95% CI, 0.54-0.79). After adjusting for traditional coronary risk factors, the heritability of carotid IMT was slightly reduced but still of considerable magnitude (0.59; 95% CI, 0.39-0.73). Genetic factors have a substantial influence on the variation of carotid IMT. Most of this genetic effect occurs through pathways independent of traditional coronary risk factors.

Interpreting Bivariate Regression Coefficients: Going beyond the Average

ERIC Educational Resources Information Center

Halcoussis, Dennis; Phillips, G. Michael

2010-01-01

Statistics, econometrics, investment analysis, and data analysis classes often review the calculation of several types of averages, including the arithmetic mean, geometric mean, harmonic mean, and various weighted averages. This note shows how each of these can be computed using a basic regression framework. By recognizing when a regression model…

Does providing more services increase the primary hospitals' revenue? An assessment of national essential medicine policy based on 2,675 counties in China.

PubMed

Chen, Fei; Yang, Min; Li, Qian; Pan, Jay; Li, Xiaosong; Meng, Qun

2018-01-01

To understand whether the increased outpatient service provision (OSP) brings in enough additional income (excluding income from essential medicine) for primary hospitals (INCOME) to compensate for reduced costs of medicine. The two outcomes, annual OSP and INCOME for the period of 2008-2012, were collected from 34,506 primary hospitals in 2,675 counties in 31 provinces in China by the national surveillance system. The data had a four-level hierarchical structure; time points were nested within primary hospital, hospitals within county, and counties within province. We fitted bivariate five-level random effects regression models to examine correlations between OSP and INCOME in terms of their mean values and dose-response effects of the essential medicine policy (EMP). We adjusted for the effects of time period and selected hospital resources. The estimated correlation coefficients between the two outcomes' mean values were strongly positive among provinces (r = 0.910), moderately positive among counties (r = 0.380), and none among hospitals (r = 0.002) and time (r = 0.007). The correlation between their policy effects was weakly positive among provinces (r = 0.234), but none at the county and hospital levels. However, there were markedly negative correlation coefficients between the mean and policy effects at -0.328 for OSP and -0.541 for INCOME at the hospital level. There was no evidence to suggest an association between the two outcomes in terms of their mean values and dose-response effects of EMP at the hospital level. This indicated that increased OSP did not bring enough additional INCOME. Sustainable mechanisms to compensate primary hospitals are needed.

Obtaining the mean relative weights of the cost of care in Catalonia (Spain): retrospective application of the adjusted clinical groups case-mix system in primary health care.

PubMed

Sicras-Mainar, Antoni; Velasco-Velasco, Soledad; Navarro-Artieda, Ruth; Aguado Jodar, Alba; Plana-Ripoll, Oleguer; Hermosilla-Pérez, Eduardo; Bolibar-Ribas, Bonaventura; Prados-Torres, Alejandra; Violan-Fors, Concepción

2013-04-01

The study aims to obtain the mean relative weights (MRWs) of the cost of care through the retrospective application of the adjusted clinical groups (ACGs) in several primary health care (PHC) centres in Catalonia (Spain) in routine clinical practice. This is a retrospective study based on computerized medical records. All patients attended by 13 PHC teams in 2008 were included. The principle measurements were: demographic variables (age and sex), dependent variables (number of diagnoses and total costs), and case-mix or co-morbidity variables (International Classification of Primary Care). The costs model for each patient was established by differentiating the fix costs from the variable costs. In the bivariate analysis, the Student's t, analysis of variance, chi-squared, Pearson's linear correlation and Mann-Whitney-Wilcoxon tests were used. In order to compare the MRW of the present study with those of the United States (US), the concordance [intraclass correlation coefficient (ICC) and concordance correlation coefficient (CCC)] and the correlation (coefficient of determination: R²) were measured. The total number of patients studied was 227,235, and the frequentation was 5.9 visits/habitant/year) and with a mean diagnoses number of 4.5 (3.2). The distribution of costs was €148.7 million, of which 29.1% were fixed costs. The mean total cost per patient/year was €654.2 (851.7), which was considered to be the reference MRW. Relationship between study-MRW and US-MRW: ICC was 0.40 [confidential interval (CI) 95%: 0.21-0.60] and the CCC was 0.42 (CI 95%: 0.35-0.49). The correlation between the US MRW and the MRW of the present study can be seen; the adjusted R² value is 0.691. The explanatory power of the ACG classification was 36.9% for the total costs. The R² of the total cost without considering outliers was 56.9%. The methodology has been shown appropriate for promoting the calculation of the MRW for each category of the classification. The results provide a possible practical application in PHC clinical management. © 2012 Blackwell Publishing Ltd.

Meta-analysis of studies with bivariate binary outcomes: a marginal beta-binomial model approach.

PubMed

Chen, Yong; Hong, Chuan; Ning, Yang; Su, Xiao

2016-01-15

When conducting a meta-analysis of studies with bivariate binary outcomes, challenges arise when the within-study correlation and between-study heterogeneity should be taken into account. In this paper, we propose a marginal beta-binomial model for the meta-analysis of studies with binary outcomes. This model is based on the composite likelihood approach and has several attractive features compared with the existing models such as bivariate generalized linear mixed model (Chu and Cole, 2006) and Sarmanov beta-binomial model (Chen et al., 2012). The advantages of the proposed marginal model include modeling the probabilities in the original scale, not requiring any transformation of probabilities or any link function, having closed-form expression of likelihood function, and no constraints on the correlation parameter. More importantly, because the marginal beta-binomial model is only based on the marginal distributions, it does not suffer from potential misspecification of the joint distribution of bivariate study-specific probabilities. Such misspecification is difficult to detect and can lead to biased inference using currents methods. We compare the performance of the marginal beta-binomial model with the bivariate generalized linear mixed model and the Sarmanov beta-binomial model by simulation studies. Interestingly, the results show that the marginal beta-binomial model performs better than the Sarmanov beta-binomial model, whether or not the true model is Sarmanov beta-binomial, and the marginal beta-binomial model is more robust than the bivariate generalized linear mixed model under model misspecifications. Two meta-analyses of diagnostic accuracy studies and a meta-analysis of case-control studies are conducted for illustration. Copyright © 2015 John Wiley & Sons, Ltd.

The Reliability, Validity, and Normative Data of Interpupillary Distance and Pupil Diameter Using Eye-Tracking Technology

PubMed Central

Murray, Nicholas P.; Hunfalvay, Melissa; Bolte, Takumi

2017-01-01

Purpose The purpose of this study was to determine the reliability of interpupillary distance (IPD) and pupil diameter (PD) measures using an infrared eye tracker and central point stimuli. Validity of the test compared to known clinical tools was determined, and normative data was established against which individuals can measure themselves. Methods Participants (416) across various demographics were examined for normative data. Of these, 50 were examined for reliability and validity. Validity for IPD measured the test (RightEye IPD/PD) against the PL850 Pupilometer and the Essilor Digital CRP. For PD, the test was measured against the Rosenbaum Pocket Vision Screener (RPVS). Reliability was analyzed with intraclass correlation coefficients (ICC) between trials with Cronbach's alpha (CA) and the standard error of measurement for each ICC. Convergent validity was investigated by calculating the bivariate correlation coefficient. Results Reliability results were strong (CA > 0.7) for all measures. High positive significant correlations were found between the RightEye IPD test and the PL850 Pupilometer (P < 0.001) and Essilor Digital CRP (P < 0.001) and for the RightEye PD test and the RPVS (P < 0.001). Conclusions Using infrared eye tracking and the RightEye IPD/PD test stimuli, reliable and accurate measures of IPD and PD were found. Results from normative data showed an adequate comparison for people with normal vision development. Translational Relevance Results revealed a central point of fixation may remove variability in examining PD reliably using infrared eye tracking when consistent environmental and experimental procedures are conducted. PMID:28685104

Mixture models in diagnostic meta-analyses--clustering summary receiver operating characteristic curves accounted for heterogeneity and correlation.

PubMed

Schlattmann, Peter; Verba, Maryna; Dewey, Marc; Walther, Mario

2015-01-01

Bivariate linear and generalized linear random effects are frequently used to perform a diagnostic meta-analysis. The objective of this article was to apply a finite mixture model of bivariate normal distributions that can be used for the construction of componentwise summary receiver operating characteristic (sROC) curves. Bivariate linear random effects and a bivariate finite mixture model are used. The latter model is developed as an extension of a univariate finite mixture model. Two examples, computed tomography (CT) angiography for ruling out coronary artery disease and procalcitonin as a diagnostic marker for sepsis, are used to estimate mean sensitivity and mean specificity and to construct sROC curves. The suggested approach of a bivariate finite mixture model identifies two latent classes of diagnostic accuracy for the CT angiography example. Both classes show high sensitivity but mainly two different levels of specificity. For the procalcitonin example, this approach identifies three latent classes of diagnostic accuracy. Here, sensitivities and specificities are quite different as such that sensitivity increases with decreasing specificity. Additionally, the model is used to construct componentwise sROC curves and to classify individual studies. The proposed method offers an alternative approach to model between-study heterogeneity in a diagnostic meta-analysis. Furthermore, it is possible to construct sROC curves even if a positive correlation between sensitivity and specificity is present. Copyright © 2015 Elsevier Inc. All rights reserved.

Numerical analysis of the accuracy of bivariate quantile distributions utilizing copulas compared to the GUM supplement 2 for oil pressure balance uncertainties

NASA Astrophysics Data System (ADS)

Ramnath, Vishal

2017-11-01

In the field of pressure metrology the effective area is Ae = A0 (1 + λP) where A0 is the zero-pressure area and λ is the distortion coefficient and the conventional practise is to construct univariate probability density functions (PDFs) for A0 and λ. As a result analytical generalized non-Gaussian bivariate joint PDFs has not featured prominently in pressure metrology. Recently extended lambda distribution based quantile functions have been successfully utilized for summarizing univariate arbitrary PDF distributions of gas pressure balances. Motivated by this development we investigate the feasibility and utility of extending and applying quantile functions to systems which naturally exhibit bivariate PDFs. Our approach is to utilize the GUM Supplement 1 methodology to solve and generate Monte Carlo based multivariate uncertainty data for an oil based pressure balance laboratory standard that is used to generate known high pressures, and which are in turn cross-floated against another pressure balance transfer standard in order to deduce the transfer standard's respective area. We then numerically analyse the uncertainty data by formulating and constructing an approximate bivariate quantile distribution that directly couples A0 and λ in order to compare and contrast its accuracy to an exact GUM Supplement 2 based uncertainty quantification analysis.

Measuring multiple spike train synchrony.

PubMed

Kreuz, Thomas; Chicharro, Daniel; Andrzejak, Ralph G; Haas, Julie S; Abarbanel, Henry D I

2009-10-15

Measures of multiple spike train synchrony are essential in order to study issues such as spike timing reliability, network synchronization, and neuronal coding. These measures can broadly be divided in multivariate measures and averages over bivariate measures. One of the most recent bivariate approaches, the ISI-distance, employs the ratio of instantaneous interspike intervals (ISIs). In this study we propose two extensions of the ISI-distance, the straightforward averaged bivariate ISI-distance and the multivariate ISI-diversity based on the coefficient of variation. Like the original measure these extensions combine many properties desirable in applications to real data. In particular, they are parameter-free, time scale independent, and easy to visualize in a time-resolved manner, as we illustrate with in vitro recordings from a cortical neuron. Using a simulated network of Hindemarsh-Rose neurons as a controlled configuration we compare the performance of our methods in distinguishing different levels of multi-neuron spike train synchrony to the performance of six other previously published measures. We show and explain why the averaged bivariate measures perform better than the multivariate ones and why the multivariate ISI-diversity is the best performer among the multivariate methods. Finally, in a comparison against standard methods that rely on moving window estimates, we use single-unit monkey data to demonstrate the advantages of the instantaneous nature of our methods.

ANALYZING CORRELATIONS BETWEEN STREAM AND WATERSHED ATTRIBUTES

EPA Science Inventory

Bivariate correlation analysis has been widely used to explore relationships between stream and watershed attributes that have all been measured on the same set of watersheds or sampling locations. Researchers routinely test H0: =0 for each correlation in a large table and then ...

Pay No Attention to That Data Behind the Curtain: On Angry Birds, Happy Children, Scholarly Squabbles, Publication Bias, and Why Betas Rule Metas.

PubMed

Ferguson, Christopher J

2015-09-01

This article responds to five comments on my "Angry Birds" meta-analysis of video game influences on children (Ferguson, 2015, this issue). Given ongoing debates on video game influences, comments varied from the supportive to the self-proclaimed "angry," yet hopefully they and this response will contribute to constructive discussion as the field moves forward. In this reply, I address some misconceptions in the comments and present data that challenge the assumption that standardized regression coefficients are invariably unsuitable for meta-analysis or that bivariate correlations are invariably suitable for meta-analysis. The suitability of any data should be considered on a case-by-case basis, and data indicates that the coefficients included in the "Angry Birds" meta-analysis did not distort results. Study selection, effect size extraction, and interpretation improved upon problematic issues in other recent meta-analyses. Further evidence is also provided to support the contention that publication bias remains problematic in video game literature. Sources of acrimony among scholars are explored as are areas of agreement. Ultimately, debates will only be resolved through a commitment to newer, more rigorous methods and open science. © The Author(s) 2015.

Spectrum-based estimators of the bivariate Hurst exponent

NASA Astrophysics Data System (ADS)

Kristoufek, Ladislav

2014-12-01

We discuss two alternate spectrum-based estimators of the bivariate Hurst exponent in the power-law cross-correlations setting, the cross-periodogram and local X -Whittle estimators, as generalizations of their univariate counterparts. As the spectrum-based estimators are dependent on a part of the spectrum taken into consideration during estimation, a simulation study showing performance of the estimators under varying bandwidth parameter as well as correlation between processes and their specification is provided as well. These estimators are less biased than the already existent averaged periodogram estimator, which, however, has slightly lower variance. The spectrum-based estimators can serve as a good complement to the popular time domain estimators.

Life History Correlates of Ministerial Success

ERIC Educational Resources Information Center

Umeda, John K.; Frey, David H.

1974-01-01

Life history or biodata correlates of ministerial success were investigated for a group of 92 Seventh-Day Adventist ministers. Two significant bivariate correlations indicated that successful ministers chose their career later than less successful ones and that earning college expenses was predictive of success. (Author/HMV)

A generalized conditional heteroscedastic model for temperature downscaling

NASA Astrophysics Data System (ADS)

Modarres, R.; Ouarda, T. B. M. J.

2014-11-01

This study describes a method for deriving the time varying second order moment, or heteroscedasticity, of local daily temperature and its association to large Coupled Canadian General Circulation Models predictors. This is carried out by applying a multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) approach to construct the conditional variance-covariance structure between General Circulation Models (GCMs) predictors and maximum and minimum temperature time series during 1980-2000. Two MGARCH specifications namely diagonal VECH and dynamic conditional correlation (DCC) are applied and 25 GCM predictors were selected for a bivariate temperature heteroscedastic modeling. It is observed that the conditional covariance between predictors and temperature is not very strong and mostly depends on the interaction between the random process governing temporal variation of predictors and predictants. The DCC model reveals a time varying conditional correlation between GCM predictors and temperature time series. No remarkable increasing or decreasing change is observed for correlation coefficients between GCM predictors and observed temperature during 1980-2000 while weak winter-summer seasonality is clear for both conditional covariance and correlation. Furthermore, the stationarity and nonlinearity Kwiatkowski-Phillips-Schmidt-Shin (KPSS) and Brock-Dechert-Scheinkman (BDS) tests showed that GCM predictors, temperature and their conditional correlation time series are nonlinear but stationary during 1980-2000 according to BDS and KPSS test results. However, the degree of nonlinearity of temperature time series is higher than most of the GCM predictors.

Shared genetic factors underlie migraine and depression

PubMed Central

Yang, Yuanhao; Zhao, Huiying; Heath, Andrew C; Madden, Pamela AF; Martin, Nicholas G; Nyholt, Dale R

2017-01-01

Migraine frequently co-occurs with depression. Using a large sample of Australian twin pairs, we aimed to characterise the extent to which shared genetic factors underlie these two disorders. Migraine was classified using three diagnostic measures, including self-reported migraine, the ID migraine™ screening tool, or migraine without aura (MO) and migraine with aura (MA) based on International Headache Society (IHS) diagnostic criteria. Major depressive disorder (MDD) and minor depressive disorder (MiDD) were classified using the Diagnostic and Statistical Manual of Mental Disorders (DSM) criteria. Univariate and bivariate twin models, with and without sex-limitation, were constructed to estimate the univariate and bivariate variance components and genetic correlation for migraine and depression. The univariate heritability of broad migraine (self-reported, ID migraine or IHS MO/MA) and broad depression (MiDD or MDD) was estimated at 56% (95% confidence interval [CI]: 53–60%) and 42% (95% CI: 37–46%), respectively. A significant additive genetic correlation (rG=0.36, 95% CI: 0.29–0.43) and bivariate heritability (h2=5.5%, 95% CI: 3.6–7.8%) was observed between broad migraine and depression using the bivariate Cholesky model. Notably, both the bivariate h2 (13.3%, 95% CI: 7.0–24.5%) and rG (0.51, 95% CI: 0.37–0.69) estimates significantly increased when analysing the more narrow clinically-accepted diagnoses of IHS MO/MA and MDD. Our results indicate that for both broad and narrow definitions, the observed comorbidity between migraine and depression can be explained almost entirely by shared underlying genetically determined disease mechanisms. PMID:27302564

Costing Hospital Surgery Services: The Method Matters

PubMed Central

Mercier, Gregoire; Naro, Gerald

2014-01-01

Background Accurate hospital costs are required for policy-makers, hospital managers and clinicians to improve efficiency and transparency. However, different methods are used to allocate direct costs, and their agreement is poorly understood. The aim of this study was to assess the agreement between bottom-up and top-down unit costs of a large sample of surgical operations in a French tertiary centre. Methods Two thousand one hundred and thirty consecutive procedures performed between January and October 2010 were analysed. Top-down costs were based on pre-determined weights, while bottom-up costs were calculated through an activity-based costing (ABC) model. The agreement was assessed using correlation coefficients and the Bland and Altman method. Variables associated with the difference between methods were identified with bivariate and multivariate linear regressions. Results The correlation coefficient amounted to 0.73 (95%CI: 0.72; 0.76). The overall agreement between methods was poor. In a multivariate analysis, the cost difference was independently associated with age (Beta = −2.4; p = 0.02), ASA score (Beta = 76.3; p<0.001), RCI (Beta = 5.5; p<0.001), staffing level (Beta = 437.0; p<0.001) and intervention duration (Beta = −10.5; p<0.001). Conclusions The ability of the current method to provide relevant information to managers, clinicians and payers is questionable. As in other European countries, a shift towards time-driven activity-based costing should be advocated. PMID:24817167

Validity and Reliability of the Brazilian Version of the Rapid Estimate of Adult Literacy in Dentistry--BREALD-30.

PubMed

Junkes, Monica C; Fraiz, Fabian C; Sardenberg, Fernanda; Lee, Jessica Y; Paiva, Saul M; Ferreira, Fernanda M

2015-01-01

The aim of the present study was to translate, perform the cross-cultural adaptation of the Rapid Estimate of Adult Literacy in Dentistry to Brazilian-Portuguese language and test the reliability and validity of this version. After translation and cross-cultural adaptation, interviews were conducted with 258 parents/caregivers of children in treatment at the pediatric dentistry clinics and health units in Curitiba, Brazil. To test the instrument's validity, the scores of Brazilian Rapid Estimate of Adult Literacy in Dentistry (BREALD-30) were compared based on occupation, monthly household income, educational attainment, general literacy, use of dental services and three dental outcomes. The BREALD-30 demonstrated good internal reliability. Cronbach's alpha ranged from 0.88 to 0.89 when words were deleted individually. The analysis of test-retest reliability revealed excellent reproducibility (intraclass correlation coefficient = 0.983 and Kappa coefficient ranging from moderate to nearly perfect). In the bivariate analysis, BREALD-30 scores were significantly correlated with the level of general literacy (rs = 0.593) and income (rs = 0.327) and significantly associated with occupation, educational attainment, use of dental services, self-rated oral health and the respondent's perception regarding his/her child's oral health. However, only the association between the BREALD-30 score and the respondent's perception regarding his/her child's oral health remained significant in the multivariate analysis. The BREALD-30 demonstrated satisfactory psychometric properties and is therefore applicable to adults in Brazil.

Validity and Reliability of the Brazilian Version of the Rapid Estimate of Adult Literacy in Dentistry – BREALD-30

PubMed Central

Junkes, Monica C.; Fraiz, Fabian C.; Sardenberg, Fernanda; Lee, Jessica Y.; Paiva, Saul M.; Ferreira, Fernanda M.

2015-01-01

Objective The aim of the present study was to translate, perform the cross-cultural adaptation of the Rapid Estimate of Adult Literacy in Dentistry to Brazilian-Portuguese language and test the reliability and validity of this version. Methods After translation and cross-cultural adaptation, interviews were conducted with 258 parents/caregivers of children in treatment at the pediatric dentistry clinics and health units in Curitiba, Brazil. To test the instrument's validity, the scores of Brazilian Rapid Estimate of Adult Literacy in Dentistry (BREALD-30) were compared based on occupation, monthly household income, educational attainment, general literacy, use of dental services and three dental outcomes. Results The BREALD-30 demonstrated good internal reliability. Cronbach’s alpha ranged from 0.88 to 0.89 when words were deleted individually. The analysis of test-retest reliability revealed excellent reproducibility (intraclass correlation coefficient = 0.983 and Kappa coefficient ranging from moderate to nearly perfect). In the bivariate analysis, BREALD-30 scores were significantly correlated with the level of general literacy (rs = 0.593) and income (rs = 0.327) and significantly associated with occupation, educational attainment, use of dental services, self-rated oral health and the respondent’s perception regarding his/her child's oral health. However, only the association between the BREALD-30 score and the respondent’s perception regarding his/her child's oral health remained significant in the multivariate analysis. Conclusion The BREALD-30 demonstrated satisfactory psychometric properties and is therefore applicable to adults in Brazil. PMID:26158724

Heritability of Carotid Intima-Media Thickness: A Twin Study

PubMed Central

Zhao, Jinying; Cheema, Faiz A.; Bremner, J. Douglas; Goldberg, Jack; Su, Shaoyong; Snieder, Harold; Maisano, Carisa; Jones, Linda; Javed, Farhan; Murrah, Nancy; Le, Ngoc-Anh; Vaccarino, Viola

2008-01-01

Objective To estimate the heritability of carotid intima-media thickness (IMT), a surrogate marker for atherosclerosis, independent of traditional coronary risk factors. Methods and Results We performed a classical twin study of carotid IMT using 98 middle-aged male twin pairs, 58 monozygotic (MZ) and 40 dizygotic (DZ) pairs, from the Vietnam Era Twin Registry. All twins were free of overt cardiovascular disease. Carotid IMT was measured by ultrasound. Bivariate and multivariate analyses were used to determine the association between traditional cardiovascular risk factors and carotid IMT. Intraclass correlation coefficients and genetic modeling techniques were used to determine the relative contributions of genes and environment to the variation in carotid IMT. In our sample, the mean of the maximum carotid IMT was 0.75 ± 0.11. Age, systolic blood pressure and HDL were significantly associated with carotid IMT. The intraclass correlation coefficient for carotid IMT was larger in MZ (0.66; 95% confidence interval [CI], 0.62–0.69) than in DZ twins (0.37; 95% CI, 0.29–0.44), and the unadjusted heritability was 0.69 (95% CI, 0.54–0.79). After adjusting for traditional coronary risk factors, the heritability of carotid IMT was slightly reduced but still of considerable magnitude (0.59; 95% CI, 0.39–0.73). Conclusion Genetic factors have a substantial influence on the variation of carotid IMT. Most of this genetic effect occurs through pathways independent of traditional coronary risk factors. PMID:17825306

Genetic correlations between body condition scores and fertility in dairy cattle using bivariate random regression models.

PubMed

De Haas, Y; Janss, L L G; Kadarmideen, H N

2007-10-01

Genetic correlations between body condition score (BCS) and fertility traits in dairy cattle were estimated using bivariate random regression models. BCS was recorded by the Swiss Holstein Association on 22,075 lactating heifers (primiparous cows) from 856 sires. Fertility data during first lactation were extracted for 40,736 cows. The fertility traits were days to first service (DFS), days between first and last insemination (DFLI), calving interval (CI), number of services per conception (NSPC) and conception rate to first insemination (CRFI). A bivariate model was used to estimate genetic correlations between BCS as a longitudinal trait by random regression components, and daughter's fertility at the sire level as a single lactation measurement. Heritability of BCS was 0.17, and heritabilities for fertility traits were low (0.01-0.08). Genetic correlations between BCS and fertility over the lactation varied from: -0.45 to -0.14 for DFS; -0.75 to 0.03 for DFLI; from -0.59 to -0.02 for CI; from -0.47 to 0.33 for NSPC and from 0.08 to 0.82 for CRFI. These results show (genetic) interactions between fat reserves and reproduction along the lactation trajectory of modern dairy cows, which can be useful in genetic selection as well as in management. Maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in mid lactation when the genetic variance for BCS is largest, and the genetic correlations between BCS and fertility is strongest.

Diagnostic accuracy of intraocular pressure measurement for the detection of raised intracranial pressure: meta-analysis: a systematic review.

PubMed

Yavin, Daniel; Luu, Judy; James, Matthew T; Roberts, Derek J; Sutherland, Garnette R; Jette, Nathalie; Wiebe, Samuel

2014-09-01

Because clinical examination and imaging may be unreliable indicators of intracranial hypertension, intraocular pressure (IOP) measurement has been proposed as a noninvasive method of diagnosis. The authors conducted a systematic review and meta-analysis to determine the correlation between IOP and intracranial pressure (ICP) and the diagnostic accuracy of IOP measurement for detection of intracranial hypertension. The authors searched bibliographic databases (Ovid MEDLINE, Ovid EMBASE, and the Cochrane Central Register of Controlled Trials) from 1950 to March 2013, references of included studies, and conference abstracts for studies comparing IOP and invasive ICP measurement. Two independent reviewers screened abstracts, reviewed full-text articles, and extracted data. Correlation coefficients, sensitivity, specificity, and positive and negative likelihood ratios were calculated using DerSimonian and Laird methods and bivariate random effects models. The I(2) statistic was used as a measure of heterogeneity. Among 355 identified citations, 12 studies that enrolled 546 patients were included in the meta-analysis. The pooled correlation coefficient between IOP and ICP was 0.44 (95% CI 0.26-0.63, I(2) = 97.7%, p < 0.001). The summary sensitivity and specificity for IOP for diagnosing intracranial hypertension were 81% (95% CI 26%-98%, I(2) = 95.2%, p < 0.01) and 95% (95% CI 43%-100%, I(2) = 97.7%, p < 0.01), respectively. The summary positive and negative likelihood ratios were 14.8 (95% CI 0.5-417.7) and 0.2 (95% CI 0.02-1.7), respectively. When ICP and IOP measurements were taken within 1 hour of another, correlation between the measures improved. Although a modest aggregate correlation was found between IOP and ICP, the pooled diagnostic accuracy suggests that IOP measurement may be of clinical utility in the detection of intracranial hypertension. Given the significant heterogeneity between included studies, further investigation is required prior to the adoption of IOP in the evaluation of intracranial hypertension into routine practice.

The Validation and Reliability of the Chinese Version of the Speech Handicap Index for Patients With Oral and Oropharyngeal Cancer.

PubMed

Li, Tianzhu; Ma, Lian; Mao, Chi

2016-03-01

The purpose of this study was to investigate the validity and reliability of the translated Chinese version of the Speech Handicap Index (SHI) questionnaire for Chinese-speaking patients with oral and oropharyngeal cancer. The original English version of the SHI was translated into Chinese. Forty-two consecutive patients with oral and oropharyngeal cancer were included in the study. All subjects were asked to complete the Chinese version of the SHI and the University of Washington Quality of Life Questionnaire (UWQOL V.04). Fifteen patients were randomly retested on both questionnaires 2 weeks later. The internal consistency, test-retest reliability, construct validity, and group validity of the Chinese version of the SHI were tested using Cronbach α, Spearman correlation coefficient (r), and Mann-Whitney U tests. Descriptive and bivariate statistics were computed, and the P value was set to 0.05. The Cronbach α for the total SHI, the speech domain, and the psychosocial domain were 0.96, 0.90, and 0.92, respectively. The test-retest reliability scores for the total SHI, the speech domain, the psychosocial domain, and the overall question were 0.94, 0.97, 0.90, and 0.83, respectively. To measure construct validity, Spearman correlation coefficients between different items of the SHI and the UWQOL were all >0.4, which signified a moderate to significant correlation. There were significant differences between patient groups when divided by age, clinical stage, educational level, radiotherapy, and reconstruction, on all or on parts of the various SHI domains. The Chinese version of the SHI is a valid and reliable tool for the speech assessment of patients with oral and oropharyngeal cancer. Copyright © 2016 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Non-Normality and Testing that a Correlation Equals Zero

ERIC Educational Resources Information Center

Levy, Kenneth J.

1977-01-01

The importance of the assumption of normality for testing that a bivariate normal correlation equals zero is examined. Both empirical and theoretical evidence suggest that such tests are robust with respect to violation of the normality assumption. (Author/JKS)

Parametric analysis for matched pair survival data.

PubMed

Manatunga, A K; Oakes, D

1999-12-01

Hougaard's (1986) bivariate Weibull distribution with positive stable frailties is applied to matched pairs survival data when either or both components of the pair may be censored and covariate vectors may be of arbitrary fixed length. When there is no censoring, we quantify the corresponding gain in Fisher information over a fixed-effects analysis. With the appropriate parameterization, the results take a simple algebraic form. An alternative marginal ("independence working model") approach to estimation is also considered. This method ignores the correlation between the two survival times in the derivation of the estimator, but provides a valid estimate of standard error. It is shown that when both the correlation between the two survival times is high, and the ratio of the within-pair variability to the between-pair variability of the covariates is high, the fixed-effects analysis captures most of the information about the regression coefficient but the independence working model does badly. When the correlation is low, and/or most of the variability of the covariates occurs between pairs, the reverse is true. The random effects model is applied to data on skin grafts, and on loss of visual acuity among diabetics. In conclusion some extensions of the methods are indicated and they are placed in a wider context of Generalized Estimation Equation methodology.

Correlation between plasma homocysteine levels and craving in alcohol dependent stabilized patients.

PubMed

Coppola, Maurizio; Mondola, Raffaella

2018-06-01

Homocysteine is a sulfur amino acid strictly related with alcohol consumption. In alcoholics, hyperhomocysteinemia can increase the risk of various alcohol-related disorders such as: brain atrophy, epileptic seizures during withdrawal, and mood disorders. To evaluate the correlation among serum homocysteine concentrations, craving, hazardous and harmful patterns of alcohol consumption in patients stabilized for withdrawal symptoms. Participants were adult outpatients accessed at the Addiction Treatment Unit. Alcoholism was assessed using the following tools: Mini-International Neuropsychiatric Interview Plus (MINI Plus), Alcohol Use Disorder Identification test (AUDIT), Visual Analogic Scale for craving (VAS). Furthermore, during the first visit a blood sample was taken from all patients to measure the plasma concentration of both homocysteine and Carboxy Deficient Transferrin (CDT). Differences between groups in socio-demographic and clinical characteristics were analyzed using the t-test and the Mann-Whitney's U test for normally and non-normally distributed data, respectively. Correlation between clinical scale scores and plasma concentration of homocysteine and CDT was evaluated using the Pearson's correlation coefficient and the Kendall's Tau-b bivariate correlation coefficient for normally and non-normally distributed data, respectively. Our study included 92 patients. No difference was found in socio-demographic characteristics between groups. The group with high homocysteine had higher prevalence of mood disorders (p < 0.001), plasma CDT percentage (p < 0.001), VAS score (p < 0.001) and AUDIT score (p < 0.001) than group with normal homocysteine. Plasma homocysteine showed a positive correlation with both VAS score (p < 0.001), and AUDIT score (p < 0.05). In our study, plasma homocysteine concentration is associated with craving, hazardous and harmful patterns of alcohol consumption. In particular, homocysteine is correlated with alcoholism in a bidirectional manner because its level appears to be related with alcohol degree, but simultaneously, hyperhomocysteinemia could enhance the alcohol consumption increasing the severity of craving in a circular self reinforcing mechanism. Copyright © 2017 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Assessing the genetic overlap between BMI and cognitive function

PubMed Central

Marioni, R E; Yang, J; Dykiert, D; Mõttus, R; Campbell, A; Ibrahim-Verbaas, Carla A; Bressler, Jan; Debette, Stephanie; Schuur, Maaike; Smith, Albert V; Davies, Gail; Bennett, David A; Deary, Ian J; Ikram, M Arfan; Launer, Lenore J; Fitzpatrick, Annette L; Seshadri, Sudha; van Duijn, Cornelia M; Mosely Jr, Thomas H; Davies, G; Hayward, C; Porteous, D J; Visscher, P M; Deary, I J

2016-01-01

Obesity and low cognitive function are associated with multiple adverse health outcomes across the life course. They have a small phenotypic correlation (r=−0.11; high body mass index (BMI)−low cognitive function), but whether they have a shared genetic aetiology is unknown. We investigated the phenotypic and genetic correlations between the traits using data from 6815 unrelated, genotyped members of Generation Scotland, an ethnically homogeneous cohort from five sites across Scotland. Genetic correlations were estimated using the following: same-sample bivariate genome-wide complex trait analysis (GCTA)–GREML; independent samples bivariate GCTA–GREML using Generation Scotland for cognitive data and four other samples (n=20 806) for BMI; and bivariate LDSC analysis using the largest genome-wide association study (GWAS) summary data on cognitive function (n=48 462) and BMI (n=339 224) to date. The GWAS summary data were also used to create polygenic scores for the two traits, with within- and cross-trait prediction taking place in the independent Generation Scotland cohort. A large genetic correlation of −0.51 (s.e. 0.15) was observed using the same-sample GCTA–GREML approach compared with −0.10 (s.e. 0.08) from the independent-samples GCTA–GREML approach and −0.22 (s.e. 0.03) from the bivariate LDSC analysis. A genetic profile score using cognition-specific genetic variants accounts for 0.08% (P=0.020) of the variance in BMI and a genetic profile score using BMI-specific variants accounts for 0.42% (P=1.9 × 10−7) of the variance in cognitive function. Seven common genetic variants are significantly associated with both traits at P<5 × 10−5, which is significantly more than expected by chance (P=0.007). All these results suggest there are shared genetic contributions to BMI and cognitive function. PMID:26857597

Asymptotics of bivariate generating functions with algebraic singularities

NASA Astrophysics Data System (ADS)

Greenwood, Torin

Flajolet and Odlyzko (1990) derived asymptotic formulae the coefficients of a class of uni- variate generating functions with algebraic singularities. Gao and Richmond (1992) and Hwang (1996, 1998) extended these results to classes of multivariate generating functions, in both cases by reducing to the univariate case. Pemantle and Wilson (2013) outlined new multivariate ana- lytic techniques and used them to analyze the coefficients of rational generating functions. After overviewing these methods, we use them to find asymptotic formulae for the coefficients of a broad class of bivariate generating functions with algebraic singularities. Beginning with the Cauchy integral formula, we explicity deform the contour of integration so that it hugs a set of critical points. The asymptotic contribution to the integral comes from analyzing the integrand near these points, leading to explicit asymptotic formulae. Next, we use this formula to analyze an example from current research. In the following chapter, we apply multivariate analytic techniques to quan- tum walks. Bressler and Pemantle (2007) found a (d + 1)-dimensional rational generating function whose coefficients described the amplitude of a particle at a position in the integer lattice after n steps. Here, the minimal critical points form a curve on the (d + 1)-dimensional unit torus. We find asymptotic formulae for the amplitude of a particle in a given position, normalized by the number of steps n, as n approaches infinity. Each critical point contributes to the asymptotics for a specific normalized position. Using Groebner bases in Maple again, we compute the explicit locations of peak amplitudes. In a scaling window of size the square root of n near the peaks, each amplitude is asymptotic to an Airy function.

Identifying tectonic parameters that affect tsunamigenesis

NASA Astrophysics Data System (ADS)

van Zelst, I.; Brizzi, S.; Heuret, A.; Funiciello, F.; van Dinther, Y.

2016-12-01

The role of tectonics in tsunami generation is at present poorly understood. However, the fact thatsome regions produce more tsunamis than others indicates that tectonics could influencetsunamigenesis. Here, we complement a global earthquake database that contains geometrical,mechanical, and seismicity parameters of subduction zones with tsunami data. We statisticallyanalyse the database to identify the tectonic parameters that affect tsunamigenesis. The Pearson'sproduct-moment correlation coefficients reveal high positive correlations of 0.65 between,amongst others, the maximum water height of tsunamis and the seismic coupling in a subductionzone. However, these correlations are mainly caused by outliers. The Spearman's rank correlationcoefficient results in statistically significant correlations of 0.60 between the number of tsunamisin a subduction zone and subduction velocity (positive correlation) and the sediment thickness atthe trench (negative correlation). Interestingly, there is a positive correlation between the latter andtsunami magnitude. These bivariate statistical methods are extended to a binary decision tree(BDT) and multivariate analysis. Using the BDT, the tectonic parameters that distinguish betweensubduction zones with tsunamigenic and non-tsunamigenic earthquakes are identified. To assessphysical causality of the tectonic parameters with regard to tsunamigenesis, we complement ouranalysis by a numerical study of the most promising parameters using a geodynamic seismic cyclemodel. We show that the inclusion of sediments on the subducting plate results in an increase insplay fault activity, which could lead to larger vertical seafloor displacements due to their steeperdips and hence a larger tsunamigenic potential. We also show that the splay fault is the preferredrupture path for a strongly velocity strengthening friction regime in the shallow part of thesubduction zone, which again increases the tsunamigenic potential.

Development and evaluation of an electromagnetic hypersensitivity questionnaire for Japanese people

PubMed Central

Tokiya, Mikiko; Mizuki, Masami; Miyata, Mikio; Kanatani, Kumiko T.; Takagi, Airi; Tsurikisawa, Naomi; Kame, Setsuko; Katoh, Takahiko; Tsujiuchi, Takuya; Kumano, Hiroaki

2016-01-01

The purpose of the present study was to evaluate the validity and reliability of a Japanese version of an electromagnetic hypersensitivity (EHS) questionnaire, originally developed by Eltiti et al. in the United Kingdom. Using this Japanese EHS questionnaire, surveys were conducted on 1306 controls and 127 self‐selected EHS subjects in Japan. Principal component analysis of controls revealed eight principal symptom groups, namely, nervous, skin‐related, head‐related, auditory and vestibular, musculoskeletal, allergy‐related, sensory, and heart/chest‐related. The reliability of the Japanese EHS questionnaire was confirmed by high to moderate intraclass correlation coefficients in a test–retest analysis, and high Cronbach's α coefficients (0.853–0.953) from each subscale. A comparison of scores of each subscale between self‐selected EHS subjects and age‐ and sex‐matched controls using bivariate logistic regression analysis, Mann–Whitney U‐ and χ 2 tests, verified the validity of the questionnaire. This study demonstrated that the Japanese EHS questionnaire is reliable and valid, and can be used for surveillance of EHS individuals in Japan. Furthermore, based on multiple logistic regression and receiver operating characteristic analyses, we propose specific preliminary criteria for screening EHS individuals in Japan. Bioelectromagnetics. 37:353–372, 2016. © 2016 The Authors. Bioelectromagnetics Published by Wiley Periodicals, Inc. PMID:27324106

Associations Between Physician Empathy, Physician Characteristics, and Standardized Measures of Patient Experience.

PubMed

Chaitoff, Alexander; Sun, Bob; Windover, Amy; Bokar, Daniel; Featherall, Joseph; Rothberg, Michael B; Misra-Hebert, Anita D

2017-10-01

To identify correlates of physician empathy and determine whether physician empathy is related to standardized measures of patient experience. Demographic, professional, and empathy data were collected during 2013-2015 from Cleveland Clinic Health System physicians prior to participation in mandatory communication skills training. Empathy was assessed using the Jefferson Scale of Empathy. Data were also collected for seven measures (six provider communication items and overall provider rating) from the visit-specific and 12-month Consumer Assessment of Healthcare Providers and Systems Clinician and Group (CG-CAHPS) surveys. Associations between empathy and provider characteristics were assessed by linear regression, ANOVA, or a nonparametric equivalent. Significant predictors were included in a multivariable linear regression model. Correlations between empathy and CG-CAHPS scores were assessed using Spearman rank correlation coefficients. In bivariable analysis (n = 847 physicians), female sex (P < .001), specialty (P < .01), outpatient practice setting (P < .05), and DO degree (P < .05) were associated with higher empathy scores. In multivariable analysis, female sex (P < .001) and four specialties (obstetrics-gynecology, pediatrics, psychiatry, and thoracic surgery; all P < .05) were significantly associated with higher empathy scores. Of the seven CG-CAHPS measures, scores on five for the 583 physicians with visit-specific data and on three for the 277 physicians with 12-month data were positively correlated with empathy. Specialty and sex were independently associated with physician empathy. Empathy was correlated with higher scores on multiple CG-CAHPS items, suggesting improving physician empathy might play a role in improving patient experience.

TEMPORAL CORRELATION OF CLASSIFICATIONS IN REMOTE SENSING

EPA Science Inventory

A bivariate binary model is developed for estimating the change in land cover from satellite images obtained at two different times. The binary classifications of a pixel at the two times are modeled as potentially correlated random variables, conditional on the true states of th...

Subjective Age Correlates: A Research Note.

ERIC Educational Resources Information Center

Barak, Benny; Stern, Barbara

1986-01-01

Five types of measures have been used to assess subjective age: identity age, comparative age, feel/age, cognitive age, and stereotype age. Bivariate and multivariate studies revealed four categories of correlates of self-perceived age: biological and physiological, demographic, psychographic and social psychological, and behavioral. (Author/ABB)

The association between body mass index and severe biliary infections: a multivariate analysis.

PubMed

Stewart, Lygia; Griffiss, J McLeod; Jarvis, Gary A; Way, Lawrence W

2012-11-01

Obesity has been associated with worse infectious disease outcomes. It is a risk factor for cholesterol gallstones, but little is known about associations between body mass index (BMI) and biliary infections. We studied this using factors associated with biliary infections. A total of 427 patients with gallstones were studied. Gallstones, bile, and blood (as applicable) were cultured. Illness severity was classified as follows: none (no infection or inflammation), systemic inflammatory response syndrome (fever, leukocytosis), severe (abscess, cholangitis, empyema), or multi-organ dysfunction syndrome (bacteremia, hypotension, organ failure). Associations between BMI and biliary bacteria, bacteremia, gallstone type, and illness severity were examined using bivariate and multivariate analysis. BMI inversely correlated with pigment stones, biliary bacteria, bacteremia, and increased illness severity on bivariate and multivariate analysis. Obesity correlated with less severe biliary infections. BMI inversely correlated with pigment stones and biliary bacteria; multivariate analysis showed an independent correlation between lower BMI and illness severity. Most patients with severe biliary infections had a normal BMI, suggesting that obesity may be protective in biliary infections. This study examined the correlation between BMI and biliary infection severity. Published by Elsevier Inc.

Comparison of the Utility and Validity of Three Scoring Tools to Measure Skin Involvement in Patients With Juvenile Dermatomyositis

PubMed Central

Campanilho‐Marques, Raquel; Almeida, Beverley; Deakin, Claire; Arnold, Katie; Gallot, Natacha; de Iorio, Maria; Nistala, Kiran; Pilkington, Clarissa A.; Armon, Kate; Ellis‐Gage, Joe; Roper, Holly; Briggs, Vanja; Watts, Joanna; McCann, Liza; Roberts, Ian; Baildam, Eileen; Hanna, Louise; Lloyd, Olivia; Riley, Phil; McGovern, Ann; Ryder, Clive; Scott, Janis; Thomas, Beverley; Southwood, Taunton; Al‐Abadi, Eslam; Wyatt, Sue; Jackson, Gillian; Amin, Tania; Wood, Mark; VanRooyen, Vanessa; Burton, Deborah; Davidson, Joyce; Gardner‐Medwin, Janet; Martin, Neil; Ferguson, Sue; Waxman, Liz; Browne, Michael; Friswell, Mark; Foster, Helen; Swift, Alison; Jandial, Sharmila; Stevenson, Vicky; Wade, Debbie; Sen, Ethan; Smith, Eve; Qiao, Lisa; Watson, Stuart; Venning, Helen; Satyapal, Rangaraj; Stretton, Elizabeth; Jordan, Mary; Mosley, Ellen; Frost, Anna; Crate, Lindsay; Warrier, Kishore; Wedderburn, Lucy; Pilkington, Clarissa; Hasson, Nathan; Nistala, Kiran; Maillard, Sue; Halkon, Elizabeth; Brown, Virginia; Juggins, Audrey; Smith, Sally; Lunt, Sian; Enayat, Elli; Varsani, Hemlata; Kassoumeri, Laura; Beard, Laura; Arnold, Katie; Glackin, Yvonne; Simou, Stephanie; Campanilho‐Marques, Raquel; Almeida, Beverley; Murray, Kevin; Ioannou, John; Suffield, Linda; Al‐Obaidi, Muthana; Lee, Helen; Leach, Sam; Smith, Helen; Wilkinson, Nick; Inness, Emma; Kendall, Eunice; Mayers, David; Clinch, Jacqui; Pluess‐Hall, Helen

2016-01-01

Objective To compare the abbreviated Cutaneous Assessment Tool (CAT), Disease Activity Score (DAS), and Myositis Intention to Treat Activity Index (MITAX) and correlate them with the physician's 10‐cm skin visual analog scale (VAS) in order to define which tool best assesses skin disease in patients with juvenile dermatomyositis. Methods A total of 71 patients recruited to the UK Juvenile Dermatomyositis Cohort and Biomarker Study were included and assessed for skin disease using the CAT, DAS, MITAX, and skin VAS. The Childhood Myositis Assessment Scale (CMAS), manual muscle testing of 8 groups (MMT8), muscle enzymes, inflammatory markers, and physician's global VAS were recorded. Relationships were evaluated using Spearman's correlations and predictors with linear regression. Interrater reliability was assessed using intraclass correlation coefficients. Results All 3 tools showed correlation with the physician's global VAS and skin VAS, with DAS skin showing the strongest correlation with skin VAS. DAS skin and CAT activity were inversely correlated with CMAS and MMT8, but these correlations were moderate. No correlations were found between the skin tools and inflammatory markers or muscle enzymes. DAS skin and CAT were the quickest to complete (mean ± SD 0.68 ± 0.1 minutes and 0.63 ± 0.1 minutes, respectively). Conclusion The 3 skin tools were quick and easy to use. The DAS skin correlated best with the skin VAS. The addition of CAT in a bivariate model containing the physician's global VAS was a statistically significant estimator of skin VAS score. We propose that there is scope for a new skin tool to be devised and tested, which takes into account the strengths of the 3 existing tools. PMID:26881696

Toward Establishing Continuity in Linguistic Skills within Early Infancy

ERIC Educational Resources Information Center

Seidl, Amanda; French, Brian; Wang, Yuanyuan; Cristia, Alejandrina

2014-01-01

A growing research line documents significant bivariate correlations between individual measures of speech perception gathered in infancy and concurrent or later vocabulary size. One interpretation of this correlation is that it reflects language specificity: Both speech perception tasks and the development of the vocabulary recruit the…

Modeling animal-vehicle collisions using diagonal inflated bivariate Poisson regression.

PubMed

Lao, Yunteng; Wu, Yao-Jan; Corey, Jonathan; Wang, Yinhai

2011-01-01

Two types of animal-vehicle collision (AVC) data are commonly adopted for AVC-related risk analysis research: reported AVC data and carcass removal data. One issue with these two data sets is that they were found to have significant discrepancies by previous studies. In order to model these two types of data together and provide a better understanding of highway AVCs, this study adopts a diagonal inflated bivariate Poisson regression method, an inflated version of bivariate Poisson regression model, to fit the reported AVC and carcass removal data sets collected in Washington State during 2002-2006. The diagonal inflated bivariate Poisson model not only can model paired data with correlation, but also handle under- or over-dispersed data sets as well. Compared with three other types of models, double Poisson, bivariate Poisson, and zero-inflated double Poisson, the diagonal inflated bivariate Poisson model demonstrates its capability of fitting two data sets with remarkable overlapping portions resulting from the same stochastic process. Therefore, the diagonal inflated bivariate Poisson model provides researchers a new approach to investigating AVCs from a different perspective involving the three distribution parameters (λ(1), λ(2) and λ(3)). The modeling results show the impacts of traffic elements, geometric design and geographic characteristics on the occurrences of both reported AVC and carcass removal data. It is found that the increase of some associated factors, such as speed limit, annual average daily traffic, and shoulder width, will increase the numbers of reported AVCs and carcass removals. Conversely, the presence of some geometric factors, such as rolling and mountainous terrain, will decrease the number of reported AVCs. Published by Elsevier Ltd.

Online Information-Seeking Behaviors of Parents of Children With ADHD.

PubMed

Sage, Adam; Carpenter, Delesha; Sayner, Robyn; Thomas, Kathleen; Mann, Larry; Sulzer, Sandy; Sandler, Adrian; Sleath, Betsy

2018-01-01

This article describes ( a) parent questions about ADHD (attention deficit/hyperactivity disorder), ( b) parent Internet use to seek ADHD information, and ( c) associations between type of Internet access and ADHD information-seeking. Seventy parents of children (ages 7-17 years) with ADHD completed questionnaires after their child's visit with their pediatrician. Bivariate relationships were assessed using chi-square statistics, Pearson correlation coefficients, or t tests. Parents identified an average of 8.9 questions about ADHD for their child's provider. Common questions were related to medication and long-term implications of ADHD. A majority of parents searched the Internet for general ADHD information (87%) and ADHD medication information (81%). White parents accessed the Internet significantly more via home computer, mobile phone, and tablet, and significantly less via public library than non-White parents. Parents who accessed the Internet via home computers and tablets were more likely to search the Internet for ADHD medication information than parents who did not.

An Empirical Examination of the Anomie Theory of Drug Use.

ERIC Educational Resources Information Center

Dull, R. Thomas

1983-01-01

Investigated the relationship between anomie theory, as measured by Srole's Anomie Scale, and self-admitted drug use in an adult population (N=1,449). Bivariate cross-comparison correlations indicated anomie was significantly correlated with several drug variables, but these associations were extremely weak and of little explanatory value.…

Ventilation-perfusion distribution in normal subjects.

PubMed

Beck, Kenneth C; Johnson, Bruce D; Olson, Thomas P; Wilson, Theodore A

2012-09-01

Functional values of LogSD of the ventilation distribution (σ(V)) have been reported previously, but functional values of LogSD of the perfusion distribution (σ(q)) and the coefficient of correlation between ventilation and perfusion (ρ) have not been measured in humans. Here, we report values for σ(V), σ(q), and ρ obtained from wash-in data for three gases, helium and two soluble gases, acetylene and dimethyl ether. Normal subjects inspired gas containing the test gases, and the concentrations of the gases at end-expiration during the first 10 breaths were measured with the subjects at rest and at increasing levels of exercise. The regional distribution of ventilation and perfusion was described by a bivariate log-normal distribution with parameters σ(V), σ(q), and ρ, and these parameters were evaluated by matching the values of expired gas concentrations calculated for this distribution to the measured values. Values of cardiac output and LogSD ventilation/perfusion (Va/Q) were obtained. At rest, σ(q) is high (1.08 ± 0.12). With the onset of ventilation, σ(q) decreases to 0.85 ± 0.09 but remains higher than σ(V) (0.43 ± 0.09) at all exercise levels. Rho increases to 0.87 ± 0.07, and the value of LogSD Va/Q for light and moderate exercise is primarily the result of the difference between the magnitudes of σ(q) and σ(V). With known values for the parameters, the bivariate distribution describes the comprehensive distribution of ventilation and perfusion that underlies the distribution of the Va/Q ratio.

Assessment of Technical Skills in Young Soccer Goalkeepers: Reliability and Validity of Two Goalkeeper-Specific Tests.

PubMed

Rebelo-Gonçalves, Ricardo; Figueiredo, António J; Coelho-E-Silva, Manuel J; Tessitore, Antonio

2016-09-01

The purpose of this study was to evaluate the reproducibility and validity of two new tests designed to examine goalkeeper-specific technique. Twenty-six goalkeepers (14.49 ± 2.52 years old) completed two trial sessions, each separated by one week, to evaluate the reproducibility of the Sprint-Keeper Test (S-Keeper) and the Lateral Shuffle-Keeper Test (LS-Keeper). Construct validity was assessed among forty goalkeepers (14.49 ± 1.71 years old) by competitive level (elite versus non-elite), after controlling for chronological age. All participants were examined in vertical jump (CMJ and CMJ-free arms), acceleration (5-m and 10-m sprint) and goalkeeper-specific technique. The S-Keeper requires the goalkeeper to accelerate during 3 m and dive over a stationary ball after performing a change of direction in a total distance of 10 m. The LS-Keeper involves three changes of direction and a diving save over a stationary ball, in a total distance of 12.55 m. Performance was respectively measured as total time for the right and left sides in each protocol. Bivariate correlations between repeated measures were high and significant (r = 0.835 - 0.912). Test-retest results for the S-Keeper and LS-Keeper showed good reliability (reliability coefficients > 0.88, intra-class correlation coefficient > 0.908 and coefficients of variation < 4.37%), even though participants tended to improve performance when diving to their right side (p < 0.05). Both tests were able to detect significant differences between elite and non-elite goalkeepers, particularly to the left side (p < 0.05). These findings suggest that the S-Keeper and LS-Keeper are reliable and valid tests for assessing goalkeeper-specific technique. Both protocols can be used as a practical tool to provide relevant information about the influence of several components of performance in the overall execution of a diving save, particularly movement patterns, take-off movements and possible asymmetries.

Correlation of hard X-ray and type 3 bursts in solar flares

NASA Technical Reports Server (NTRS)

Petrosian, V.; Leach, J.

1982-01-01

Correlations between X-ray and type 3 radio emission of solar bursts are described through a bivariate distribution function. Procedures for determining the form of this distribution are described. A model is constructed to explain the correlation between the X-ray spectral index and the ratio of X-ray to radio intensities. Implications of the model are discussed.

A Correlational Study of iPad Efficacy and 21st Century Teaching among Elementary School Teachers

ERIC Educational Resources Information Center

Shultz, Christopher F.

2017-01-01

This study was a longitudinal correlational study that applied the quantitative methodology of bi-variate correlation as well as a paired-samples "t"-test to the data. The purpose was to study the nature of the relationship between iPad efficacy, 21st century teaching, teacher efficacy, and teacher characteristics. The study also…

Nonlinear bivariate dependency of price-volume relationships in agricultural commodity futures markets: A perspective from Multifractal Detrended Cross-Correlation Analysis

NASA Astrophysics Data System (ADS)

He, Ling-Yun; Chen, Shu-Peng

2011-01-01

Nonlinear dependency between characteristic financial and commodity market quantities (variables) is crucially important, especially between trading volume and market price. Studies on nonlinear dependency between price and volume can provide practical insights into market trading characteristics, as well as the theoretical understanding of market dynamics. Actually, nonlinear dependency and its underlying dynamical mechanisms between price and volume can help researchers and technical analysts in understanding the market dynamics by integrating the market variables, instead of investigating them in the current literature. Therefore, for investigating nonlinear dependency of price-volume relationships in agricultural commodity futures markets in China and the US, we perform a new statistical test to detect cross-correlations and apply a new methodology called Multifractal Detrended Cross-Correlation Analysis (MF-DCCA), which is an efficient algorithm to analyze two spatially or temporally correlated time series. We discuss theoretically the relationship between the bivariate cross-correlation exponent and the generalized Hurst exponents for time series of respective variables. We also perform an empirical study and find that there exists a power-law cross-correlation between them, and that multifractal features are significant in all the analyzed agricultural commodity futures markets.

Correlation of USMLE Step 1 scores with performance on dermatology in-training examinations.

PubMed

Fening, Katherine; Vander Horst, Anthony; Zirwas, Matthew

2011-01-01

Although United States Medical Licensing Examination (USMLE) Step 1 was not designed to predict resident performance, scores are used to compare residency applicants. Multiple studies have displayed a significant correlation among Step 1 scores, in-training examination (ITE) scores, and board passage, although no such studies have been performed in dermatology. The purpose of this study is to determine if this correlation exists in dermatology, and how much of the variability in ITE scores is a result of differences in Step 1 scores. This study also seeks to determine if it is appropriate to individualize expectations for resident ITE performance. This project received institutional review board exemption. From 5 dermatology residency programs (86 residents), we collected Step 1 and ITE scores for each of the 3 years of dermatology residency, and recorded passage/failure on boards. Bivariate Pearson correlation analysis was used to assess correlation between USMLE and ITE scores. Ordinary least squares regression was computed to determine how much USMLE scores contribute to ITE variability. USMLE and ITE score correlations were highly significant (P < .001). Correlation coefficients with USMLE were: 0.467, 0.541, and 0.527 for ITE in years 1, 2, and 3, respectively. Variability in ITE scores caused by differences in USMLE scores were: ITE first-year residency = 21.8%, ITE second-year residency = 29.3%, and ITE third-year residency = 27.8%. This study had a relatively small sample size, with data from only 5 programs. There is a moderate correlation between USMLE and ITE scores, with USMLE scores explaining ∼26% of the variability in ITE scores. Copyright © 2009 American Academy of Dermatology, Inc. Published by Mosby, Inc. All rights reserved.

A bivariate contaminated binormal model for robust fitting of proper ROC curves to a pair of correlated, possibly degenerate, ROC datasets.

PubMed

Zhai, Xuetong; Chakraborty, Dev P

2017-06-01

The objective was to design and implement a bivariate extension to the contaminated binormal model (CBM) to fit paired receiver operating characteristic (ROC) datasets-possibly degenerate-with proper ROC curves. Paired datasets yield two correlated ratings per case. Degenerate datasets have no interior operating points and proper ROC curves do not inappropriately cross the chance diagonal. The existing method, developed more than three decades ago utilizes a bivariate extension to the binormal model, implemented in CORROC2 software, which yields improper ROC curves and cannot fit degenerate datasets. CBM can fit proper ROC curves to unpaired (i.e., yielding one rating per case) and degenerate datasets, and there is a clear scientific need to extend it to handle paired datasets. In CBM, nondiseased cases are modeled by a probability density function (pdf) consisting of a unit variance peak centered at zero. Diseased cases are modeled with a mixture distribution whose pdf consists of two unit variance peaks, one centered at positive μ with integrated probability α, the mixing fraction parameter, corresponding to the fraction of diseased cases where the disease was visible to the radiologist, and one centered at zero, with integrated probability (1-α), corresponding to disease that was not visible. It is shown that: (a) for nondiseased cases the bivariate extension is a unit variances bivariate normal distribution centered at (0,0) with a specified correlation ρ 1 ; (b) for diseased cases the bivariate extension is a mixture distribution with four peaks, corresponding to disease not visible in either condition, disease visible in only one condition, contributing two peaks, and disease visible in both conditions. An expression for the likelihood function is derived. A maximum likelihood estimation (MLE) algorithm, CORCBM, was implemented in the R programming language that yields parameter estimates and the covariance matrix of the parameters, and other statistics. A limited simulation validation of the method was performed. CORCBM and CORROC2 were applied to two datasets containing nine readers each contributing paired interpretations. CORCBM successfully fitted the data for all readers, whereas CORROC2 failed to fit a degenerate dataset. All fits were visually reasonable. All CORCBM fits were proper, whereas all CORROC2 fits were improper. CORCBM and CORROC2 were in agreement (a) in declaring only one of the nine readers as having significantly different performances in the two modalities; (b) in estimating higher correlations for diseased cases than for nondiseased ones; and (c) in finding that the intermodality correlation estimates for nondiseased cases were consistent between the two methods. All CORCBM fits yielded higher area under curve (AUC) than the CORROC2 fits, consistent with the fact that a proper ROC model like CORCBM is based on a likelihood-ratio-equivalent decision variable, and consequently yields higher performance than the binormal model-based CORROC2. The method gave satisfactory fits to four simulated datasets. CORCBM is a robust method for fitting paired ROC datasets, always yielding proper ROC curves, and able to fit degenerate datasets. © 2017 American Association of Physicists in Medicine.

Statistical analysis of multivariate atmospheric variables. [cloud cover

NASA Technical Reports Server (NTRS)

Tubbs, J. D.

1979-01-01

Topics covered include: (1) estimation in discrete multivariate distributions; (2) a procedure to predict cloud cover frequencies in the bivariate case; (3) a program to compute conditional bivariate normal parameters; (4) the transformation of nonnormal multivariate to near-normal; (5) test of fit for the extreme value distribution based upon the generalized minimum chi-square; (6) test of fit for continuous distributions based upon the generalized minimum chi-square; (7) effect of correlated observations on confidence sets based upon chi-square statistics; and (8) generation of random variates from specified distributions.

Dynamics of intracranial electroencephalographic recordings from epilepsy patients using univariate and bivariate recurrence networks.

PubMed

Subramaniyam, Narayan Puthanmadam; Hyttinen, Jari

2015-02-01

Recently Andrezejak et al. combined the randomness and nonlinear independence test with iterative amplitude adjusted Fourier transform (iAAFT) surrogates to distinguish between the dynamics of seizure-free intracranial electroencephalographic (EEG) signals recorded from epileptogenic (focal) and nonepileptogenic (nonfocal) brain areas of epileptic patients. However, stationarity is a part of the null hypothesis for iAAFT surrogates and thus nonstationarity can violate the null hypothesis. In this work we first propose the application of the randomness and nonlinear independence test based on recurrence network measures to distinguish between the dynamics of focal and nonfocal EEG signals. Furthermore, we combine these tests with both iAAFT and truncated Fourier transform (TFT) surrogate methods, which also preserves the nonstationarity of the original data in the surrogates along with its linear structure. Our results indicate that focal EEG signals exhibit an increased degree of structural complexity and interdependency compared to nonfocal EEG signals. In general, we find higher rejections for randomness and nonlinear independence tests for focal EEG signals compared to nonfocal EEG signals. In particular, the univariate recurrence network measures, the average clustering coefficient C and assortativity R, and the bivariate recurrence network measure, the average cross-clustering coefficient C(cross), can successfully distinguish between the focal and nonfocal EEG signals, even when the analysis is restricted to nonstationary signals, irrespective of the type of surrogates used. On the other hand, we find that the univariate recurrence network measures, the average path length L, and the average betweenness centrality BC fail to distinguish between the focal and nonfocal EEG signals when iAAFT surrogates are used. However, these two measures can distinguish between focal and nonfocal EEG signals when TFT surrogates are used for nonstationary signals. We also report an improvement in the performance of nonlinear prediction error N and nonlinear interdependence measure L used by Andrezejak et al., when TFT surrogates are used for nonstationary EEG signals. We also find that the outcome of the nonlinear independence test based on the average cross-clustering coefficient C(cross) is independent of the outcome of the randomness test based on the average clustering coefficient C. Thus, the univariate and bivariate recurrence network measures provide independent information regarding the dynamics of the focal and nonfocal EEG signals. In conclusion, recurrence network analysis combined with nonstationary surrogates can be applied to derive reliable biomarkers to distinguish between epileptogenic and nonepileptogenic brain areas using EEG signals.

Dynamics of intracranial electroencephalographic recordings from epilepsy patients using univariate and bivariate recurrence networks

NASA Astrophysics Data System (ADS)

Subramaniyam, Narayan Puthanmadam; Hyttinen, Jari

2015-02-01

Recently Andrezejak et al. combined the randomness and nonlinear independence test with iterative amplitude adjusted Fourier transform (iAAFT) surrogates to distinguish between the dynamics of seizure-free intracranial electroencephalographic (EEG) signals recorded from epileptogenic (focal) and nonepileptogenic (nonfocal) brain areas of epileptic patients. However, stationarity is a part of the null hypothesis for iAAFT surrogates and thus nonstationarity can violate the null hypothesis. In this work we first propose the application of the randomness and nonlinear independence test based on recurrence network measures to distinguish between the dynamics of focal and nonfocal EEG signals. Furthermore, we combine these tests with both iAAFT and truncated Fourier transform (TFT) surrogate methods, which also preserves the nonstationarity of the original data in the surrogates along with its linear structure. Our results indicate that focal EEG signals exhibit an increased degree of structural complexity and interdependency compared to nonfocal EEG signals. In general, we find higher rejections for randomness and nonlinear independence tests for focal EEG signals compared to nonfocal EEG signals. In particular, the univariate recurrence network measures, the average clustering coefficient C and assortativity R , and the bivariate recurrence network measure, the average cross-clustering coefficient Ccross, can successfully distinguish between the focal and nonfocal EEG signals, even when the analysis is restricted to nonstationary signals, irrespective of the type of surrogates used. On the other hand, we find that the univariate recurrence network measures, the average path length L , and the average betweenness centrality BC fail to distinguish between the focal and nonfocal EEG signals when iAAFT surrogates are used. However, these two measures can distinguish between focal and nonfocal EEG signals when TFT surrogates are used for nonstationary signals. We also report an improvement in the performance of nonlinear prediction error N and nonlinear interdependence measure L used by Andrezejak et al., when TFT surrogates are used for nonstationary EEG signals. We also find that the outcome of the nonlinear independence test based on the average cross-clustering coefficient Ccross is independent of the outcome of the randomness test based on the average clustering coefficient C . Thus, the univariate and bivariate recurrence network measures provide independent information regarding the dynamics of the focal and nonfocal EEG signals. In conclusion, recurrence network analysis combined with nonstationary surrogates can be applied to derive reliable biomarkers to distinguish between epileptogenic and nonepileptogenic brain areas using EEG signals.

Mortality prediction of head Abbreviated Injury Score and Glasgow Coma Scale: analysis of 7,764 head injuries.

PubMed

Demetriades, Demetrios; Kuncir, Eric; Murray, James; Velmahos, George C; Rhee, Peter; Chan, Linda

2004-08-01

We assessed the prognostic value and limitations of Glasgow Coma Scale (GCS) and head Abbreviated Injury Score (AIS) and correlated head AIS with GCS. We studied 7,764 patients with head injuries. Bivariate analysis was performed to examine the relationship of GCS, head AIS, age, gender, and mechanism of injury with mortality. Stepwise logistic regression analysis was used to identify the independent risk factors associated with mortality. The overall mortality in the group of head injury patients with no other major extracranial injuries and no hypotension on admission was 9.3%. Logistic regression analysis identified head AIS, GCS, age, and mechanism of injury as significant independent risk factors of death. The prognostic value of GCS and head AIS was significantly affected by the mechanism of injury and the age of the patient. Patients with similar GCS or head AIS but different mechanisms of injury or ages had significantly different outcomes. The adjusted odds ratio of death in penetrating trauma was 5.2 (3.9, 7.0), p < 0.0001, and in the age group > or = 55 years the adjusted odds ratio was 3.4 (2.6, 4.6), p < 0.0001. There was no correlation between head AIS and GCS (correlation coefficient -0.31). Mechanism of injury and age have a major effect in the predictive value of GCS and head AIS. There is no good correlation between GCS and head AIS.

Multivariate modelling of endophenotypes associated with the metabolic syndrome in Chinese twins.

PubMed

Pang, Z; Zhang, D; Li, S; Duan, H; Hjelmborg, J; Kruse, T A; Kyvik, K O; Christensen, K; Tan, Q

2010-12-01

The common genetic and environmental effects on endophenotypes related to the metabolic syndrome have been investigated using bivariate and multivariate twin models. This paper extends the pairwise analysis approach by introducing independent and common pathway models to Chinese twin data. The aim was to explore the common genetic architecture in the development of these phenotypes in the Chinese population. Three multivariate models including the full saturated Cholesky decomposition model, the common factor independent pathway model and the common factor common pathway model were fitted to 695 pairs of Chinese twins representing six phenotypes including BMI, total cholesterol, total triacylglycerol, fasting glucose, HDL and LDL. Performances of the nested models were compared with that of the full Cholesky model. Cross-phenotype correlation coefficients gave clear indication of common genetic or environmental backgrounds in the phenotypes. Decomposition of phenotypic correlation by the Cholesky model revealed that the observed phenotypic correlation among lipid phenotypes had genetic and unique environmental backgrounds. Both pathway models suggest a common genetic architecture for lipid phenotypes, which is distinct from that of the non-lipid phenotypes. The declining performance with model restriction indicates biological heterogeneity in development among some of these phenotypes. Our multivariate analyses revealed common genetic and environmental backgrounds for the studied lipid phenotypes in Chinese twins. Model performance showed that physiologically distinct endophenotypes may follow different genetic regulations.

Powerful Bivariate Genome-Wide Association Analyses Suggest the SOX6 Gene Influencing Both Obesity and Osteoporosis Phenotypes in Males

PubMed Central

Liu, Yao-Zhong; Pei, Yu-Fang; Liu, Jian-Feng; Yang, Fang; Guo, Yan; Zhang, Lei; Liu, Xiao-Gang; Yan, Han; Wang, Liang; Zhang, Yin-Ping; Levy, Shawn; Recker, Robert R.; Deng, Hong-Wen

2009-01-01

Background Current genome-wide association studies (GWAS) are normally implemented in a univariate framework and analyze different phenotypes in isolation. This univariate approach ignores the potential genetic correlation between important disease traits. Hence this approach is difficult to detect pleiotropic genes, which may exist for obesity and osteoporosis, two common diseases of major public health importance that are closely correlated genetically. Principal Findings To identify such pleiotropic genes and the key mechanistic links between the two diseases, we here performed the first bivariate GWAS of obesity and osteoporosis. We searched for genes underlying co-variation of the obesity phenotype, body mass index (BMI), with the osteoporosis risk phenotype, hip bone mineral density (BMD), scanning ∼380,000 SNPs in 1,000 unrelated homogeneous Caucasians, including 499 males and 501 females. We identified in the male subjects two SNPs in intron 1 of the SOX6 (SRY-box 6) gene, rs297325 and rs4756846, which were bivariately associated with both BMI and hip BMD, achieving p values of 6.82×10−7 and 1.47×10−6, respectively. The two SNPs ranked at the top in significance for bivariate association with BMI and hip BMD in the male subjects among all the ∼380,000 SNPs examined genome-wide. The two SNPs were replicated in a Framingham Heart Study (FHS) cohort containing 3,355 Caucasians (1,370 males and 1,985 females) from 975 families. In the FHS male subjects, the two SNPs achieved p values of 0.03 and 0.02, respectively, for bivariate association with BMI and femoral neck BMD. Interestingly, SOX6 was previously found to be essential to both cartilage formation/chondrogenesis and obesity-related insulin resistance, suggesting the gene's dual role in both bone and fat. Conclusions Our findings, together with the prior biological evidence, suggest the SOX6 gene's importance in co-regulation of obesity and osteoporosis. PMID:19714249

Multidimensional stock network analysis: An Escoufier's RV coefficient approach

NASA Astrophysics Data System (ADS)

Lee, Gan Siew; Djauhari, Maman A.

2013-09-01

The current practice of stocks network analysis is based on the assumption that the time series of closed stock price could represent the behaviour of the each stock. This assumption leads to consider minimal spanning tree (MST) and sub-dominant ultrametric (SDU) as an indispensible tool to filter the economic information contained in the network. Recently, there is an attempt where researchers represent stock not only as a univariate time series of closed price but as a bivariate time series of closed price and volume. In this case, they developed the so-called multidimensional MST to filter the important economic information. However, in this paper, we show that their approach is only applicable for that bivariate time series only. This leads us to introduce a new methodology to construct MST where each stock is represented by a multivariate time series. An example of Malaysian stock exchange will be presented and discussed to illustrate the advantages of the method.

Milestone Ratings and Supervisory Role Categorizations Swim Together, but is the Water Muddy?

PubMed

Schumacher, Daniel J; Bartlett, Kathleen W; Elliott, Sean P; Michelson, Catherine; Sharma, Tanvi; Garfunkel, Lynn C; King, Beth; Schwartz, Alan

2018-06-17

This single specialty, multi-institutional study aimed to determine: 1) the association between milestone ratings for individual competencies and average milestone ratings (AMRs) and 2) the association between AMRs and recommended supervisory role categorizations made by individual clinical competency committee (CCC) members. During the 2015-16 academic year, CCC members at 14 pediatric residencies reported milestone ratings for 21 competencies and recommended supervisory role categories (may not supervise, may supervise in some settings, may supervise in all settings) for residents they reviewed. An exploratory factor analysis of competencies was conducted. The associations between individual competencies, the AMR, and supervisory role categorizations were determined by computing bivariate correlations. The relationship between AMRs and recommended supervisory role categorizations was examined using an ordinal mixed logistic regression model. 68/155 CCC members completed both milestone assignments and supervision categorizations for 451 residents. Factor analysis of individual competencies controlling for clustering of residents in raters and sites resulted in a single-factor solution (cumulative variance 0.75). All individual competencies had large positive correlations with the AMR (correlation coefficient: 0.84-0.93), except for two professionalism competencies (Prof1: 0.63 and Prof4: 0.65). When combined across training year and time points, the AMR and supervisory role categorization had a moderately positive correlation (0.56). This exploratory study identified a modest correlation between average milestone ratings and supervisory role categorization. Convergence of competencies on a single factor deserves further exploration, with possible rater effects warranting attention. Copyright © 2018. Published by Elsevier Inc.

Influence of geomagnetic activity and atmospheric pressure in hypertensive adults.

PubMed

Azcárate, T; Mendoza, B

2017-09-01

We performed a study of the systolic and diastolic arterial blood pressure behavior under natural variables such as the atmospheric pressure and the horizontal geomagnetic field component. We worked with a group of eight adult hypertensive volunteers, four men and four women, with ages between 18 and 27 years in Mexico City during a geomagnetic storm in 2014. The data was divided by gender, age, and day/night cycle. We studied the time series using three methods: correlations, bivariate analysis, and superposed epoch (within a window of 2 days around the day of occurrence of a geomagnetic storm) analysis, between the systolic and diastolic blood pressure and the natural variables. The correlation analysis indicated a correlation between the systolic and diastolic blood pressure and the atmospheric pressure and the horizontal geomagnetic field component, being the largest during the night. Furthermore, the correlation and bivariate analyses showed that the largest correlations are between the systolic and diastolic blood pressure and the horizontal geomagnetic field component. Finally, the superposed epoch analysis showed that the largest number of significant changes in the blood pressure under the influence of geomagnetic field occurred in the systolic blood pressure for men.

Influence of geomagnetic activity and atmospheric pressure in hypertensive adults

NASA Astrophysics Data System (ADS)

Azcárate, T.; Mendoza, B.

2017-09-01

We performed a study of the systolic and diastolic arterial blood pressure behavior under natural variables such as the atmospheric pressure and the horizontal geomagnetic field component. We worked with a group of eight adult hypertensive volunteers, four men and four women, with ages between 18 and 27 years in Mexico City during a geomagnetic storm in 2014. The data was divided by gender, age, and day/night cycle. We studied the time series using three methods: correlations, bivariate analysis, and superposed epoch (within a window of 2 days around the day of occurrence of a geomagnetic storm) analysis, between the systolic and diastolic blood pressure and the natural variables. The correlation analysis indicated a correlation between the systolic and diastolic blood pressure and the atmospheric pressure and the horizontal geomagnetic field component, being the largest during the night. Furthermore, the correlation and bivariate analyses showed that the largest correlations are between the systolic and diastolic blood pressure and the horizontal geomagnetic field component. Finally, the superposed epoch analysis showed that the largest number of significant changes in the blood pressure under the influence of geomagnetic field occurred in the systolic blood pressure for men.

Ecologically relevant outcome measure for post-inpatient rehabilitation.

PubMed

Marquez de la Plata, Carlos; Qualls, Devin; Plenger, Patrick; Malec, James F; Hayden, Mary Ellen

2017-01-01

Transfer of skills learned within the clinic environment to patients' home or community is important in post-inpatient brain injury rehabilitation (PBIR). Outcome measures used in PBIR assess level of independence during functional tasks; however, available functional instruments do not quantitate the environment in which the behaviors occur. To examine the reliability and validity of an instrument used to assess patients' functional abilities while quantifying the amount of structure and distractions in the environment. 2501 patients who sustained a traumatic brain injury (TBI) or cerebrovascular accident (CVA) and participated in a multidisciplinary PBIR program between 2006 and 2014 were identified retrospectively for this study. The PERPOS and MPAI-4 were used to assess functional abilities at admission and at discharge. Construct validity was assessed using a bivariate Spearman rho analysis A subsample of 56 consecutive admissions during 2014 were examined to determine inter-rater reliability. Intra-class correlation coefficient (ICC) and Kappa coefficients assessed inter-rater agreement of the total PERPOS and PERPOS subscales respectively. The PERPOS and MPAI-4 demonstrated a strong negative association among both TBI and CVA patients. Kappa scores for the three PERPOS scales each demonstrated good to excellent inter-rater agreement. The ICC for overall PERPOS scores fell in the good agreement range. The PERPOS can be used reliably in PBIR to quantify patients' functional abilities within the context of environmental demands.

A New Method for the Evaluation and Prediction of Base Stealing Performance.

PubMed

Bricker, Joshua C; Bailey, Christopher A; Driggers, Austin R; McInnis, Timothy C; Alami, Arya

2016-11-01

Bricker, JC, Bailey, CA, Driggers, AR, McInnis, TC, and Alami, A. A new method for the evaluation and prediction of base stealing performance. J Strength Cond Res 30(11): 3044-3050, 2016-The purposes of this study were to evaluate a new method using electronic timing gates to monitor base stealing performance in terms of reliability, differences between it and traditional stopwatch-collected times, and its ability to predict base stealing performance. Twenty-five healthy collegiate baseball players performed maximal effort base stealing trials with a right and left-handed pitcher. An infrared electronic timing system was used to calculate the reaction time (RT) and total time (TT), whereas coaches' times (CT) were recorded with digital stopwatches. Reliability of the TGM was evaluated with intraclass correlation coefficients (ICCs) and coefficient of variation (CV). Differences between the TGM and traditional CT were calculated with paired samples t tests Cohen's d effect size estimates. Base stealing performance predictability of the TGM was evaluated with Pearson's bivariate correlations. Acceptable relative reliability was observed (ICCs 0.74-0.84). Absolute reliability measures were acceptable for TT (CVs = 4.4-4.8%), but measures were elevated for RT (CVs = 32.3-35.5%). Statistical and practical differences were found between TT and CT (right p = 0.00, d = 1.28 and left p = 0.00, d = 1.49). The TGM TT seems to be a decent predictor of base stealing performance (r = -0.49 to -0.61). The authors recommend using the TGM used in this investigation for athlete monitoring because it was found to be reliable, seems to be more precise than traditional CT measured with a stopwatch, provides an additional variable of value (RT), and may predict future performance.

General Health status of workers among different workplaces in Qom Province, Iran

PubMed Central

Koohpaei, Alireza; Khandan, Mohammad; Gaeeni, Mahdi; Momenyan, Somayeh

2015-01-01

Introduction In a healthy organization, psychological health and physical health are as important as production and productivity; and healthy workers have higher productivity. Regarding lack of information about workers’ general health profile in Qom Province, this study aimed to assess and compare the staffs’ general health and its components among different workplaces in 2014. Methods In a cross-sectional study, 2,276 employees working at 46 industries and organizations completed a standardized General Health Questionnaire (GHQ 28) and a demographic questionnaire. Data were analyzed using t-test, ANOVA, and Pearson product-moment correlation coefficient by IBM SPSS version 20. Results The mean age of the participants was 32.22 (±7.55) years. Seventy-nine point four percent of participants were married and the rest were single. Highest and lowest scores belonged to social dysfunction and depression, respectively. Also, total score of staffs’ general health was 17.87 ± 10.93. The results showed that, in spite of the non-relationship between general health score difference among married and single personnel (p > 0.05), there was a significant difference between men and women and among organizations and industries with regards to general health score (p < 0.05), and drivers had the most difference with others. The relationship between workers’ ages and GH was significant (p < 0.05, Pearson’s bivariate correlation coefficient = −0.05). Conclusion The findings of this study collectively indicated that participants had an acceptable condition for mental factors, such as depression, but not in viewpoints of social dysfunction. In other words, staffs’ interfaces with circumstances and personal innovation/creativity in the workplaces are at risk. Altogether, the general health score in the studied population was suitable in its entirety. PMID:26813624

General Health status of workers among different workplaces in Qom Province, Iran.

PubMed

Koohpaei, Alireza; Khandan, Mohammad; Gaeeni, Mahdi; Momenyan, Somayeh

2015-12-01

In a healthy organization, psychological health and physical health are as important as production and productivity; and healthy workers have higher productivity. Regarding lack of information about workers' general health profile in Qom Province, this study aimed to assess and compare the staffs' general health and its components among different workplaces in 2014. In a cross-sectional study, 2,276 employees working at 46 industries and organizations completed a standardized General Health Questionnaire (GHQ 28) and a demographic questionnaire. Data were analyzed using t-test, ANOVA, and Pearson product-moment correlation coefficient by IBM SPSS version 20. The mean age of the participants was 32.22 (±7.55) years. Seventy-nine point four percent of participants were married and the rest were single. Highest and lowest scores belonged to social dysfunction and depression, respectively. Also, total score of staffs' general health was 17.87 ± 10.93. The results showed that, in spite of the non-relationship between general health score difference among married and single personnel (p > 0.05), there was a significant difference between men and women and among organizations and industries with regards to general health score (p < 0.05), and drivers had the most difference with others. The relationship between workers' ages and GH was significant (p < 0.05, Pearson's bivariate correlation coefficient = -0.05). The findings of this study collectively indicated that participants had an acceptable condition for mental factors, such as depression, but not in viewpoints of social dysfunction. In other words, staffs' interfaces with circumstances and personal innovation/creativity in the workplaces are at risk. Altogether, the general health score in the studied population was suitable in its entirety.

Evaluating Dynamic Bivariate Correlations in Resting-state fMRI: A comparison study and a new approach

PubMed Central

Lindquist, Martin A.; Xu, Yuting; Nebel, Mary Beth; Caffo, Brain S.

2014-01-01

To date, most functional Magnetic Resonance Imaging (fMRI) studies have assumed that the functional connectivity (FC) between time series from distinct brain regions is constant across time. However, recently, there has been increased interest in quantifying possible dynamic changes in FC during fMRI experiments, as it is thought this may provide insight into the fundamental workings of brain networks. In this work we focus on the specific problem of estimating the dynamic behavior of pair-wise correlations between time courses extracted from two different regions of the brain. We critique the commonly used sliding-windows technique, and discuss some alternative methods used to model volatility in the finance literature that could also prove useful in the neuroimaging setting. In particular, we focus on the Dynamic Conditional Correlation (DCC) model, which provides a model-based approach towards estimating dynamic correlations. We investigate the properties of several techniques in a series of simulation studies and find that DCC achieves the best overall balance between sensitivity and specificity in detecting dynamic changes in correlations. We also investigate its scalability beyond the bivariate case to demonstrate its utility for studying dynamic correlations between more than two brain regions. Finally, we illustrate its performance in an application to test-retest resting state fMRI data. PMID:24993894

Bivariate Heritability of Total and Regional Brain Volumes: the Framingham Study

PubMed Central

DeStefano, Anita L.; Seshadri, Sudha; Beiser, Alexa; Atwood, Larry D.; Massaro, Joe M.; Au, Rhoda; Wolf, Philip A.; DeCarli, Charles

2009-01-01

Heritability and genetic and environmental correlations of total and regional brain volumes were estimated from a large, generally healthy, community-based sample, to determine if there are common elements to the genetic influence of brain volumes and white matter hyperintensity volume. There were 1538 Framingham Heart Study participants with brain volume measures from quantitative magnetic resonance imaging (MRI) who were free of stroke and other neurological disorders that might influence brain volumes and who were members of families with at least two Framingham Heart Study participants. Heritability was estimated using variance component methodology and adjusting for the components of the Framingham stroke risk profile. Genetic and environmental correlations between traits were obtained from bivariate analysis. Heritability estimates ranging from 0.46 to 0.60, were observed for total brain, white matter hyperintensity, hippocampal, temporal lobe, and lateral ventricular volumes. Moderate, yet significant, heritability was observed for the other measures. Bivariate analyses demonstrated that relationships between brain volume measures, except for white matter hyperintensity, reflected both moderate to strong shared genetic and shared environmental influences. This study confirms strong genetic effects on brain and white matter hyperintensity volumes. These data extend current knowledge by showing that these two different types of MRI measures do not share underlying genetic or environmental influences. PMID:19812462

Correlation between the sudden jump-like increases of the atrio-Hisian interval induced during burst atrial pacing and during programmed atrial stimulation in patients with atrioventricular nodal reentrant tachycardia.

PubMed

Bayraktarova, Iskra H; Stoyanov, Milko K; Kunev, Boyan T; Shalganov, Tchavdar N

To study the correlation between the sudden prolongations of the atrio-Hisian (AH) interval with ≥50 ms during burst and programmed atrial stimulation, and to define whether the AH jump during burst atrial pacing is a reliable diagnostic criterion for dual AV nodal physiology. Retrospective data on 304 patients with preliminary ECG diagnosis of AV nodal reentrant tachycardia (AVNRT), confirmed during electrophysiological study, was analyzed for the presence of AH jump during burst and programmed atrial stimulation, and for correlation between the pacing modes for inducing the jump. Wilcoxon signed-ranks test and Spearman's bivariate correlation coefficient were applied, significant was P-value <0.05. The population was aged 48.5 ± 15.7 (12-85) years; males were 38.5%. AH jump occurred during burst atrial pacing in 81% of the patients, and during programmed stimulation - in 78%, P = 0.366. In 63.2% AH jump was induced by both pacing modes; in 17.8% - only by burst pacing; in 14.8% - only by programmed pacing; in 4.2% there was no inducible jump. There was negative correlation between both pacing modes, ρ = -0.204, Р<0.001. Burst and programmed atrial stimulation separately prove the presence of dual AV nodal physiology in 81 and 78% of the patients with AVNRT, respectively. There is negative correlation between the two pacing modes, allowing the combination of the two methods to prove diagnostic in 95.8% of the patients. Copyright © 2017 Indian Heart Rhythm Society. Production and hosting by Elsevier B.V. All rights reserved.

Univariate and bivariate likelihood-based meta-analysis methods performed comparably when marginal sensitivity and specificity were the targets of inference.

PubMed

Dahabreh, Issa J; Trikalinos, Thomas A; Lau, Joseph; Schmid, Christopher H

2017-03-01

To compare statistical methods for meta-analysis of sensitivity and specificity of medical tests (e.g., diagnostic or screening tests). We constructed a database of PubMed-indexed meta-analyses of test performance from which 2 × 2 tables for each included study could be extracted. We reanalyzed the data using univariate and bivariate random effects models fit with inverse variance and maximum likelihood methods. Analyses were performed using both normal and binomial likelihoods to describe within-study variability. The bivariate model using the binomial likelihood was also fit using a fully Bayesian approach. We use two worked examples-thoracic computerized tomography to detect aortic injury and rapid prescreening of Papanicolaou smears to detect cytological abnormalities-to highlight that different meta-analysis approaches can produce different results. We also present results from reanalysis of 308 meta-analyses of sensitivity and specificity. Models using the normal approximation produced sensitivity and specificity estimates closer to 50% and smaller standard errors compared to models using the binomial likelihood; absolute differences of 5% or greater were observed in 12% and 5% of meta-analyses for sensitivity and specificity, respectively. Results from univariate and bivariate random effects models were similar, regardless of estimation method. Maximum likelihood and Bayesian methods produced almost identical summary estimates under the bivariate model; however, Bayesian analyses indicated greater uncertainty around those estimates. Bivariate models produced imprecise estimates of the between-study correlation of sensitivity and specificity. Differences between methods were larger with increasing proportion of studies that were small or required a continuity correction. The binomial likelihood should be used to model within-study variability. Univariate and bivariate models give similar estimates of the marginal distributions for sensitivity and specificity. Bayesian methods fully quantify uncertainty and their ability to incorporate external evidence may be useful for imprecisely estimated parameters. Copyright © 2017 Elsevier Inc. All rights reserved.

CI2 for creating and comparing confidence-intervals for time-series bivariate plots.

PubMed

Mullineaux, David R

2017-02-01

Currently no method exists for calculating and comparing the confidence-intervals (CI) for the time-series of a bivariate plot. The study's aim was to develop 'CI2' as a method to calculate the CI on time-series bivariate plots, and to identify if the CI between two bivariate time-series overlap. The test data were the knee and ankle angles from 10 healthy participants running on a motorised standard-treadmill and non-motorised curved-treadmill. For a recommended 10+ trials, CI2 involved calculating 95% confidence-ellipses at each time-point, then taking as the CI the points on the ellipses that were perpendicular to the direction vector between the means of two adjacent time-points. Consecutive pairs of CI created convex quadrilaterals, and any overlap of these quadrilaterals at the same time or ±1 frame as a time-lag calculated using cross-correlations, indicated where the two time-series differed. CI2 showed no group differences between left and right legs on both treadmills, but the same legs between treadmills for all participants showed differences of less knee extension on the curved-treadmill before heel-strike. To improve and standardise the use of CI2 it is recommended to remove outlier time-series, use 95% confidence-ellipses, and scale the ellipse by the fixed Chi-square value as opposed to the sample-size dependent F-value. For practical use, and to aid in standardisation or future development of CI2, Matlab code is provided. CI2 provides an effective method to quantify the CI of bivariate plots, and to explore the differences in CI between two bivariate time-series. Copyright © 2016 Elsevier B.V. All rights reserved.

Modeling continuous covariates with a "spike" at zero: Bivariate approaches.

PubMed

Jenkner, Carolin; Lorenz, Eva; Becher, Heiko; Sauerbrei, Willi

2016-07-01

In epidemiology and clinical research, predictors often take value zero for a large amount of observations while the distribution of the remaining observations is continuous. These predictors are called variables with a spike at zero. Examples include smoking or alcohol consumption. Recently, an extension of the fractional polynomial (FP) procedure, a technique for modeling nonlinear relationships, was proposed to deal with such situations. To indicate whether or not a value is zero, a binary variable is added to the model. In a two stage procedure, called FP-spike, the necessity of the binary variable and/or the continuous FP function for the positive part are assessed for a suitable fit. In univariate analyses, the FP-spike procedure usually leads to functional relationships that are easy to interpret. This paper introduces four approaches for dealing with two variables with a spike at zero (SAZ). The methods depend on the bivariate distribution of zero and nonzero values. Bi-Sep is the simplest of the four bivariate approaches. It uses the univariate FP-spike procedure separately for the two SAZ variables. In Bi-D3, Bi-D1, and Bi-Sub, proportions of zeros in both variables are considered simultaneously in the binary indicators. Therefore, these strategies can account for correlated variables. The methods can be used for arbitrary distributions of the covariates. For illustration and comparison of results, data from a case-control study on laryngeal cancer, with smoking and alcohol intake as two SAZ variables, is considered. In addition, a possible extension to three or more SAZ variables is outlined. A combination of log-linear models for the analysis of the correlation in combination with the bivariate approaches is proposed. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Revisiting the Marshmallow Test: A Conceptual Replication Investigating Links Between Early Delay of Gratification and Later Outcomes.

PubMed

Watts, Tyler W; Duncan, Greg J; Quan, Haonan

2018-05-01

We replicated and extended Shoda, Mischel, and Peake's (1990) famous marshmallow study, which showed strong bivariate correlations between a child's ability to delay gratification just before entering school and both adolescent achievement and socioemotional behaviors. Concentrating on children whose mothers had not completed college, we found that an additional minute waited at age 4 predicted a gain of approximately one tenth of a standard deviation in achievement at age 15. But this bivariate correlation was only half the size of those reported in the original studies and was reduced by two thirds in the presence of controls for family background, early cognitive ability, and the home environment. Most of the variation in adolescent achievement came from being able to wait at least 20 s. Associations between delay time and measures of behavioral outcomes at age 15 were much smaller and rarely statistically significant.

An empirical study of statistical properties of variance partition coefficients for multi-level logistic regression models

USGS Publications Warehouse

Li, Ji; Gray, B.R.; Bates, D.M.

2008-01-01

Partitioning the variance of a response by design levels is challenging for binomial and other discrete outcomes. Goldstein (2003) proposed four definitions for variance partitioning coefficients (VPC) under a two-level logistic regression model. In this study, we explicitly derived formulae for multi-level logistic regression model and subsequently studied the distributional properties of the calculated VPCs. Using simulations and a vegetation dataset, we demonstrated associations between different VPC definitions, the importance of methods for estimating VPCs (by comparing VPC obtained using Laplace and penalized quasilikehood methods), and bivariate dependence between VPCs calculated at different levels. Such an empirical study lends an immediate support to wider applications of VPC in scientific data analysis.

An empirical comparison of methods for analyzing correlated data from a discrete choice survey to elicit patient preference for colorectal cancer screening

PubMed Central

2012-01-01

Background A discrete choice experiment (DCE) is a preference survey which asks participants to make a choice among product portfolios comparing the key product characteristics by performing several choice tasks. Analyzing DCE data needs to account for within-participant correlation because choices from the same participant are likely to be similar. In this study, we empirically compared some commonly-used statistical methods for analyzing DCE data while accounting for within-participant correlation based on a survey of patient preference for colorectal cancer (CRC) screening tests conducted in Hamilton, Ontario, Canada in 2002. Methods A two-stage DCE design was used to investigate the impact of six attributes on participants' preferences for CRC screening test and willingness to undertake the test. We compared six models for clustered binary outcomes (logistic and probit regressions using cluster-robust standard error (SE), random-effects and generalized estimating equation approaches) and three models for clustered nominal outcomes (multinomial logistic and probit regressions with cluster-robust SE and random-effects multinomial logistic model). We also fitted a bivariate probit model with cluster-robust SE treating the choices from two stages as two correlated binary outcomes. The rank of relative importance between attributes and the estimates of β coefficient within attributes were used to assess the model robustness. Results In total 468 participants with each completing 10 choices were analyzed. Similar results were reported for the rank of relative importance and β coefficients across models for stage-one data on evaluating participants' preferences for the test. The six attributes ranked from high to low as follows: cost, specificity, process, sensitivity, preparation and pain. However, the results differed across models for stage-two data on evaluating participants' willingness to undertake the tests. Little within-patient correlation (ICC ≈ 0) was found in stage-one data, but substantial within-patient correlation existed (ICC = 0.659) in stage-two data. Conclusions When small clustering effect presented in DCE data, results remained robust across statistical models. However, results varied when larger clustering effect presented. Therefore, it is important to assess the robustness of the estimates via sensitivity analysis using different models for analyzing clustered data from DCE studies. PMID:22348526

Correlates of Quality of Life in New Migrants to Hong Kong from Mainland China

ERIC Educational Resources Information Center

Wong, Winky K. F.; Chou, Kee-Lee; Chow, Nelson W. S.

2012-01-01

The concept of Quality of life (QOL) has received considerable attention from different disciplines. The aim of this study was to identify what are the correlates of QOL among Chinese new immigrants in Hong Kong. Data were collected through a cross-sectional survey among 449 Hong Kong new immigrants from Mainland China. Bivariate and multiple…

Calculations of actual corneal astigmatism using total corneal refractive power before and after myopic keratorefractive surgery.

PubMed

Seo, Kyoung Yul; Yang, Hun; Kim, Wook Kyum; Nam, Sang Min

2017-01-01

To calculate actual corneal astigmatism using the total corneal refractive astigmatism for the 4-mm apex zone of the Pentacam (TCRP4astig) and keratometric astigmatism (Kastig) before and after photorefractive keratectomy or laser in situ keratomileusis. Uncomplicated 56 eyes after more than 6 months from the surgery were recruited by chart review. Various corneal astigmatisms were measured using the Pentacam and autokeratometer before and after surgery. Three eyes were excluded and 53 eyes of 38 subjects with with-the-rule astigmatism (WTR) were finally included. The astigmatisms were investigated using polar value analysis. When TCRP4astig was set as an actual astigmatism, the efficacy of arithmetic or coefficient adjustment of Kastig was evaluated using bivariate analysis. The difference between the simulated keratometer astigmatism of the Pentacam (SimKastig) and Kastig was strongly correlated with the difference between TCRP4astig and Kastig. TCRP4astig was different from Kastig in magnitude rather than meridian before and after surgery; the preoperative difference was due to the posterior cornea only; however, the postoperative difference was observed in both anterior and posterior parts. For arithmetic adjustment, 0.28 D and 0.27 D were subtracted from the preoperative and postoperative magnitudes of Kastig, respectively. For coefficient adjustment, the preoperative and postoperative magnitudes of Kastig were multiplied by 0.80 and 0.66, respectively. By arithmetic or coefficient adjustment, the difference between TCRP4astig and adjusted Kastig would be less than 0.75 D in magnitude for 95% of cases. Kastig was successfully adjusted to TCPR4astig before and after myopic keratorefractive surgery in cases of WTR. For use of TCRP4astig directly, SimKastig and Kastig should be matched.

Calculations of actual corneal astigmatism using total corneal refractive power before and after myopic keratorefractive surgery

PubMed Central

Seo, Kyoung Yul; Yang, Hun; Kim, Wook Kyum; Nam, Sang Min

2017-01-01

Purpose To calculate actual corneal astigmatism using the total corneal refractive astigmatism for the 4-mm apex zone of the Pentacam (TCRP4astig) and keratometric astigmatism (Kastig) before and after photorefractive keratectomy or laser in situ keratomileusis Methods Uncomplicated 56 eyes after more than 6 months from the surgery were recruited by chart review. Various corneal astigmatisms were measured using the Pentacam and autokeratometer before and after surgery. Three eyes were excluded and 53 eyes of 38 subjects with with-the-rule astigmatism (WTR) were finally included. The astigmatisms were investigated using polar value analysis. When TCRP4astig was set as an actual astigmatism, the efficacy of arithmetic or coefficient adjustment of Kastig was evaluated using bivariate analysis. Results The difference between the simulated keratometer astigmatism of the Pentacam (SimKastig) and Kastig was strongly correlated with the difference between TCRP4astig and Kastig. TCRP4astig was different from Kastig in magnitude rather than meridian before and after surgery; the preoperative difference was due to the posterior cornea only; however, the postoperative difference was observed in both anterior and posterior parts. For arithmetic adjustment, 0.28 D and 0.27 D were subtracted from the preoperative and postoperative magnitudes of Kastig, respectively. For coefficient adjustment, the preoperative and postoperative magnitudes of Kastig were multiplied by 0.80 and 0.66, respectively. By arithmetic or coefficient adjustment, the difference between TCRP4astig and adjusted Kastig would be less than 0.75 D in magnitude for 95% of cases. Conclusions Kastig was successfully adjusted to TCPR4astig before and after myopic keratorefractive surgery in cases of WTR. For use of TCRP4astig directly, SimKastig and Kastig should be matched. PMID:28403194

Correlates of Suicidality: Investigation of a Representative Sample of Manitoba First Nations Adolescents

PubMed Central

Mota, Natalie; Elias, Brenda; Tefft, Bruce; Medved, Maria; Munro, Garry

2012-01-01

Objectives. We examined individual, friend or family, and community or tribe correlates of suicidality in a representative on-reserve sample of First Nations adolescents. Methods. Data came from the 2002–2003 Manitoba First Nations Regional Longitudinal Health Survey of Youth. Interviews were conducted with adolescents aged 12 to 17 years (n = 1125) from 23 First Nations communities in Manitoba. We used bivariate logistic regression analyses to examine the relationships between a range of factors and lifetime suicidality. We conducted sex-by-correlate interactions for each significant correlate at the bivariate level. A multivariate logistic regression analysis identified those correlates most strongly related to suicidality. Results. We found several variables to be associated with an increased likelihood of suicidality in the multivariate model, including being female, depressed mood, abuse or fear of abuse, a hospital stay, and substance use (adjusted odds ratio range = 2.43–11.73). Perceived community caring was protective against suicidality (adjusted odds ratio = 0.93; 95% confidence interval = 0.88, 0.97) in the same model. Conclusions. Results of this study may be important in informing First Nations and government policy related to the implementation of suicide prevention strategies in First Nations communities. PMID:22676500

Determining Directional Dependency in Causal Associations

PubMed Central

Pornprasertmanit, Sunthud; Little, Todd D.

2014-01-01

Directional dependency is a method to determine the likely causal direction of effect between two variables. This article aims to critique and improve upon the use of directional dependency as a technique to infer causal associations. We comment on several issues raised by von Eye and DeShon (2012), including: encouraging the use of the signs of skewness and excessive kurtosis of both variables, discouraging the use of D’Agostino’s K2, and encouraging the use of directional dependency to compare variables only within time points. We offer improved steps for determining directional dependency that fix the problems we note. Next, we discuss how to integrate directional dependency into longitudinal data analysis with two variables. We also examine the accuracy of directional dependency evaluations when several regression assumptions are violated. Directional dependency can suggest the direction of a relation if (a) the regression error in population is normal, (b) an unobserved explanatory variable correlates with any variables equal to or less than .2, (c) a curvilinear relation between both variables is not strong (standardized regression coefficient ≤ .2), (d) there are no bivariate outliers, and (e) both variables are continuous. PMID:24683282

Wealth inequality and health: a political economy perspective.

PubMed

Nowatzki, Nadine R

2012-01-01

Despite a plethora of studies on income inequality and health, researchers have been unable to make any firm conclusions as a result of methodological and theoretical limitations. Within this body of research, there has been a call for studies of wealth inequality and health. Wealth is far more unequally distributed than income and is conceptually unique from income. This paper discusses the results of bivariate cross-sectional analyses of the relationship between wealth inequality (Gini coefficient) and population health (life expectancy and infant mortality) in 14 wealthy countries. The results confirm that wealth inequality is associated with poor population health. Both unweighted and weighted correlations between wealth inequality and health are strong and significant, even after controlling for a variety of potential aggregate-level confounders, including gross domestic product per capita, and after excluding the United States, the most unequal country. The results are strongest for female life expectancy and infant mortality. The author outlines potential pathways through which wealth inequality might affect health, using specific countries to illustrate. The article concludes with policy recommendations that could contribute to a more equitable distribution of wealth and, ultimately, decreased health disparities.

Global health inequalities and breast cancer: an impending public health problem for developing countries.

PubMed

Igene, Helen

2008-01-01

The aim of the study was to provide information on the global health inequality pattern produced by the increasing incidence of breast cancer and its relationship with the health expenditure of developing countries with emphasis on sub-Saharan Africa. It examines the difference between the health expenditure of developed and developing countries, and how this affects breast cancer incidence and mortality. The data collected from the World Health Organization and World Bank were examined, using bivariate analysis, through scatter-plots and Pearson's product moment correlation coefficient. Multivariate analysis was carried out by multiple regression analysis. National income, health expenditure affects breast cancer incidence, particularly between the developed and developing countries. However, these factors do not adequately explain variations in mortality rates. The study reveals the risk posed to developing countries to solving the present and predicted burden of breast cancer, currently characterized by late presentation, inadequate health care systems, and high mortality. Findings from this study contribute to the knowledge of the burden of disease in developing countries, especially sub-Saharan Africa, and how that is related to globalization and health inequalities.

Work Ability and Its Related Factors Among Workers in Small and Medium Enterprises: Comparison Among Four ASEAN Countries.

PubMed

Kaewboonchoo, Orawan; Isahak, Marzuki; Susilowati, Indri; Phuong, Toai Nguyen; Morioka, Ikuharu; Harncharoen, Kitiphong; Low, Wah Yun; Ratanasiripong, Paul

2016-07-01

Work ability is related to many factors that might influence one's capacity to work. This study aimed to examine the work ability and its related factors among small and medium enterprises (SME) workers in 4 Association of Southeast Asian Nations (ASEAN) countries. The participants in this study included 2098 workers from food and textile industries in Indonesia, Malaysia, Thailand, and Vietnam. A cross-sectional survey of anonymous self-administrated questionnaire was designed to collect information on sociodemographic factors, work environment and ergonomic condition, musculoskeletal disorders, and work ability. Bivariate correlation coefficient and multiple linear regression analyses were used to predict the work ability. Results of this study confirm that work ability in 4 ASEAN countries was similar to that in European countries, and that the sociodemographic factors, work environment and ergonomic condition, and musculoskeletal disorder (MSD) were associated with work ability. These factors are important for considering occupational health and safety policy to promote work ability in food, textile, and other SME workers. © 2016 APJPH.

Importance of vital signs to the early diagnosis and severity of sepsis: association between vital signs and sequential organ failure assessment score in patients with sepsis.

PubMed

Kenzaka, Tsuneaki; Okayama, Masanobu; Kuroki, Shigehiro; Fukui, Miho; Yahata, Shinsuke; Hayashi, Hiroki; Kitao, Akihito; Sugiyama, Daisuke; Kajii, Eiji; Hashimoto, Masayoshi

2012-01-01

While much attention is given to the fifth vital sign, the utility of the 4 classic vital signs (blood pressure, respiratory rate, body temperature, and heart rate) has been neglected. The aim of this study was to assess a possible association between vital signs and the Sequential Organ Failure Assessment (SOFA) score in patients with sepsis. We performed a prospective, observational study of 206 patients with sepsis. Blood pressure, respiratory rate, body temperature, and heart rate were measured on arrival at the hospital. The SOFA score was also determined on the day of admission. Bivariate correlation analysis showed that all of the vital signs were correlated with the SOFA score. Multiple regression analysis indicated that decreased values of systolic blood pressure (multivariate regression coefficient [Coef] = -0.030, 95% confidence interval [CI] = -0.046 to -0.013) and diastolic blood pressure (Coef = -0.045, 95% CI = -0.070 to -0.019), increased respiratory rate (Coef = 0.176, 95% CI = 0.112 to 0.240), and increased shock index (Coef = 4.232, 95% CI = 2.401 to 6.062) significantly influenced the SOFA score. Increased respiratory rate and shock index were significantly correlated with disease severity in patients with sepsis. Evaluation of these signs may therefore improve early identification of severely ill patients at triage, allowing more aggressive and timely interventions to improve the prognosis of these patients.

A bivariate rational interpolation with a bi-quadratic denominator

NASA Astrophysics Data System (ADS)

Duan, Qi; Zhang, Huanling; Liu, Aikui; Li, Huaigu

2006-10-01

In this paper a new rational interpolation with a bi-quadratic denominator is developed to create a space surface using only values of the function being interpolated. The interpolation function has a simple and explicit rational mathematical representation. When the knots are equally spaced, the interpolating function can be expressed in matrix form, and this form has a symmetric property. The concept of integral weights coefficients of the interpolation is given, which describes the "weight" of the interpolation points in the local interpolating region.

Idealized models of the joint probability distribution of wind speeds

NASA Astrophysics Data System (ADS)

Monahan, Adam H.

2018-05-01

The joint probability distribution of wind speeds at two separate locations in space or points in time completely characterizes the statistical dependence of these two quantities, providing more information than linear measures such as correlation. In this study, we consider two models of the joint distribution of wind speeds obtained from idealized models of the dependence structure of the horizontal wind velocity components. The bivariate Rice distribution follows from assuming that the wind components have Gaussian and isotropic fluctuations. The bivariate Weibull distribution arises from power law transformations of wind speeds corresponding to vector components with Gaussian, isotropic, mean-zero variability. Maximum likelihood estimates of these distributions are compared using wind speed data from the mid-troposphere, from different altitudes at the Cabauw tower in the Netherlands, and from scatterometer observations over the sea surface. While the bivariate Rice distribution is more flexible and can represent a broader class of dependence structures, the bivariate Weibull distribution is mathematically simpler and may be more convenient in many applications. The complexity of the mathematical expressions obtained for the joint distributions suggests that the development of explicit functional forms for multivariate speed distributions from distributions of the components will not be practical for more complicated dependence structure or more than two speed variables.

Genetic and Environmental Basis in Phenotype Correlation Between Physical Function and Cognition in Aging Chinese Twins.

PubMed

Xu, Chunsheng; Zhang, Dongfeng; Tian, Xiaocao; Wu, Yili; Pang, Zengchang; Li, Shuxia; Tan, Qihua

2017-02-01

Although the correlation between cognition and physical function has been well studied in the general population, the genetic and environmental nature of the correlation has been rarely investigated. We conducted a classical twin analysis on cognitive and physical function, including forced expiratory volume in one second (FEV1), forced vital capacity (FVC), handgrip strength, five-times-sit-to-stand test (FTSST), near visual acuity, and number of teeth lost in 379 complete twin pairs. Bivariate twin models were fitted to estimate the genetic and environmental correlation between physical and cognitive function. Bivariate analysis showed mildly positively genetic correlations between cognition and FEV1, r G = 0.23 [95% CI: 0.03, 0.62], as well as FVC, r G = 0.35 [95% CI: 0.06, 1.00]. We found that FTSST and cognition presented very high common environmental correlation, r C = -1.00 [95% CI: -1.00, -0.57], and low but significant unique environmental correlation, r E = -0.11 [95% CI: -0.22, -0.01], all in the negative direction. Meanwhile, near visual acuity and cognition also showed unique environmental correlation, r E = 0.16 [95% CI: 0.03, 0.27]. We found no significantly genetic correlation for cognition with handgrip strength, FTSST, near visual acuity, and number of teeth lost. Cognitive function was genetically related to pulmonary function. The FTSST and cognition shared almost the same common environmental factors but only part of the unique environmental factors, both with negative correlation. In contrast, near visual acuity and cognition may positively share part of the unique environmental factors.

Overweight and Obesity: Prevalence and Correlates in a Large Clinical Sample of Children with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Zuckerman, Katharine E.; Hill, Alison P.; Guion, Kimberly; Voltolina, Lisa; Fombonne, Eric

2014-01-01

Autism Spectrum Disorders (ASDs) and childhood obesity (OBY) are rising public health concerns. This study aimed to evaluate the prevalence of overweight (OWT) and OBY in a sample of 376 Oregon children with ASD, and to assess correlates of OWT and OBY in this sample. We used descriptive statistics, bivariate, and focused multivariate analyses to…

Genetic overlap between impulsivity and alcohol dependence: a large-scale national twin study.

PubMed

Khemiri, L; Kuja-Halkola, R; Larsson, H; Jayaram-Lindström, N

2016-04-01

Alcohol dependence is associated with increased levels of impulsivity, but the genetic and environmental underpinnings of this overlap remain unclear. The purpose of the current study was to investigate the degree to which genetic and environmental factors contribute to the overlap between alcohol dependence and impulsivity. Univariate and bivariate twin model fitting was conducted for alcohol dependence and impulsivity in a national sample of 16 819 twins born in Sweden from 1959 to 1985. The heritability estimate for alcohol dependence was 44% [95% confidence interval (CI) 31-57%] for males and 62% (95% CI 52-72%) for females. For impulsivity, the heritability was 33% (95% CI 30-36%) in males and females. The bivariate twin analysis indicated a statistically significant genetic correlation between alcohol dependence and impulsivity of 0.40 (95% CI 0.23-0.58) in males and 0.20 (95% CI 0.07-0.33) in females. The phenotypic correlation between alcohol dependence and impulsivity was 0.20 and 0.17 for males and females, respectively, and the bivariate heritability was 80% (95% CI 47-117%) for males and 53% (95% CI 19-86%) for females. The remaining variance in all models was accounted for by non-shared environmental factors. The association between alcohol dependence and impulsivity can be partially accounted for by shared genetic factors. The genetic correlation was greater in men compared with women, which may indicate different pathways to the development of alcohol dependence between sexes. The observed genetic overlap has clinical implications regarding treatment and prevention, and partially explains the substantial co-morbidity between alcohol dependence and psychiatric disorders characterized by impulsive behaviour.

Predictors of obturator functioning and satisfaction in Turkish patients using an obturator prosthesis after maxillectomy.

PubMed

Ozdemir-Karatas, Meltem; Balik, Ali; Evlioglu, Gülümser; Uysal, Ömer; Peker, Kadriye

2018-03-01

The aim of this study was to determine the sociodemographic, behavioral, and clinical factors affecting obturator function and satisfaction using the obturator functioning scale (OFS) in maxillectomy patients rehabilitated with obturator prostheses. The study sample consisted of 41 maxillectomy patients. The OFS was translated into Turkish and adapted for assessing obturator functioning and patient satisfaction among Turkish patients. Data were collected from patients' medical records and self-completed questionnaires, including the Turkish version of the OFS, sociodemographic and behavioral characteristics. Descriptive statistics, Mann-Whitney U test, Spearman's correlation coefficient, and backward stepwise multiple linear regression were used for data analysis. Internal consistency (Cronbach's alpha = 0.85) and test-retest reliability (intraclass correlation coefficient = 0.86) were acceptable for the OFS. The most frequently reported problem was "difficulty chewing." Bivariate analysis revealed significant differences in total OFS scores in terms of surgery type, defect size, and education level, except for the other clinical and sociodemographic characteristics and behavioral factors. Education level and surgery type were found to be the most important predictors of patient satisfaction and functioning of the obturator. The Turkish version of the OFS might be a useful tool for clinicians to identify patients who are at risk for poor functioning of the obturator, lack of satisfaction, and unmet needs. Copyright © 2017 Elsevier Inc. All rights reserved.

Association between dental caries experience and sense of coherence among adolescents and mothers.

PubMed

Lage, Carolina Freitas; Fulgencio, Livia Bonfim; Corrêa-Faria, Patricia; Serra-Negra, Junia Maria; Paiva, Saul Martins; Pordeus, Isabela Almeida

2017-09-01

Sense of coherence (SOC) is associated with oral health. Investigate associations between dental caries experience and SOC among mothers and adolescents. A cross-sectional study was conducted with 1195 adolescents and their mothers. Data were collected through a questionnaire, the short version of the SOC and oral clinical examinations. The data were statistically analyzed using bivariate analysis, Poisson regression models with robust variance, and Spearman's correlation coefficient. The prevalence of dental caries experience was 41.8%. A moderate correlation was found between the SOC of mothers and adolescents (r = 0.563; P < 0.001). A higher mother's SOC (PR: 0.44; 95% CI: 0.36-0.53) and adolescent's SOC (PR: 0.46; 95% CI: 0.39-0.55) were protective factors against dental caries experience in the adolescents. The prevalence of dental caries experience was higher among adolescents with visible plaque (Model 1-PR: 1.77; 95% CI: 1.53-2.04; Model 2-PR: 1.59; 95% CI: 1.37-1.84) and those whose families were in a lower economic class (Model 1-PR: 1.56; 95% CI: 1.35-1.80; Model 2-PR: 1.57; 95% CI: 1.36-1.81). Dental caries in adolescents was associated with social determinants evaluated through the sense of coherence. © 2016 BSPD, IAPD and John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The relationship of area-level sociodemographic characteristics, household composition and individual-level socioeconomic status on walking behavior among adults.

PubMed

Hearst, Mary O; Sirard, John R; Forsyth, Ann; Parker, Emily D; Klein, Elizabeth G; Green, Christine G; Lytle, Leslie A

2013-04-01

Understanding the contextual factors associated with why adults walk is important for those interested in increasing walking as a mode of transportation and leisure. This paper investigates the relationships between neighborhood-level sociodemographic context, individual level sociodemographic characteristics and walking for leisure and transport. Data from two community-based studies of adults (n=550) were used to determine the association between the area-sociodemographic environment (ASDE), calculated from U.S. Census variables, and individual-level SES as potential correlates of walking behavior. Descriptive statistics, mean comparisons and Pearson's correlations coefficients were used to assess bivariate relationships. Generalized estimating equations were used to model the relationship between ASDE, as quartiles, and walking behavior. Adjusted models suggest adults engage in more minutes of walking for transportation and less walking for leisure in the most disadvantaged compared to the least disadvantaged neighborhoods but adding individual level demographics and SES eliminated the significant results. However, when models were stratified for free or reduced cost lunch, of those with children who qualified for free or reduced lunch, those who lived in the wealthiest neighborhoods engaged in 10.7 minutes less of total walking per day compared to those living in the most challenged neighborhoods (p<0.001). Strategies to increase walking for transportation or leisure need to take account of individual level socioeconomic factors in addition to area-level measures.

Intra- and inter-basin mercury comparisons: Importance of basin scale and time-weighted methylmercury estimates

USGS Publications Warehouse

Bradley, Paul M.; Journey, Celeste A.; Bringham, Mark E.; Burns, Douglas A.; Button, Daniel T.; Riva-Murray, Karen

2013-01-01

To assess inter-comparability of fluvial mercury (Hg) observations at substantially different scales, Hg concentrations, yields, and bivariate-relations were evaluated at nested-basin locations in the Edisto River, South Carolina and Hudson River, New York. Differences between scales were observed for filtered methylmercury (FMeHg) in the Edisto (attributed to wetland coverage differences) but not in the Hudson. Total mercury (THg) concentrations and bivariate-relationships did not vary substantially with scale in either basin. Combining results of this and a previously published multi-basin study, fish Hg correlated strongly with sampled water FMeHg concentration (p = 0.78; p = 0.003) and annual FMeHg basin yield (p = 0.66; p = 0.026). Improved correlation (p = 0.88; p < 0.0001) was achieved with time-weighted mean annual FMeHg concentrations estimated from basin-specific LOADEST models and daily streamflow. Results suggest reasonable scalability and inter-comparability for different basin sizes if wetland area or related MeHg-source-area metrics are considered.

Correlation between quantitative traits and correlation between corresponding LOD scores: detection of pleiotropic effects.

PubMed

Ulgen, Ayse; Han, Zhihua; Li, Wentian

2003-12-31

We address the question of whether statistical correlations among quantitative traits lead to correlation of linkage results of these traits. Five measured quantitative traits (total cholesterol, fasting glucose, HDL cholesterol, blood pressure, and triglycerides), and one derived quantitative trait (total cholesterol divided by the HDL cholesterol) are used for phenotype correlation studies. Four of them are used for linkage analysis. We show that although correlation among phenotypes partially reflects the correlation among linkage analysis results, the LOD-score correlations are on average low. The most significant peaks found by using different traits do not often overlap. Studying covariances at specific locations in LOD scores may provide clues for further bivariate linkage analyses.

Reference Clinical Database for Fixation Stability Metrics in Normal Subjects Measured with the MAIA Microperimeter.

PubMed

Morales, Marco U; Saker, Saker; Wilde, Craig; Pellizzari, Carlo; Pallikaris, Aristophanes; Notaroberto, Neil; Rubinstein, Martin; Rui, Chiara; Limoli, Paolo; Smolek, Michael K; Amoaku, Winfried M

2016-11-01

The purpose of this study was to establish a normal reference database for fixation stability measured with the bivariate contour ellipse area (BCEA) in the Macular Integrity Assessment (MAIA) microperimeter. Subjects were 358 healthy volunteers who had the MAIA examination. Fixation stability was assessed using two BCEA fixation indices (63% and 95% proportional values) and the percentage of fixation points within 1° and 2° from the fovea (P1 and P2). Statistical analysis was performed with linear regression and Pearson's product moment correlation coefficient. Average areas of 0.80 deg 2 (min = 0.03, max = 3.90, SD = 0.68) for the index BCEA@63% and 2.40 deg 2 (min = 0.20, max = 11.70, SD = 2.04) for the index BCEA@95% were found. The average values of P1 and P2 were 95% (min = 76, max = 100, SD = 5.31) and 99% (min = 91, max = 100, SD = 1.42), respectively. The Pearson's product moment test showed an almost perfect correlation index, r = 0.999, between BCEA@63% and BCEA@95%. Index P1 showed a very strong correlation with BCEA@63%, r = -0.924, as well as with BCEA@95%, r = -0.925. Index P2 demonstrated a slightly lower correlation with both BCEA@63% and BCEA@95%, r = -0.874 and -0.875, respectively. The single parameter of the BCEA@95% may be taken as accurately reporting fixation stability and serves as a reference database of normal subjects with a cutoff area of 2.40 ± 2.04 deg 2 in MAIA microperimeter. Fixation stability can be measured with different indices. This study originates reference fixation values for the MAIA using a single fixation index.

Iron status as a covariate in methylmercury-associated neurotoxicity risk.

PubMed

Fonseca, Márlon de Freitas; De Souza Hacon, Sandra; Grandjean, Philippe; Choi, Anna Lai; Bastos, Wanderley Rodrigues

2014-04-01

Intrauterine methylmercury exposure and prenatal iron deficiency negatively affect offspring's brain development. Since fish is a major source of both methylmercury and iron, occurrence of negative confounding may affect the interpretation of studies concerning cognition. We assessed relationships between methylmercury exposure and iron-status in childbearing females from a population naturally exposed to methylmercury through fish intake (Amazon). We concluded a census (refuse <20%) collecting samples from 274 healthy females (12-49 years) for hair-mercury determination and assessed iron-status through red cell tests and determination of serum ferritin and iron. Reactive C protein and thyroid hormones was used for excluding inflammation and severe thyroid dysfunctions that could affect results. We assessed the association between iron-status and hair-mercury by bivariate correlation analysis and also by different multivariate models: linear regression (to check trends); hierarchical agglomerative clustering method (groups of variables correlated with each other); and factor analysis (to examine redundancy or duplication from a set of correlated variables). Hair-mercury correlated weakly with mean corpuscular volume (r=.141; P=.020) and corpuscular hemoglobin (r=.132; .029), but not with the best biomarker of iron-status, ferritin (r=.037; P=.545). In the linear regression analysis, methylmercury exposure showed weak association with age-adjusted ferritin; age had a significant coefficient (Beta=.015; 95% CI: .003-.027; P=.016) but ferritin did not (Beta=.034; 95% CI: -.147 to .216; P=.711). In the hierarchical agglomerative clustering method, hair-mercury and iron-status showed the smallest similarities. Regarding factor analysis, iron-status and hair-mercury loaded different uncorrelated components. We concluded that iron-status and methylmercury exposure probably occur in an independent way. Copyright © 2013 Elsevier Ltd. All rights reserved.

Brain Pathology Contributes to Simultaneous Change in Physical Frailty and Cognition in Old Age

PubMed Central

Yu, Lei; Wilson, Robert S.; Boyle, Patricia A.; Schneider, Julie A.; Bennett, David. A.

2014-01-01

Objective. First, we tested the hypothesis that the rate of change of physical frailty and cognitive function in older adults are correlated. Next, we examined if their rates of change are associated with the same brain pathologies. Methods. About 2,167 older adults participating in the Religious Orders Study and the Rush Memory and Aging Project had annual clinical evaluations. Bivariate random coefficient models were used to estimate simultaneously the rates of change in both frailty and cognition, and the correlation of change was characterized by a joint distribution of the random effects. Then, we examined whether postmortem indices from deceased were associated with the rate of change of frailty and cognition. Results. During an average follow-up of 6 years, frailty worsened by 0.09 unit/y and cognition declined by 0.08 unit/y. Most individuals showed worsening frailty and cognition (82.8%); 17% showed progressive frailty alone and <1% showed only cognitive decline. The rates of change of frailty and cognition were strongly correlated (ρ = −0.73, p < .001). Among deceased (N = 828), Alzheimer’s disease pathology, macroinfarcts, and nigral neuronal loss showed independent associations with the rate of change in both frailty and cognition (all ps < .001). In these models, demographics explained about 9% of the variation in individual rate of change in frailty, and neuropathologies explained about 8%. In contrast, demographics and neuropathologies accounted for 2% and 30%, respectively, of the variance in the cognitive decline. Conclusion. The rates of change in frailty and cognition are strongly correlated and this may be due in part because they share a common pathologic basis. PMID:25136002

Situational judgment test as an additional tool in a medical admission test: an observational investigation.

PubMed

Luschin-Ebengreuth, Marion; Dimai, Hans P; Ithaler, Daniel; Neges, Heide M; Reibnegger, Gilbert

2015-03-14

In the framework of medical university admission procedures the assessment of non-cognitive abilities is increasingly demanded. As tool for assessing personal qualities or the ability to handle theoretical social constructs in complex situations, the Situational Judgment Test (SJT), among other measurement instruments, is discussed in the literature. This study focuses on the development and the results of the SJT as part of the admission test for the study of human medicine and dentistry at one medical university in Austria. Observational investigation focusing on the results of the SJT. 4741 applicants were included in the study. To yield comparable results for the different test parts, "relative scores" for each test part were calculated. Performance differences between women and men in the various test parts are analyzed using effect sizes based on comparison of mean values (Cohen's d). The associations between the relative scores achieved in the various test parts were assessed by computing pairwise linear correlation coefficients between all test parts and visualized by bivariate scatterplots. Among successful candidates, men consistently outperform women. Men perform better in physics and mathematics. Women perform better in the SJT part. The least discriminatory test part was the SJT. A strong correlation between biology and chemistry and moderate correlations between the other test parts except SJT is obvious. The relative scores are not symmetrically distributed. The cognitive loading of the performed SJTs points to the low correlation between the SJTs and cognitive abilities. Adding the SJT part into the admission test, in order to cover more than only knowledge and understanding of natural sciences among the applicants has been quite successful.

Prevalence of electrolyte disturbances in perinatal asphyxia: a prospective study.

PubMed

Thakur, Jitendra; Bhatta, Nisha Keshary; Singh, Rupa Rajbhandari; Poudel, Prakash; Lamsal, Madhab; Shakya, Anjum

2018-05-21

Birth asphyxia is defined as the presence of hypoxia, hypercapnia, and acidosis leading the newborn to systemic disturbances probably electrolyte disturbance also. Knowledge of these electrolyte disturbances is very valuable as it can be an important parameter affecting perinatal morbidity, mortality and ongoing management. Serum sodium, potassium and ionized calcium of asphyxiated term newborn were sent within one hour of birth as per the inclusion criteria. Statistical comparison of mean values of different electrolytes between different groups of perinatal asphyxia was performed by ANOVA test for parametric data and significant data were further analyzed using post hoc test. Bivariate analysis was done to determine the correlations between Apgar score at 5 min and serum electrolytes. Pearson test was used to calculate the correlation coefficient. Box plot was used to show the median and quartile between serum electrolytes and Apgar score at 5 min. The mean values of sodium for mild, moderate and severe asphyxia were 135.52, 130.7 and 127.15 meq/l respectively. The values of potassium for mild, moderate and severe asphyxia were 4.96, 5.93 and 6.78 meq/l respectively. Similarly, the mean values of ionized calcium for mild, moderate and severe asphyxia were 1.07, 1.12 and 0.99 mmol/l respectively. The values of sodium and potassium among different severity of asphyxia were significantly different (p-value< 0.001). Significant positive correlation was found between serum sodium and Apgar score at 5 min. Significant negative correlation was present between serum potassium and Apgar score at 5 min. The degree of hyponatremia and hyperkalemia was directly proportional to the severity of birth asphyxia. So these electrolyte disturbances should always be kept in mind while managing cases of perinatal asphyxia and should be managed accordingly.

Comparison of the Variations of Sunspot Number, Number of Sunspot Groups, and Sunspot Area, 1875 -2013

NASA Technical Reports Server (NTRS)

Wilson, Robert M.

2014-01-01

Examined are the yearly variations and ratios of sunspot number, the number of sunspot groups, and the total corrected sunspot area for the interval 1875-2013. While yearly sunspot number independently correlates strongly (r = 0.98) with the yearly number of sunspot groups (y = -2 + 11.99x) and the total corrected sunspot area (y = 5 + 0.059x), the strongest correlation (Ry12 = 0.99) is the one based on the bivariate fit of sunspot number against the combined variations of the number of sunspot groups and sunspot area (y = 1 + 5.88x1 + 0.031x2, where y refers to sunspot number, x1 refers to the number of sunspot groups, and x2 refers to the sunspot area). While all cycle minima based on the bivariate fit are concurrent with the observed minimum in sunspot number, cycle maxima are sometimes found to differ. For sunspot cycles 12, 19, 20, and 23, cycle maximum is inferred to have occurred in 1884, 1958, 1970, and 2002, respectively, rather than in 1883, 1957, 1968, and 2000, based on the observed sunspot number. Also, cycle 19's maximum amplitude based on observed sunspot number seems too high in comparison to that found using the bivariate fit. During the 139-year interval 1875-2013, the difference between the observed and predicted sunspot number based on the bivariate fit is <1 standard error of estimate (se) (<6.4) for 111 years, between 1 and <2 se (6.4 to <12.8) for 28 years, and =2 se (=12.8) for only 4 years, these years being 1957 (16.6), 1978 (-15.8), 1980 (23), and 1982 (-16.3). For sunspot cycle 24, the difference between observed and predicted values has been only -0.7 and 3.2 (=0.5 se).

Asymptotic confidence intervals for the Pearson correlation via skewness and kurtosis.

PubMed

Bishara, Anthony J; Li, Jiexiang; Nash, Thomas

2018-02-01

When bivariate normality is violated, the default confidence interval of the Pearson correlation can be inaccurate. Two new methods were developed based on the asymptotic sampling distribution of Fisher's z' under the general case where bivariate normality need not be assumed. In Monte Carlo simulations, the most successful of these methods relied on the (Vale & Maurelli, 1983, Psychometrika, 48, 465) family to approximate a distribution via the marginal skewness and kurtosis of the sample data. In Simulation 1, this method provided more accurate confidence intervals of the correlation in non-normal data, at least as compared to no adjustment of the Fisher z' interval, or to adjustment via the sample joint moments. In Simulation 2, this approximate distribution method performed favourably relative to common non-parametric bootstrap methods, but its performance was mixed relative to an observed imposed bootstrap and two other robust methods (PM1 and HC4). No method was completely satisfactory. An advantage of the approximate distribution method, though, is that it can be implemented even without access to raw data if sample skewness and kurtosis are reported, making the method particularly useful for meta-analysis. Supporting information includes R code. © 2017 The British Psychological Society.

ASURV: Astronomical SURVival Statistics

NASA Astrophysics Data System (ADS)

Feigelson, E. D.; Nelson, P. I.; Isobe, T.; LaValley, M.

2014-06-01

ASURV (Astronomical SURVival Statistics) provides astronomy survival analysis for right- and left-censored data including the maximum-likelihood Kaplan-Meier estimator and several univariate two-sample tests, bivariate correlation measures, and linear regressions. ASURV is written in FORTRAN 77, and is stand-alone and does not call any specialized libraries.

Bayesian bivariate meta-analysis of diagnostic test studies with interpretable priors.

PubMed

Guo, Jingyi; Riebler, Andrea; Rue, Håvard

2017-08-30

In a bivariate meta-analysis, the number of diagnostic studies involved is often very low so that frequentist methods may result in problems. Using Bayesian inference is particularly attractive as informative priors that add a small amount of information can stabilise the analysis without overwhelming the data. However, Bayesian analysis is often computationally demanding and the selection of the prior for the covariance matrix of the bivariate structure is crucial with little data. The integrated nested Laplace approximations method provides an efficient solution to the computational issues by avoiding any sampling, but the important question of priors remain. We explore the penalised complexity (PC) prior framework for specifying informative priors for the variance parameters and the correlation parameter. PC priors facilitate model interpretation and hyperparameter specification as expert knowledge can be incorporated intuitively. We conduct a simulation study to compare the properties and behaviour of differently defined PC priors to currently used priors in the field. The simulation study shows that the PC prior seems beneficial for the variance parameters. The use of PC priors for the correlation parameter results in more precise estimates when specified in a sensible neighbourhood around the truth. To investigate the usage of PC priors in practice, we reanalyse a meta-analysis using the telomerase marker for the diagnosis of bladder cancer and compare the results with those obtained by other commonly used modelling approaches. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Bivariate random-effects meta-analysis models for diagnostic test accuracy studies using arcsine-based transformations.

PubMed

Negeri, Zelalem F; Shaikh, Mateen; Beyene, Joseph

2018-05-11

Diagnostic or screening tests are widely used in medical fields to classify patients according to their disease status. Several statistical models for meta-analysis of diagnostic test accuracy studies have been developed to synthesize test sensitivity and specificity of a diagnostic test of interest. Because of the correlation between test sensitivity and specificity, modeling the two measures using a bivariate model is recommended. In this paper, we extend the current standard bivariate linear mixed model (LMM) by proposing two variance-stabilizing transformations: the arcsine square root and the Freeman-Tukey double arcsine transformation. We compared the performance of the proposed methods with the standard method through simulations using several performance measures. The simulation results showed that our proposed methods performed better than the standard LMM in terms of bias, root mean square error, and coverage probability in most of the scenarios, even when data were generated assuming the standard LMM. We also illustrated the methods using two real data sets. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

How valid are self-reports of illness-related absence? Evidence from a university employee health management program.

PubMed

Jenkins, Kristi Rahrig

2014-08-01

The present study uses a focused approach to compare self-reported versus administratively recorded measures of absences related to health or illness. To date, the few studies that focus on this topic produced mixed results. To help shed light on this issue, the present research has 2 related objectives: (1) examine how highly correlated self-reported and administratively recorded measures of absences related to health or illness might be, and (2) how each measure predicts various aspects of health. Using data from the 2012 StayWell® Health Management health risk appraisal (HRA) and 1 year (2011) of administratively recorded timekeeping data, bivariate analyses for continuous variables and generalized linear modeling for variables with greater than 2 response categories were used. For the multivariate analyses, linear regression models controlling for sex, age, race, income, job status, and campus location were calculated for the continuous outcomes (ie, self-rated health and chronic conditions). Results indicate that self-reported and administratively recorded absences related to health or illness were moderately correlated (correlation coefficient of 0.47). In addition, each measure functioned similarly (in direction and magnitude) to predict health outcomes. Both greater self-reported and recorded illness-related absenteeism was associated with poorer self-rated health and greater numbers of chronic conditions. These results suggest that self-rated illness-related absenteeism may be a reasonable way to assess various program outcomes meaningful to employers, particularly if administratively recorded measures are unavailable or too time consuming or expensive to analyze.

How to compare cross-lagged associations in a multilevel autoregressive model.

PubMed

Schuurman, Noémi K; Ferrer, Emilio; de Boer-Sonnenschein, Mieke; Hamaker, Ellen L

2016-06-01

By modeling variables over time it is possible to investigate the Granger-causal cross-lagged associations between variables. By comparing the standardized cross-lagged coefficients, the relative strength of these associations can be evaluated in order to determine important driving forces in the dynamic system. The aim of this study was twofold: first, to illustrate the added value of a multilevel multivariate autoregressive modeling approach for investigating these associations over more traditional techniques; and second, to discuss how the coefficients of the multilevel autoregressive model should be standardized for comparing the strength of the cross-lagged associations. The hierarchical structure of multilevel multivariate autoregressive models complicates standardization, because subject-based statistics or group-based statistics can be used to standardize the coefficients, and each method may result in different conclusions. We argue that in order to make a meaningful comparison of the strength of the cross-lagged associations, the coefficients should be standardized within persons. We further illustrate the bivariate multilevel autoregressive model and the standardization of the coefficients, and we show that disregarding individual differences in dynamics can prove misleading, by means of an empirical example on experienced competence and exhaustion in persons diagnosed with burnout. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Modeling short duration extreme precipitation patterns using copula and generalized maximum pseudo-likelihood estimation with censoring

NASA Astrophysics Data System (ADS)

Bargaoui, Zoubeida Kebaili; Bardossy, Andràs

2015-10-01

The paper aims to develop researches on the spatial variability of heavy rainfall events estimation using spatial copula analysis. To demonstrate the methodology, short time resolution rainfall time series from Stuttgart region are analyzed. They are constituted by rainfall observations on continuous 30 min time scale recorded over a network composed by 17 raingages for the period July 1989-July 2004. The analysis is performed aggregating the observations from 30 min up to 24 h. Two parametric bivariate extreme copula models, the Husler-Reiss model and the Gumbel model are investigated. Both involve a single parameter to be estimated. Thus, model fitting is operated for every pair of stations for a giving time resolution. A rainfall threshold value representing a fixed rainfall quantile is adopted for model inference. Generalized maximum pseudo-likelihood estimation is adopted with censoring by analogy with methods of univariate estimation combining historical and paleoflood information with systematic data. Only pairs of observations greater than the threshold are assumed as systematic data. Using the estimated copula parameter, a synthetic copula field is randomly generated and helps evaluating model adequacy which is achieved using Kolmogorov Smirnov distance test. In order to assess dependence or independence in the upper tail, the extremal coefficient which characterises the tail of the joint bivariate distribution is adopted. Hence, the extremal coefficient is reported as a function of the interdistance between stations. If it is less than 1.7, stations are interpreted as dependent in the extremes. The analysis of the fitted extremal coefficients with respect to stations inter distance highlights two regimes with different dependence structures: a short spatial extent regime linked to short duration intervals (from 30 min to 6 h) with an extent of about 8 km and a large spatial extent regime related to longer rainfall intervals (from 12 h to 24 h) with an extent of 34 to 38 km.

Moving Average Models with Bivariate Exponential and Geometric Distributions.

DTIC Science & Technology

1985-03-01

ordinary time series and of point processes. Developments in Statistics, Vol. 1, P.R. Krishnaiah , ed. Academic Press, New York. [9] Esary, J.D. and...valued and discrete - valued time series with ARMA correlation structure. Multivariate Analysis V, P.R. Krishnaiah , ed. North-Holland. 151-166. [28

Acculturation, Internet Use, and Psychological Well-Being among Chinese International Students

ERIC Educational Resources Information Center

Li, Jia Qi; Liu, Xun; Wei, Tianlan; Lan, William

2013-01-01

In this study, the authors examined the relationships of acculturation as measured with two subscales of cultural maintenance and cultural assimilation, Internet use, and psychological well-being among Chinese international students. A total of 170 Chinese international students participated in this study. Bivariate correlation analyses revealed…

Psychosocial Correlates of Cigarette Smoking among College Students in China

ERIC Educational Resources Information Center

Mao, Rong; Li, Xiaoming; Stanton, Bonita; Wang, Jing; Hong, Yan; Zhang, Hongshia; Chen, Xinguang

2009-01-01

The objectives are to examine the smoking practice and intention among Chinese college students and to explore the association between cigarette smoking and individual and psychosocial factors. Cross-sectional data were collected from 1874 students from 19 college campuses in Jiangsu province, China. Both bivariate and multivariate analyses were…

Parenting Style, Perfectionism, and Creativity in High-Ability and High-Achieving Young Adults

ERIC Educational Resources Information Center

Miller, Angie L.; Lambert, Amber D.; Speirs Neumeister, Kristie L.

2012-01-01

The current study explores the potential relationships among perceived parenting style, perfectionism, and creativity in a high-ability and high-achieving young adult population. Using data from 323 honors college students at a Midwestern university, bivariate correlations suggested positive relationships between (a) permissive parenting style and…

Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.

PubMed

Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J

2008-06-18

Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson correlation coefficient and the SD-weighted correlation coefficient, and is particularly useful for clustering replicated microarray data. This computational approach should be generally useful for proteomic data or other high-throughput analysis methodology.

Tests of Hypotheses Arising In the Correlated Random Coefficient Model*

PubMed Central

Heckman, James J.; Schmierer, Daniel

2010-01-01

This paper examines the correlated random coefficient model. It extends the analysis of Swamy (1971), who pioneered the uncorrelated random coefficient model in economics. We develop the properties of the correlated random coefficient model and derive a new representation of the variance of the instrumental variable estimator for that model. We develop tests of the validity of the correlated random coefficient model against the null hypothesis of the uncorrelated random coefficient model. PMID:21170148

Oral cancer associated with chronic mechanical irritation of the oral mucosa.

PubMed

Piemonte, E; Lazos, J; Belardinelli, P; Secchi, D; Brunotto, M; Lanfranchi-Tizeira, H

2018-03-01

Most of the studies dealing with Chronic Mechanical Irritation (CMI) and Oral Cancer (OC) only considered prosthetic and dental variables separately, and CMI functional factors are not registered. Thus, the aim of this study was to assess OC risk in individuals with dental, prosthetic and functional CMI. Also, we examined CMI presence in relation to tumor size. A case-control study was carried out from 2009 to 2013. Study group were squamous cell carcinoma cases; control group was patients seeking dental treatment in the same institution. 153 patients were studied (Study group n=53, Control group n=100). CMI reproducibility displayed a correlation coefficient of 1 (p<0.0001). Bivariate analysis showed statistically significant associations for all variables (age, gender, tobacco and alcohol consumption and CMI). Multivariate analysis exhibited statistical significance for age, alcohol, and CMI, but not for gender or tobacco. Relationship of CMI with tumor size showed no statistically significant differences. CMI could be regarded as a risk factor for oral cancer. In individuals with other OC risk factors, proper treatment of the mechanical injuring factors (dental, prosthetic and functional) could be an important measure to reduce the risk of oral cancer.

[Sense of coherence and subjective overload, anxiety and depression in caregivers of elderly relatives].

PubMed

López-Martínez, Catalina; Frías-Osuna, Antonio; Del-Pino-Casado, Rafael

2017-11-23

To analyze the relationship between the sense of coherence and subjective overload, anxiety and depression in caregivers of dependent elderly relatives. Cross-sectional study in an area of the province of Jaén (Andalusia, Spain) with a probabilistic sample of 132 caregivers of dependent elderly. sense of coherence (Life Orientation Questionnaire), subjective burden (Caregiver Strain Index), anxiety and depression (Goldberg Scale), objective burden (Dedication to Care Scale), sex and kinship. Main analyses: bivariate analysis using the Pearson correlation coefficient and multivariate analysis using multiple linear regression. Most of the caregivers studied were women (86.4%), daughter or son of the care recipient (74.2%) and shared home with the latter (69.7%). When controlling for objective burden, sex and kinship, we found that the sense of coherence was inversely related to subjective burden (β = -0.46; p <0.001), anxiety (β = -0.57; p = 0.001) and depression (β = -0.66; p <0.001). The sense of coherence might be an important protective factor of subjective burden, anxiety and depression in caregivers of dependent elderly relatives. Copyright © 2017 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

Influence of geomagnetic activity and atmospheric pressure on human arterial pressure during the solar cycle 24

NASA Astrophysics Data System (ADS)

Azcárate, T.; Mendoza, B.; Levi, J. R.

2016-11-01

We performed a study of the systolic (SBP) and diastolic (DBP) arterial blood pressure behavior under natural variables such as the atmospheric pressure (AtmP) and the horizontal geomagnetic field component (H). We worked with a sample of 304 healthy normotense volunteers, 152 men and 152 women, with ages between 18 and 84 years in Mexico City during the period 2008-2014, corresponding to the minimum, ascending and maximum phases of the solar cycle 24. The data was divided by gender, age and day/night cycle. We studied the time series using three methods: Correlations, bivariate and superposed epochs (within a window of three days around the day of occurrence of a geomagnetic storm) analysis, between the SBP and DBP and the natural variables (AtmP and H). The correlation analysis indicated correlation between the SBP and DBP and AtmP and H, being the largest during the night. Furthermore, the correlation and bivariate analysis showed that the largest correlations are between the SBP and DBP and the AtmP. The superposed epoch analysis found that the largest number of significant SBP and DBP changes occurred for women. Finally, the blood pressure changes are larger during the solar minimum and ascending solar cycle phases than during the solar maximum; the storms of the minimum were more intense than those of the maximum and this could be the reason of behavior of the blood pressure changes along the solar cycle.

Modified Regression Correlation Coefficient for Poisson Regression Model

NASA Astrophysics Data System (ADS)

Kaengthong, Nattacha; Domthong, Uthumporn

2017-09-01

This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).

Distance correlation methods for discovering associations in large astrophysical databases

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

Martínez-Gómez, Elizabeth; Richards, Mercedes T.; Richards, Donald St. P., E-mail: elizabeth.martinez@itam.mx, E-mail: mrichards@astro.psu.edu, E-mail: richards@stat.psu.edu

2014-01-20

High-dimensional, large-sample astrophysical databases of galaxy clusters, such as the Chandra Deep Field South COMBO-17 database, provide measurements on many variables for thousands of galaxies and a range of redshifts. Current understanding of galaxy formation and evolution rests sensitively on relationships between different astrophysical variables; hence an ability to detect and verify associations or correlations between variables is important in astrophysical research. In this paper, we apply a recently defined statistical measure called the distance correlation coefficient, which can be used to identify new associations and correlations between astrophysical variables. The distance correlation coefficient applies to variables of any dimension,more » can be used to determine smaller sets of variables that provide equivalent astrophysical information, is zero only when variables are independent, and is capable of detecting nonlinear associations that are undetectable by the classical Pearson correlation coefficient. Hence, the distance correlation coefficient provides more information than the Pearson coefficient. We analyze numerous pairs of variables in the COMBO-17 database with the distance correlation method and with the maximal information coefficient. We show that the Pearson coefficient can be estimated with higher accuracy from the corresponding distance correlation coefficient than from the maximal information coefficient. For given values of the Pearson coefficient, the distance correlation method has a greater ability than the maximal information coefficient to resolve astrophysical data into highly concentrated horseshoe- or V-shapes, which enhances classification and pattern identification. These results are observed over a range of redshifts beyond the local universe and for galaxies from elliptical to spiral.« less

Clustering Coefficients for Correlation Networks.

PubMed

Masuda, Naoki; Sakaki, Michiko; Ezaki, Takahiro; Watanabe, Takamitsu

2018-01-01

Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other) measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node) are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients were strongly correlated with and therefore may be confounded by the node's connectivity. The proposed methods are expected to help us to understand clustering and lack thereof in correlational brain networks, such as those derived from functional time series and across-participant correlation in neuroanatomical properties.

Clustering Coefficients for Correlation Networks

PubMed Central

Masuda, Naoki; Sakaki, Michiko; Ezaki, Takahiro; Watanabe, Takamitsu

2018-01-01

Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other) measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node) are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients were strongly correlated with and therefore may be confounded by the node's connectivity. The proposed methods are expected to help us to understand clustering and lack thereof in correlational brain networks, such as those derived from functional time series and across-participant correlation in neuroanatomical properties. PMID:29599714

[Correlation coefficient-based classification method of hydrological dependence variability: With auto-regression model as example].

PubMed

Zhao, Yu Xi; Xie, Ping; Sang, Yan Fang; Wu, Zi Yi

2018-04-01

Hydrological process evaluation is temporal dependent. Hydrological time series including dependence components do not meet the data consistency assumption for hydrological computation. Both of those factors cause great difficulty for water researches. Given the existence of hydrological dependence variability, we proposed a correlationcoefficient-based method for significance evaluation of hydrological dependence based on auto-regression model. By calculating the correlation coefficient between the original series and its dependence component and selecting reasonable thresholds of correlation coefficient, this method divided significance degree of dependence into no variability, weak variability, mid variability, strong variability, and drastic variability. By deducing the relationship between correlation coefficient and auto-correlation coefficient in each order of series, we found that the correlation coefficient was mainly determined by the magnitude of auto-correlation coefficient from the 1 order to p order, which clarified the theoretical basis of this method. With the first-order and second-order auto-regression models as examples, the reasonability of the deduced formula was verified through Monte-Carlo experiments to classify the relationship between correlation coefficient and auto-correlation coefficient. This method was used to analyze three observed hydrological time series. The results indicated the coexistence of stochastic and dependence characteristics in hydrological process.

Lifestyle Markers Predict Cognitive Function.

PubMed

Masley, Steven C; Roetzheim, Richard; Clayton, Gwendolyn; Presby, Angela; Sundberg, Kelley; Masley, Lucas V

2017-01-01

Rates of mild cognitive impairment and Alzheimer's disease are increasing rapidly. None of the current treatment regimens for Alzheimer's disease are effective in arresting progression. Lifestyle choices may prevent cognitive decline. This study aims to clarify which factors best predict cognitive function. This was a prospective cross-sectional analysis of 799 men and women undergoing health and cognitive testing every 1 to 3 years at an outpatient center. This study utilizes data collected from the first patient visit. Participant ages were 18 to 88 (mean = 50.7) years and the sample was 26.6% female and 73.4% male. Measurements were made of body composition, fasting laboratory and anthropometric measures, strength and aerobic fitness, nutrient and dietary intake, and carotid intimal media thickness (IMT). Each participant was tested with a computerized neurocognitive test battery. Cognitive outcomes were assessed in bivariate analyses using t-tests and correlation coefficients and in multivariable analysis (controlling for age) using multiple linear regression. The initial bivariate analyses showed better Neurocognitive Index (NCI) scores with lower age, greater fitness scores (push-up strength, VO 2 max, and exercise duration during treadmill testing), and lower fasting glucose levels. Better cognitive flexibility scores were also noted with younger age, lower systolic blood pressure, lower body fat, lower carotid IMT scores, greater fitness, and higher alcohol intake. After controlling for age, factors that remained associated with better NCI scores include no tobacco use, lower fasting glucose levels, and better fitness (aerobic and strength). Higher cognitive flexibility scores remained associated with greater aerobic and strength fitness, lower body fat, and higher intake of alcohol. Modifiable biomarkers that impact cognitive performance favorably include greater aerobic fitness and strength, lower blood sugar levels, greater alcohol intake, lower body fat, and avoidance of tobacco. Further studies are warranted to study whether modifying these lifestyle factors improves cognitive function and slows cognitive decline.

Whole-coal versus ash basis in coal geochemistry: a mathematical approach to consistent interpretations

USGS Publications Warehouse

Geboy, Nicholas J.; Engle, Mark A.; Hower, James C.

2013-01-01

Several standard methods require coal to be ashed prior to geochemical analysis. Researchers, however, are commonly interested in the compositional nature of the whole-coal, not its ash. Coal geochemical data for any given sample can, therefore, be reported in the ash basis on which it is analyzed or the whole-coal basis to which the ash basis data are back calculated. Basic univariate (mean, variance, distribution, etc.) and bivariate (correlation coefficients, etc.) measures of the same suite of samples can be very different depending which reporting basis the researcher uses. These differences are not real, but an artifact resulting from the compositional nature of most geochemical data. The technical term for this artifact is subcompositional incoherence. Since compositional data are forced to a constant sum, such as 100% or 1,000,000 ppm, they possess curvilinear properties which make the Euclidean principles on which most statistical tests rely inappropriate, leading to erroneous results. Applying the isometric logratio (ilr) transformation to compositional data allows them to be represented in Euclidean space and evaluated using traditional tests without fear of producing mathematically inconsistent results. When applied to coal geochemical data, the issues related to differences between the two reporting bases are resolved as demonstrated in this paper using major oxide and trace metal data from the Pennsylvanian-age Pond Creek coal of eastern Kentucky, USA. Following ilr transformation, univariate statistics, such as mean and variance, still differ between the ash basis and whole-coal basis, but in predictable and calculated manners. Further, the stability between two different components, a bivariate measure, is identical, regardless of the reporting basis. The application of ilr transformations addresses both the erroneous results of Euclidean-based measurements on compositional data as well as the inconsistencies observed on coal geochemical data reported on different bases.

On the suitability of the copula types for the joint modelling of flood peaks and volumes along the Danube River

NASA Astrophysics Data System (ADS)

Kohnová, Silvia; Papaioannou, George; Bacigál, Tomáš; Szolgay, Ján; Hlavčová, Kamila; Loukas, Athanasios; Výleta, Roman

2017-04-01

Flood frequency analysis is often performed as a univariate analysis of flood peaks using a suitable theoretical probability distribution of the annual maximum flood peaks or peak over threshold values. However, also other flood attributes, such as flood volume and duration, are often necessary for the design of hydrotechnical structures and projects. In this study, the suitability of various copula families for a bivariate analysis of peak discharges and flood volumes has been tested on the streamflow data from gauging stations along the whole Danube River. Kendall's rank correlation coefficient (tau) quantifies the dependence between flood peak discharge and flood volume settings. The methodology is tested on two different data samples: 1) annual maximum flood (AMF) peaks with corresponding flood volumes, which is a typical choice for engineering studies and 2). annual maximum flood (AMF) peaks combined with annual maximum flow volumes of fixed durations at 5, 10, 15, 20, 25, 30 and 60 days, which can be regarded as a regime analysis of the dependence between the extremes of both variables in a given year. The bivariate modelling of the peak discharge - flood volume couples is achieved with the use of the the following copulas: Ali-Mikhail-Haq (AMH), Clayton, Frank, Joe, Gumbel, HuslerReiss, Galambos, Tawn, Normal, Plackett and FGM, respectively. Scatterplots of the observed and simulated peak discharge - flood volume pairs and goodness-of-fit tests have been used to assess the overall applicability of the copulas as well as observing any changes in suitable models along the Danube River. The results indicate that, almost all of the considered Archimedean class copulas (e.g. Frank, Clayton and Ali-Mikhail-Haq) perform better than the other copula families selected for this study, and that for the second data samples mostly the upper-tail-flat copulas were suitable.

A new method for correlation analysis of compositional (environmental) data - a worked example.

PubMed

Reimann, C; Filzmoser, P; Hron, K; Kynčlová, P; Garrett, R G

2017-12-31

Most data in environmental sciences and geochemistry are compositional. Already the unit used to report the data (e.g., μg/l, mg/kg, wt%) implies that the analytical results for each element are not free to vary independently of the other measured variables. This is often neglected in statistical analysis, where a simple log-transformation of the single variables is insufficient to put the data into an acceptable geometry. This is also important for bivariate data analysis and for correlation analysis, for which the data need to be appropriately log-ratio transformed. A new approach based on the isometric log-ratio (ilr) transformation, leading to so-called symmetric coordinates, is presented here. Summarizing the correlations in a heat-map gives a powerful tool for bivariate data analysis. Here an application of the new method using a data set from a regional geochemical mapping project based on soil O and C horizon samples is demonstrated. Differences to 'classical' correlation analysis based on log-transformed data are highlighted. The fact that some expected strong positive correlations appear and remain unchanged even following a log-ratio transformation has probably led to the misconception that the special nature of compositional data can be ignored when working with trace elements. The example dataset is employed to demonstrate that using 'classical' correlation analysis and plotting XY diagrams, scatterplots, based on the original or simply log-transformed data can easily lead to severe misinterpretations of the relationships between elements. Copyright © 2017 Elsevier B.V. All rights reserved.

Estimation of the biserial correlation and its sampling variance for use in meta-analysis.

PubMed

Jacobs, Perke; Viechtbauer, Wolfgang

2017-06-01

Meta-analyses are often used to synthesize the findings of studies examining the correlational relationship between two continuous variables. When only dichotomous measurements are available for one of the two variables, the biserial correlation coefficient can be used to estimate the product-moment correlation between the two underlying continuous variables. Unlike the point-biserial correlation coefficient, biserial correlation coefficients can therefore be integrated with product-moment correlation coefficients in the same meta-analysis. The present article describes the estimation of the biserial correlation coefficient for meta-analytic purposes and reports simulation results comparing different methods for estimating the coefficient's sampling variance. The findings indicate that commonly employed methods yield inconsistent estimates of the sampling variance across a broad range of research situations. In contrast, consistent estimates can be obtained using two methods that appear to be unknown in the meta-analytic literature. A variance-stabilizing transformation for the biserial correlation coefficient is described that allows for the construction of confidence intervals for individual coefficients with close to nominal coverage probabilities in most of the examined conditions. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Estimation of the simple correlation coefficient.

PubMed

Shieh, Gwowen

2010-11-01

This article investigates some unfamiliar properties of the Pearson product-moment correlation coefficient for the estimation of simple correlation coefficient. Although Pearson's r is biased, except for limited situations, and the minimum variance unbiased estimator has been proposed in the literature, researchers routinely employ the sample correlation coefficient in their practical applications, because of its simplicity and popularity. In order to support such practice, this study examines the mean squared errors of r and several prominent formulas. The results reveal specific situations in which the sample correlation coefficient performs better than the unbiased and nearly unbiased estimators, facilitating recommendation of r as an effect size index for the strength of linear association between two variables. In addition, related issues of estimating the squared simple correlation coefficient are also considered.

Consistent Small-Sample Variances for Six Gamma-Family Measures of Ordinal Association

ERIC Educational Resources Information Center

Woods, Carol M.

2009-01-01

Gamma-family measures are bivariate ordinal correlation measures that form a family because they all reduce to Goodman and Kruskal's gamma in the absence of ties (1954). For several gamma-family indices, more than one variance estimator has been introduced. In previous research, the "consistent" variance estimator described by Cliff and…

An Analysis of the Relationship between Phonological and Nonphonological Language and Early Reading Development

ERIC Educational Resources Information Center

Batson-Magnuson, LuAnn

2017-01-01

This study explores the relationship between preschool phonological and nonphonological language performance and first-grade reading performance. Data were gathered from the files of 149 students who had completed a universal kindergarten screening program in the spring prior to enrollment. Bivariate correlation analyses, Steiger's Z comparisons,…

Organizational Response to Conflict: Future Conflict and Work Outcomes

ERIC Educational Resources Information Center

Meyer, Susan

2004-01-01

The purpose of this study was to examine how on organization's response to conflict affected the amount and intensity of future conflict and negative work outcomes. In this cross-sectional study of 3,374 government service workers, bivariate correlations and multiple regressions revealed associations between managers' conflict-handling style (CHS)…

Parent Characteristics, Economic Stress and Neighborhood Context as Predictors of Parent Involvement in Preschool Children's Education

ERIC Educational Resources Information Center

Waanders, Christine; Mendez, Julia L.; Downer, Jason T.

2007-01-01

This study examines factors related to three dimensions of parent involvement in preschool: school-based involvement, home-based involvement, and the parent-teacher relationship. Participants were 154 predominantly African American parents recruited from two Head Start programs. Results of bivariate and canonical correlation analyses support the…

Family Functioning and the Development of Trust and Intimacy among Adolescents in Residential Treatment

ERIC Educational Resources Information Center

Coll, Kenneth M.; Powell, Stephanie; Thobro, Patti; Haas, Robin

2010-01-01

This study examined relations between family cohesion and adaptability (as measured by the Family Adaptability and Cohesion Scales-III) and the formation of trust and intimacy (assessed with the Measure of Psychosocial Development) among adolescents in residential treatment. Bivariate correlation revealed a significant association between family…

Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.

PubMed

Faul, Franz; Erdfelder, Edgar; Buchner, Axel; Lang, Albert-Georg

2009-11-01

G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.

Bivariate and multivariate analyses of the correlations between stability of the erythrocyte membrane, serum lipids and hematological variables.

PubMed

Bernardino Neto, M; de Avelar, E B; Arantes, T S; Jordão, I A; da Costa Huss, J C; de Souza, T M T; de Souza Penha, V A; da Silva, S C; de Souza, P C A; Tavares, M; Penha-Silva, N

2013-01-01

The observation that the fluidity must remain within a critical interval, outside which the stability and functionality of the cell tends to decrease, shows that stability, fluidity and function are related and that the measure of erythrocyte stability allows inferences about the fluidity or functionality of these cells. This study determined the biochemical and hematological variables that are directly or indirectly related to erythrocyte stability in a population of 71 volunteers. Data were evaluated by bivariate and multivariate analysis. The erythrocyte stability showed a greater association with hematological variables than the biochemical variables. The RDW stands out for its strong correlation with the stability of erythrocyte membrane, without being heavily influenced by other factors. Regarding the biochemical variables, the erythrocyte stability was more sensitive to LDL-C. Erythrocyte stability was significantly associated with RDW and LDL-C. Thus, the level of LDL-C is a consistent link between stability and functionality, suggesting that a measure of stability could be more one indirect parameter for assessing the risk of degenerative processes associated with high levels of LDL-C.

Why Do Some First Nations Communities Have Safe Water and Others Not? Socioeconomic Determinants of Drinking Water Risk

PubMed Central

Brown, Brandon; Wachowiak-Smolíková, Renata; Spence, Nicholas D.; Wachowiak, Mark P.; Walters, Dan F.

2016-01-01

Securing safe and adequate drinking water is an ongoing issue for many Canadian First Nations communities despite nearly 15 years of reports, studies, policy changes, financial commitments, and regulations. The federal drinking water evaluation scheme is narrowly scoped, ignoring community level social factors, which may play a role in access to safe water in First Nations. This research used the 2006 Aboriginal Affairs and Northern Development Canada First Nations Drinking Water System Risk Survey data and the Community Well-Being Index, including labour force, education, housing, and income, from the 2006 Census. Bivariate analysis was conducted using the Spearman’s correlation, Kendall’s tau correlation, and Pearson’s correlation. Multivariable analysis was conducted using an ordinal (proportional or cumulative odds) regression model. Results showed that the regression model was significant. Community socioeconomic indicators had no relationship with drinking water risk characterization in both the bivariate and multivariable models, with the sole exception of labour force, which had a significantly positive effect on drinking water risk rankings. Socioeconomic factors were not important in explaining access to safe drinking water in First Nations communities. Improvements in the quality of safe water data as well as an examination of other community processes are required to address this pressing policy issue. PMID:27157172

Why Do Some First Nations Communities Have Safe Water and Others Not? Socioeconomic Determinants of Drinking Water Risk.

PubMed

Brown, Brandon; Wachowiak-Smolíková, Renata; Spence, Nicholas D; Wachowiak, Mark P; Walters, Dan F

2016-09-01

Securing safe and adequate drinking water is an ongoing issue for many Canadian First Nations communities despite nearly 15 years of reports, studies, policy changes, financial commitments, and regulations. The federal drinking water evaluation scheme is narrowly scoped, ignoring community level social factors, which may play a role in access to safe water in First Nations. This research used the 2006 Aboriginal Affairs and Northern Development Canada First Nations Drinking Water System Risk Survey data and the Community Well-Being Index, including labour force, education, housing, and income, from the 2006 Census. Bivariate analysis was conducted using the Spearman's correlation, Kendall's tau correlation, and Pearson's correlation. Multivariable analysis was conducted using an ordinal (proportional or cumulative odds) regression model. Results showed that the regression model was significant. Community socioeconomic indicators had no relationship with drinking water risk characterization in both the bivariate and multivariable models, with the sole exception of labour force, which had a significantly positive effect on drinking water risk rankings. Socioeconomic factors were not important in explaining access to safe drinking water in First Nations communities. Improvements in the quality of safe water data as well as an examination of other community processes are required to address this pressing policy issue.

The Attenuation of Correlation Coefficients: A Statistical Literacy Issue

ERIC Educational Resources Information Center

Trafimow, David

2016-01-01

Much of the science reported in the media depends on correlation coefficients. But the size of correlation coefficients depends, in part, on the reliability with which the correlated variables are measured. Understanding this is a statistical literacy issue.

Non-parametric directionality analysis - Extension for removal of a single common predictor and application to time series.

PubMed

Halliday, David M; Senik, Mohd Harizal; Stevenson, Carl W; Mason, Rob

2016-08-01

The ability to infer network structure from multivariate neuronal signals is central to computational neuroscience. Directed network analyses typically use parametric approaches based on auto-regressive (AR) models, where networks are constructed from estimates of AR model parameters. However, the validity of using low order AR models for neurophysiological signals has been questioned. A recent article introduced a non-parametric approach to estimate directionality in bivariate data, non-parametric approaches are free from concerns over model validity. We extend the non-parametric framework to include measures of directed conditional independence, using scalar measures that decompose the overall partial correlation coefficient summatively by direction, and a set of functions that decompose the partial coherence summatively by direction. A time domain partial correlation function allows both time and frequency views of the data to be constructed. The conditional independence estimates are conditioned on a single predictor. The framework is applied to simulated cortical neuron networks and mixtures of Gaussian time series data with known interactions. It is applied to experimental data consisting of local field potential recordings from bilateral hippocampus in anaesthetised rats. The framework offers a non-parametric approach to estimation of directed interactions in multivariate neuronal recordings, and increased flexibility in dealing with both spike train and time series data. The framework offers a novel alternative non-parametric approach to estimate directed interactions in multivariate neuronal recordings, and is applicable to spike train and time series data. Copyright © 2016 Elsevier B.V. All rights reserved.

Parapapillary Gamma Zone and Progression of Myopia in School Children: The Beijing Children Eye Study.

PubMed

Guo, Yin; Liu, Li Juan; Tang, Ping; Feng, Yi; Lv, Yan Yun; Wu, Min; Xu, Liang; Jonas, Jost B

2018-03-01

To assess the development and enlargement of the parapapillary gamma zone in school children. This school-based prospective longitudinal study included Chinese children attending grade 1 in 2011 and returning for yearly follow-up examinations until 2016. These examinations consisted of a comprehensive ocular examination with biometry and color fundus photographs. The parents underwent a standardized interview. The parapapillary gamma zone was defined as the area with visible sclera at the temporal optic disc margin, and the optic disc itself was measured on fundus photographs. The study included 294 children (mean age in 2016, 11.4 ± 0.5 years [range, 10-13 years]; mean axial length, 24.1 ± 1.1 mm [range, 21.13-27.29 mm]). In multivariate analysis, larger increases in the gamma zone area during the study period were correlated (coefficient of determination for bivariate analysis [r2], r2 = 0.69) with larger increases in the vertical-to-horizontal disc diameter ratios (P < 0.001; standardized regression coefficient beta [beta], 0.53; nonstandardized regression coefficient B [B], 4.05; 95% confidence intervals [CI], 3.37-4.73), larger axial elongation (P < 0.001; beta, 0.32; B, 0.37; 95% CI, 0.26-0.47), a larger vertical disc diameter at baseline (P < 0.001; beta, 0.22; B, 0.98; 95% CI, 0.62-1.33), a larger gamma zone area at baseline (P < 0.001; beta, 0.14; B, 0.41; 95% CI, 0.17-0.64), and more time spent indoors studying (P = 0.015; beta, 0.10; B, 0.09; 95% CI, 0.02-0.17). The development and enlargement of the gamma zone in the temporal parapapillary region were associated with an optic disc rotation around the vertical disc axis as indicated by an increasing vertical-to-horizontal disc diameter ratio. These morphologic findings fit with the notion of a backward pull of the temporal peripapillary sclera through the optic nerve dura mater in axially elongated eyes.

Disagreement between self-reported and clinician-ascertained suicidal ideation and its correlation with depression and anxiety severity in patients with major depressive disorder or bipolar disorder.

PubMed

Gao, Keming; Wu, Renrong; Wang, Zuowei; Ren, Ming; Kemp, David E; Chan, Philip K; Conroy, Carla M; Serrano, Mary Beth; Ganocy, Stephen J; Calabrese, Joseph R

2015-01-01

To study the disagreement between self-reported suicidal ideation (SR-SI) and clinician-ascertained suicidal ideation (CA-SI) and its correlation with depression and anxiety severity in patients with major depressive disorder (MDD) or bipolar disorder (BPD). Routine clinical outpatients were diagnosed with the MINI-STEP-BD version. SR-SI was extracted from the 16 Item Quick Inventory of Depression Symptomatology Self-Report (QIDS-SR-16) item 12. CA-SI was extracted from a modified Suicide Assessment module of the MINI. Depression and anxiety severity were measured with the QIDS-SR-16 and Zung Self-Rating Anxiety Scale. Chi-square, Fisher exact, and bivariate linear logistic regression were used for analyses. Of 103 patients with MDD, 5.8% endorsed any CA-SI and 22.4% endorsed any SR-SI. Of the 147 patients with BPD, 18.4% endorsed any CA-SI and 35.9% endorsed any SR-SI. The agreement between any SR-SI and any CA-SI was 83.5% for MDD and 83.1% for BPD, with weighted Kappa of 0.30 and 0.43, respectively. QIDS-SR-16 score, female gender, and ≥4 year college education were associated with increased risk for disagreement, 15.44 ± 4.52 versus 18.39 ± 3.49 points (p = 0.0026), 67% versus 46% (p = 0.0783), and 61% versus 29% (p = 0.0096). The disagreement was positively correlated to depression severity in both MDD and BPD with a correlation coefficient R(2) = 0.40 and 0.79, respectively, but was only positively correlated to anxiety severity in BPD with a R(2) = 0.46. Self-reported questionnaire was more likely to reveal higher frequency and severity of SI than clinician-ascertained, suggesting that a combination of self-reported and clinical-ascertained suicidal risk assessment with measuring depression and anxiety severity may be necessary for suicide prevention. Copyright © 2014 Elsevier Ltd. All rights reserved.

Identification of Correlated GRACE Monthly Harmonic Coefficients Using Pattern Recognition and Neural Networks

NASA Astrophysics Data System (ADS)

Piretzidis, D.; Sra, G.; Sideris, M. G.

2016-12-01

This study explores new methods for identifying correlation errors in harmonic coefficients derived from monthly solutions of the Gravity Recovery and Climate Experiment (GRACE) satellite mission using pattern recognition and neural network algorithms. These correlation errors are evidenced in the differences between monthly solutions and can be suppressed using a de-correlation filter. In all studies so far, the implementation of the de-correlation filter starts from a specific minimum order (i.e., 11 for RL04 and 38 for RL05) until the maximum order of the monthly solution examined. This implementation method has two disadvantages, namely, the omission of filtering correlated coefficients of order less than the minimum order and the filtering of uncorrelated coefficients of order higher than the minimum order. In the first case, the filtered solution is not completely free of correlated errors, whereas the second case results in a monthly solution that suffers from loss of geophysical signal. In the present study, a new method of implementing the de-correlation filter is suggested, by identifying and filtering only the coefficients that show indications of high correlation. Several numerical and geometric properties of the harmonic coefficient series of all orders are examined. Extreme cases of both correlated and uncorrelated coefficients are selected, and their corresponding properties are used to train a two-layer feed-forward neural network. The objective of the neural network is to identify and quantify the correlation by providing the probability of an order of coefficients to be correlated. Results show good performance of the neural network, both in the validation stage of the training procedure and in the subsequent use of the trained network to classify independent coefficients. The neural network is also capable of identifying correlated coefficients even when a small number of training samples and neurons are used (e.g.,100 and 10, respectively).

Contributory fault and level of personal injury to drivers involved in head-on collisions: Application of copula-based bivariate ordinal models.

PubMed

Wali, Behram; Khattak, Asad J; Xu, Jingjing

2018-01-01

The main objective of this study is to simultaneously investigate the degree of injury severity sustained by drivers involved in head-on collisions with respect to fault status designation. This is complicated to answer due to many issues, one of which is the potential presence of correlation between injury outcomes of drivers involved in the same head-on collision. To address this concern, we present seemingly unrelated bivariate ordered response models by analyzing the joint injury severity probability distribution of at-fault and not-at-fault drivers. Moreover, the assumption of bivariate normality of residuals and the linear form of stochastic dependence implied by such models may be unduly restrictive. To test this, Archimedean copula structures and normal mixture marginals are integrated into the joint estimation framework, which can characterize complex forms of stochastic dependencies and non-normality in residual terms. The models are estimated using 2013 Virginia police reported two-vehicle head-on collision data, where exactly one driver is at-fault. The results suggest that both at-fault and not-at-fault drivers sustained serious/fatal injuries in 8% of crashes, whereas, in 4% of the cases, the not-at-fault driver sustained a serious/fatal injury with no injury to the at-fault driver at all. Furthermore, if the at-fault driver is fatigued, apparently asleep, or has been drinking the not-at-fault driver is more likely to sustain a severe/fatal injury, controlling for other factors and potential correlations between the injury outcomes. While not-at-fault vehicle speed affects injury severity of at-fault driver, the effect is smaller than the effect of at-fault vehicle speed on at-fault injury outcome. Contrarily, and importantly, the effect of at-fault vehicle speed on injury severity of not-at-fault driver is almost equal to the effect of not-at-fault vehicle speed on injury outcome of not-at-fault driver. Compared to traditional ordered probability models, the study provides evidence that copula based bivariate models can provide more reliable estimates and richer insights. Practical implications of the results are discussed. Published by Elsevier Ltd.

Validation of a Spanish translation of the Gratitude Questionnaire (GQ-6) with a Chilean sample of adults and high schoolers.

PubMed

Langer, Álvaro I; Ulloa, Valentina G; Aguilar-Parra, José M; Araya-Véliz, Claudio; Brito, Gonzalo

2016-03-31

Recent studies have associated positive emotions with several variables such as learning, coping strategies or assertive behaviour. The concept of gratitude has been specifically defined as a tendency to recognise and respond to people or situations with grateful emotion. Unfortunately in Latin America, no validated measures of gratitude on different populations are available. The aim of this study was to analyse the psychometric properties of the Gratitude Questionnaire (GQ-6) in two Chilean samples. Two studies were conducted: the first with 668 high school adolescents (390 women and 278 men, with ages ranging between 12 and 20, and a mean age 15.54 ± 1.22) and the second with 331 adults (231 women and 100 men, with an average age of 37.59 ± 12.6). An analysis of the psychometric properties of the GQ-6 scale to determine the validity and reliability of the instrument in Chilean adolescents and adults was performed. Bivariate correlations, multiple regression analyses, exploratory factor analysis (EFA) and Monte Carlo simulations were carried out. Finally, a confirmatory factor analysis (CFA) was performed. A single-factor solution was found in both studies, a 5 item version for the adolescents and 6 items for adults. This factorial solution was invariant across genders. Reliability of the GQ was adequate in both samples (using Cronbach's alpha coefficient). In addition convergent and discriminate validity were assessed. Additionally, a negative correlation between the GQ-5 and depression in adolescents and a positive correlation between the GQ-6 and happiness in adults was found. The GQ is a suitable measure for evaluating a person's disposition toward gratitude in Chilean adolescents and adults. This instrument may contribute to the advancement of the study of positive emotions in Latin America.

International development and psychometric properties of the Child and Adolescent Trauma Screen (CATS).

PubMed

Sachser, Cedric; Berliner, Lucy; Holt, Tonje; Jensen, Tine K; Jungbluth, Nathaniel; Risch, Elizabeth; Rosner, Rita; Goldbeck, Lutz

2017-03-01

Systematic screening is a powerful means by which children and adolescents with posttraumatic stress symptoms (PTSS) can be detected. Reliable and valid measures based on current diagnostic criteria are needed. To investigate the internal consistency and construct validity of the Child and Adolescent Trauma Screen (CATS) in three samples of trauma-exposed children in the US (self-reports: n=249; caregiver reports: n=267; pre-school n=190), in Germany (self-reports: n=117; caregiver reports: n=95) and in Norway (self-reports: n=109; caregiver reports: n=62). Internal consistency was calculated using Cronbach's α. Convergent-discriminant validity was investigated using bivariate correlation coefficients with measures of depression, anxiety and externalizing symptoms. CFA was used to investigate the DSM-5 factor structure. In all three language samples the 20 item symptom score of the self-report and the caregiver report proved good to excellent reliability with α ranging between .88 and .94. The convergent-discriminant validity pattern showed medium to strong correlations with measures of depression (r =.62-.82) and anxiety (r =.40-.77) and low to medium correlations with externalizing symptoms (r =-.15-.43) within informants in all language versions. Using CFA the underlying DSM-5 factor structure with four symptom clusters (re-experiencing, avoidance, negative alterations in mood and cognitions, hyperarousal) was supported (n =475 for self-report; n =424 for caregiver reports). The external validation of the CATS with a DSM-5 based semi-structured clinical interview and corresponding determination of cut-points is pending. The CATS has satisfactory psychometric properties. Clinicians may consider the CATS as a screening tool and for symptom monitoring. Copyright © 2016 Elsevier B.V. All rights reserved.

Identifying factors associated with fast food consumption among adolescents in Beijing China using a theory-based approach.

PubMed

Ma, R; Castellanos, D C; Bachman, J

2016-07-01

China is in the midst of the nutrition transition with increasing rates of obesity and dietary changes. One contributor is the increase in fast food chains within the country. The purpose of this study was to develop a theory-based instrument that explores influencing factors of fast food consumption in adolescents residing in Beijing, China. Cross-sectional study. Value expectancy and theory of planned behaviour were utilised to explore influencing factors of fast food consumption in the target population. There were 201 Chinese adolescents between the ages of 12 and 18. Cronbach's alpha correlation coefficients were used to examine internal reliability of the theory-based questionnaire. Bivariate correlations and a MANOVA were utilised to determine the relationship between theory-based constructs, body mass index (BMI)-for-age and fast food intake frequency as well as to determine differences in theory-based scores among fast food consumption frequency groupings. The theory-based questionnaire showed good reliability. Furthermore, there was a significant difference in the theory-based subcategory scores between fast food frequency groups. A significant positive correlation was observed between times per week fast food was consumed and each theory-based subscale score. Using BMI-for-age of 176 participants, 81% were normal weight and 19% were considered overweight or obese. Results showed consumption of fast food to be on average 1.50 ± 1.33 per week. The relationship between BMI-for-age and times per week fast food was consumed was not significant. As the nutrition transition continues and fast food chains expand, it is important to explore factors effecting fast food consumption in China. Interventions targeting influencing factors can be developed to encourage healthy dietary choice in the midst of this transition. Copyright © 2016. Published by Elsevier Ltd.

Diagnosing cysts with correlation coefficient images from 2-dimensional freehand elastography.

PubMed

Booi, Rebecca C; Carson, Paul L; O'Donnell, Matthew; Richards, Michael S; Rubin, Jonathan M

2007-09-01

We compared the diagnostic potential of using correlation coefficient images versus elastograms from 2-dimensional (2D) freehand elastography to characterize breast cysts. In this preliminary study, which was approved by the Institutional Review Board and compliant with the Health Insurance Portability and Accountability Act, we imaged 4 consecutive human subjects (4 cysts, 1 biopsy-verified benign breast parenchyma) with freehand 2D elastography. Data were processed offline with conventional 2D phase-sensitive speckle-tracking algorithms. The correlation coefficient in the cyst and surrounding tissue was calculated, and appearances of the cysts in the correlation coefficient images and elastograms were compared. The correlation coefficient in the cysts was considerably lower (14%-37%) than in the surrounding tissue because of the lack of sufficient speckle in the cysts, as well as the prominence of random noise, reverberations, and clutter, which decorrelated quickly. Thus, the cysts were visible in all correlation coefficient images. In contrast, the elastograms associated with these cysts each had different elastographic patterns. The solid mass in this study did not have the same high decorrelation rate as the cysts, having a correlation coefficient only 2.1% lower than that of surrounding tissue. Correlation coefficient images may produce a more direct, reliable, and consistent method for characterizing cysts than elastograms.

A Preliminary Comparison of the Effectiveness of Cluster Analysis Weighting Procedures for Within-Group Covariance Structure.

ERIC Educational Resources Information Center

Donoghue, John R.

A Monte Carlo study compared the usefulness of six variable weighting methods for cluster analysis. Data were 100 bivariate observations from 2 subgroups, generated according to a finite normal mixture model. Subgroup size, within-group correlation, within-group variance, and distance between subgroup centroids were manipulated. Of the clustering…

Differential Neonatal and Postneonatal Infant Mortality Rates across US Counties: The Role of Socioeconomic Conditions and Rurality

ERIC Educational Resources Information Center

Sparks, P. Johnelle; McLaughlin, Diane K.; Stokes, C. Shannon

2009-01-01

Purpose: To examine differences in correlates of neonatal and postneonatal infant mortality rates, across counties, by degree of rurality. Methods: Neonatal and postneonatal mortality rates were calculated from the 1998 to 2002 Compressed Mortality Files from the National Center for Health Statistics. Bivariate analyses assessed the relationship…

Approximating Multivariate Normal Orthant Probabilities. ONR Technical Report. [Biometric Lab Report No. 90-1.

ERIC Educational Resources Information Center

Gibbons, Robert D.; And Others

The probability integral of the multivariate normal distribution (ND) has received considerable attention since W. F. Sheppard's (1900) and K. Pearson's (1901) seminal work on the bivariate ND. This paper evaluates the formula that represents the "n x n" correlation matrix of the "chi(sub i)" and the standardized multivariate…

Perceived Autonomy-Support, Expectancy, Value, Metacognitive Strategies and Performance in Chemistry: A Structural Equation Model in Undergraduates

ERIC Educational Resources Information Center

González, Antonio; Paoloni, Paola-Verónica

2015-01-01

Research in chemistry education has highlighted a number of variables that predict learning and performance, such as teacher-student interactions, academic motivation and metacognition. Most of this chemistry research has examined these variables by identifying dyadic relationships through bivariate correlations. The main purpose of this study was…

A New Methodology of Spatial Cross-Correlation Analysis

PubMed Central

Chen, Yanguang

2015-01-01

Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran’s index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson’s correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China’s urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes. PMID:25993120

A new methodology of spatial cross-correlation analysis.

PubMed

Chen, Yanguang

2015-01-01

Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran's index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson's correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China's urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes.

Flood risk analysis for flood control and sediment transportation: a case study in the catchments of the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Wang, Y.; Chang, J.; Guo, A.

2017-12-01

Traditional flood risk analysis focuses on the probability of flood events exceeding the design flood of downstream hydraulic structures while neglecting the influence of sedimentation in river channels on flood control systems. Given this focus, a univariate and copula-based bivariate hydrological risk framework focusing on flood control and sediment transport is proposed in the current work. Additionally, the conditional probabilities of occurrence of different flood events under various extreme precipitation scenarios are estimated by exploiting the copula model. Moreover, a Monte Carlo-based algorithm is used to evaluate the uncertainties of univariate and bivariate hydrological risk. Two catchments located on the Loess plateau are selected as study regions: the upper catchments of the Xianyang and Huaxian stations (denoted as UCX and UCH, respectively). The results indicate that (1) 2-day and 3-day consecutive rainfall are highly correlated with the annual maximum flood discharge (AMF) in UCX and UCH, respectively; and (2) univariate and bivariate return periods, risk and reliability for the purposes of flood control and sediment transport are successfully estimated. Sedimentation triggers higher risks of damaging the safety of local flood control systems compared with the AMF, exceeding the design flood of downstream hydraulic structures in the UCX and UCH. Most importantly, there was considerable sampling uncertainty in the univariate and bivariate hydrologic risk analysis, which would greatly challenge measures of future flood mitigation. The proposed hydrological risk framework offers a promising technical reference for flood risk analysis in sandy regions worldwide.

Random matrix theory analysis of cross-correlations in the US stock market: Evidence from Pearson’s correlation coefficient and detrended cross-correlation coefficient

NASA Astrophysics Data System (ADS)

Wang, Gang-Jin; Xie, Chi; Chen, Shou; Yang, Jiao-Jiao; Yang, Ming-Yan

2013-09-01

In this study, we first build two empirical cross-correlation matrices in the US stock market by two different methods, namely the Pearson’s correlation coefficient and the detrended cross-correlation coefficient (DCCA coefficient). Then, combining the two matrices with the method of random matrix theory (RMT), we mainly investigate the statistical properties of cross-correlations in the US stock market. We choose the daily closing prices of 462 constituent stocks of S&P 500 index as the research objects and select the sample data from January 3, 2005 to August 31, 2012. In the empirical analysis, we examine the statistical properties of cross-correlation coefficients, the distribution of eigenvalues, the distribution of eigenvector components, and the inverse participation ratio. From the two methods, we find some new results of the cross-correlations in the US stock market in our study, which are different from the conclusions reached by previous studies. The empirical cross-correlation matrices constructed by the DCCA coefficient show several interesting properties at different time scales in the US stock market, which are useful to the risk management and optimal portfolio selection, especially to the diversity of the asset portfolio. It will be an interesting and meaningful work to find the theoretical eigenvalue distribution of a completely random matrix R for the DCCA coefficient because it does not obey the Marčenko-Pastur distribution.

Explaining fruit and vegetable intake using a consumer marketing tool.

PubMed

Della, Lindsay J; Dejoy, David M; Lance, Charles E

2009-10-01

In response to calls to reinvent the 5 A Day fruit and vegetable campaign, this study assesses the utility of VALS, a consumer-based audience segmentation tool that divides the U.S. population into groups leading similar lifestyles. The study examines whether the impact of theory of planned behavior (TPB) constructs varies across VALS groups in a cross-sectional sample of 1,588 U.S. adults. In a multigroup structural equation model, the VALS audience group variable moderated latent TPB relationships. Attitudes, subjective norms, and perceived behavioral control explained 57% to 70% of the variation in intention to eat fruit and vegetables across 5 different VALS groups. Perceived behavioral control and intention also predicted self-reported consumption behavior (R2 = 20% to 71% across VALS groups). Bivariate z tests were calculated to determine statistical differences in parameter estimates across groups. Nine of the bivariate z tests were statistically significant (p < or = .04), with standardized coefficients ranging from .05 to .70. These findings confirm the efficacy of using the TPB to explain variation in fruit and vegetable consumption as well as the validity of using a consumer-based algorithm to segment audiences for fruit and vegetable consumption messaging.

The relation between working conditions, aberrant driving behaviour and crash propensity among taxi drivers in China.

PubMed

Wang, Yonggang; Li, Linchao; Prato, Carlo G

2018-04-03

Although the taxi industry is playing an important role in Chinese everyday life, little attention has been posed towards occupational health issues concerning the taxi drivers' working conditions, driving behaviour and road safety. A cross-sectional survey was administered to 1021 taxi drivers from 21 companies in four Chinese cities and collected information about (i) sociodemographic characteristics, (ii) working conditions, (iii) frequency of daily aberrant driving behaviour, and (iv) involvement in property-damage-only (PDO) and personal injury (PI) crashes over the past two years. A hybrid bivariate model of crash involvement was specified: (i) the hybrid part concerned a latent variable model capturing unobserved traits of the taxi drivers; (ii) the bivariate part modelled jointly both types of crashes while capturing unobserved correlation between error terms. The survey answers paint a gloomy picture in terms of workload, as taxi drivers reported averages of 9.4 working hours per day and 6.7 working days per week that amount on average to about 63.0 working hours per week. Moreover, the estimates of the hybrid bivariate model reveal that increasing levels of fatigue, reckless behaviour and aggressive behaviour are positively related to a higher propensity of crash involvement. Lastly, the heavy workload is also positively correlated with the higher propensity of crashing, not only directly as a predictor of crash involvement, but also indirectly as a covariate of fatigue and aberrant driving behaviour. The findings from this study provide insights into potential strategies for preventive education and taxi industry management to improve the working conditions and hence reduce fatigue and road risk for the taxi drivers. Copyright © 2018 Elsevier Ltd. All rights reserved.

Identifying presence of correlated errors in GRACE monthly harmonic coefficients using machine learning algorithms

NASA Astrophysics Data System (ADS)

Piretzidis, Dimitrios; Sra, Gurveer; Karantaidis, George; Sideris, Michael G.

2017-04-01

A new method for identifying correlated errors in Gravity Recovery and Climate Experiment (GRACE) monthly harmonic coefficients has been developed and tested. Correlated errors are present in the differences between monthly GRACE solutions, and can be suppressed using a de-correlation filter. In principle, the de-correlation filter should be implemented only on coefficient series with correlated errors to avoid losing useful geophysical information. In previous studies, two main methods of implementing the de-correlation filter have been utilized. In the first one, the de-correlation filter is implemented starting from a specific minimum order until the maximum order of the monthly solution examined. In the second one, the de-correlation filter is implemented only on specific coefficient series, the selection of which is based on statistical testing. The method proposed in the present study exploits the capabilities of supervised machine learning algorithms such as neural networks and support vector machines (SVMs). The pattern of correlated errors can be described by several numerical and geometric features of the harmonic coefficient series. The features of extreme cases of both correlated and uncorrelated coefficients are extracted and used for the training of the machine learning algorithms. The trained machine learning algorithms are later used to identify correlated errors and provide the probability of a coefficient series to be correlated. Regarding SVMs algorithms, an extensive study is performed with various kernel functions in order to find the optimal training model for prediction. The selection of the optimal training model is based on the classification accuracy of the trained SVM algorithm on the same samples used for training. Results show excellent performance of all algorithms with a classification accuracy of 97% - 100% on a pre-selected set of training samples, both in the validation stage of the training procedure and in the subsequent use of the trained algorithms to classify independent coefficients. This accuracy is also confirmed by the external validation of the trained algorithms using the hydrology model GLDAS NOAH. The proposed method meet the requirement of identifying and de-correlating only coefficients with correlated errors. Also, there is no need of applying statistical testing or other techniques that require prior de-correlation of the harmonic coefficients.

Factors That Attenuate the Correlation Coefficient and Its Analogs.

ERIC Educational Resources Information Center

Dolenz, Beverly

The correlation coefficient is an integral part of many other statistical techniques (analysis of variance, t-tests, etc.), since all analytic methods are actually correlational (G. V. Glass and K. D. Hopkins, 1984). The correlation coefficient is a statistical summary that represents the degree and direction of relationship between two variables.…

Pressure loss modulus correlation for Delta p across uniformly distributed-loss devices

NASA Technical Reports Server (NTRS)

Nunz, Gregory J.

1994-01-01

A dimensionless group, called a pressure loss modulus (N(sub PL)), is introduced that, in conjunction with an appropriately defined Reynolds number, is of considerable engineering utility in correlating steady-state Delta p vs flow calibration data and subsequently as a predictor, using the same or a different fluid, in uniformly distributed pressure loss devices. It is particularly useful under operation in the transition regime. Applications of this simple bivariate correlation to three diverse devices of particular interest for small liquid rocket engine fluid systems are discussed: large L/D capillary tube restrictors, packed granular catalyst beds, and stacked vortex-loss disk restrictors.

ppcor: An R Package for a Fast Calculation to Semi-partial Correlation Coefficients.

PubMed

Kim, Seongho

2015-11-01

Lack of a general matrix formula hampers implementation of the semi-partial correlation, also known as part correlation, to the higher-order coefficient. This is because the higher-order semi-partial correlation calculation using a recursive formula requires an enormous number of recursive calculations to obtain the correlation coefficients. To resolve this difficulty, we derive a general matrix formula of the semi-partial correlation for fast computation. The semi-partial correlations are then implemented on an R package ppcor along with the partial correlation. Owing to the general matrix formulas, users can readily calculate the coefficients of both partial and semi-partial correlations without computational burden. The package ppcor further provides users with the level of the statistical significance with its test statistic.

Impact of physical activity and cardiovascular fitness on total homocysteine concentrations in European adolescents: The HELENA study.

PubMed

Benser, Jasmin; Valtueña, Jara; Ruiz, Jonatan R; Mielgo-Ayuso, Juan; Breidenassel, Christina; Vicente-Rodriguez, German; Ferrari, Marika; Widhalm, Kurt; Manios, Yannis; Sjöström, Michael; Molnar, Denes; Gómez-Martínez, Sonia; Kafatos, Antony; Palacios, Gonzalo; Moreno, Luis A; Castillo, Manuel J; Stehle, Peter; González-Gross, Marcela

2015-01-01

We examined the association of physical activity (PA), cardiovascular fitness (CVF) and fatness with total homocysteine (tHcy) concentrations in European adolescents. The present study comprised 713 European adolescents aged 14.8 ± 1.2 y (females 55.3%) from the multicenter HELENA cross-sectional study. PA was assessed through accelerometry, CVF by the 20-m shuttle run test, and body fat by skinfold thicknesses with the Slaughter equation. Plasma folate, cobalamin, and tHcy concentrations were measured. To examine the association of tHcy with PA, CVF, and fatness after controlling for a set of confounders including age, maturity, folate, cobalamin, creatinine, smoking, supplement use, and methylenetetrahydrofolate reductase 677 genotype (CC 47%, CT 43%, TT 10%), bivariate correlations followed by multiple regression models were performed. In the bivariate correlation analysis, tHcy concentrations were slightly negatively correlated (p<0.05) with CVF in females (measured both by stages: r=-0.118 and by VO2max: r=-0.102) and positively with body mass index (r=0.100). However, daily time spent with moderate and vigorous PA showed a weak positive association with tHcy in females (p<0.05). tHcy concentrations showed a tendency to decrease with increasing CVF and increase with increasing BMI in female European adolescents. However, tHcy concentrations were positively associated with moderate and vigorous PA in female European adolescents.

Bivariate Gaussian bridges: directional factorization of diffusion in Brownian bridge models.

PubMed

Kranstauber, Bart; Safi, Kamran; Bartumeus, Frederic

2014-01-01

In recent years high resolution animal tracking data has become the standard in movement ecology. The Brownian Bridge Movement Model (BBMM) is a widely adopted approach to describe animal space use from such high resolution tracks. One of the underlying assumptions of the BBMM is isotropic diffusive motion between consecutive locations, i.e. invariant with respect to the direction. Here we propose to relax this often unrealistic assumption by separating the Brownian motion variance into two directional components, one parallel and one orthogonal to the direction of the motion. Our new model, the Bivariate Gaussian bridge (BGB), tracks movement heterogeneity across time. Using the BGB and identifying directed and non-directed movement within a trajectory resulted in more accurate utilisation distributions compared to dynamic Brownian bridges, especially for trajectories with a non-isotropic diffusion, such as directed movement or Lévy like movements. We evaluated our model with simulated trajectories and observed tracks, demonstrating that the improvement of our model scales with the directional correlation of a correlated random walk. We find that many of the animal trajectories do not adhere to the assumptions of the BBMM. The proposed model improves accuracy when describing the space use both in simulated correlated random walks as well as observed animal tracks. Our novel approach is implemented and available within the "move" package for R.

Optimal portfolio strategy with cross-correlation matrix composed by DCCA coefficients: Evidence from the Chinese stock market

NASA Astrophysics Data System (ADS)

Sun, Xuelian; Liu, Zixian

2016-02-01

In this paper, a new estimator of correlation matrix is proposed, which is composed of the detrended cross-correlation coefficients (DCCA coefficients), to improve portfolio optimization. In contrast to Pearson's correlation coefficients (PCC), DCCA coefficients acquired by the detrended cross-correlation analysis (DCCA) method can describe the nonlinear correlation between assets, and can be decomposed in different time scales. These properties of DCCA make it possible to improve the investment effect and more valuable to investigate the scale behaviors of portfolios. The minimum variance portfolio (MVP) model and the Mean-Variance (MV) model are used to evaluate the effectiveness of this improvement. Stability analysis shows the effect of two kinds of correlation matrices on the estimation error of portfolio weights. The observed scale behaviors are significant to risk management and could be used to optimize the portfolio selection.

Relationships among the slopes of lines derived from various data analysis techniques and the associated correlation coefficient

NASA Technical Reports Server (NTRS)

Cohen, S. C.

1980-01-01

A technique for fitting a straight line to a collection of data points is given. The relationships between the slopes and correlation coefficients, and between the corresponding standard deviations and correlation coefficient are given.

Common genetic variants explain the majority of the correlation between height and intelligence: the generation Scotland study.

PubMed

Marioni, Riccardo E; Batty, G David; Hayward, Caroline; Kerr, Shona M; Campbell, Archie; Hocking, Lynne J; Porteous, David J; Visscher, Peter M; Deary, Ian J

2014-03-01

Greater height and higher intelligence test scores are predictors of better health outcomes. Here, we used molecular (single-nucleotide polymorphism) data to estimate the genetic correlation between height and general intelligence (g) in 6,815 unrelated subjects (median age 57, IQR 49-63) from the Generation Scotland: Scottish Family Health Study cohort. The phenotypic correlation between height and g was 0.16 (SE 0.01). The genetic correlation between height and g was 0.28 (SE 0.09) with a bivariate heritability estimate of 0.71. Understanding the molecular basis of the correlation between height and intelligence may help explain any shared role in determining health outcomes. This study identified a modest genetic correlation between height and intelligence with the majority of the phenotypic correlation being explained by shared genetic influences.

On the Genetic and Environmental Correlations between Trait Emotional Intelligence and Vocational Interest Factors.

PubMed

Schermer, Julie Aitken; Petrides, Konstantinos V; Vernon, Philip A

2015-04-01

The phenotypic (observed), genetic, and environmental correlations were examined in a sample of adult twins between the four factors and global score of the trait emotional intelligence questionnaire (TEIQue) and the seven vocational interest factors of the Jackson Career Explorer (JCE). Multiple significant correlations were found involving the work style vocational interest factor (consisting of job security, stamina, accountability, planfulness, and interpersonal confidence) and the social vocational interest factor (which included interests in the social sciences, personal services, teaching, social services, and elementary education), both of which correlated significantly with all of the TEIQue variables (well-being, self-control, emotionality, sociability, and global trait EI). Following bivariate genetic analyses, most of the significant phenotypic correlations were found to also have significant genetic correlations as well as significant non-shared (unique) environmental correlations.

Spirituality/Religiosity, Life Satisfaction, and Life Meaning as Protective Factors for Nonsuicidal Self-Injury in College Students

ERIC Educational Resources Information Center

Kress, Victoria E.; Newgent, Rebecca A.; Whitlock, Janis; Mease, Laura

2015-01-01

The purpose of this study was to identify factors that may protect or insulate people from engaging in nonsuicidal self-injury (NSSI). College students (N = 14,385) from 8 universities participated in a web-based survey. Results of bivariate correlations and multiple regression revealed that spirituality/religiosity, life satisfaction, and life…

Testing for the Endogenous Nature between Women's Empowerment and Antenatal Health Care Utilization: Evidence from a Cross-Sectional Study in Egypt

PubMed Central

Hussein, Mohamed Ali

2014-01-01

Women's relative lack of decision-making power and their unequal access to employment, finances, education, basic health care, and other resources are considered to be the root causes of their ill-health and that of their children. The main purpose of this paper is to examine the interactive relation between women's empowerment and the use of maternal health care. Two model specifications are tested. One assumes no correlation between empowerment and antenatal care while the second specification allows for correlation. Both the univariate and the recursive bivariate probit models are tested. The data used in this study is EDHS 2008. Factor Analysis Technique is also used to construct some of the explanatory variables such as the availability and quality of health services indicators. The findings show that women's empowerment and receiving regular antenatal care are simultaneously determined and the recursive bivariate probit is a better approximation to the relationship between them. Women's empowerment has significant and positive impact on receiving regular antenatal care. The availability and quality of health services do significantly increase the likelihood of receiving regular antenatal care. PMID:25140310

Correlation Between Minimum Apparent Diffusion Coefficient (ADCmin) and Tumor Cellularity: A Meta-analysis.

PubMed

Surov, Alexey; Meyer, Hans Jonas; Wienke, Andreas

2017-07-01

Diffusion-weighted imaging (DWI) is a magnetic resonance imaging (MRI) technique based on measure of water diffusion that can provide information about tissue microstructure, especially about cell count. Increase of cell density induces restriction of water diffusion and decreases apparent diffusion coefficient (ADC). ADC can be divided into three sub-parameters: ADC minimum or ADC min , mean ADC or ADC mean and ADC maximum or ADC max Some studies have suggested that ADC min shows stronger correlations with cell count in comparison to other ADC fractions and may be used as a parameter for estimation of tumor cellularity. The aim of the present meta-analysis was to summarize correlation coefficients between ADC min and cellularity in different tumors based on large patient data. For this analysis, MEDLINE database was screened for associations between ADC and cell count in different tumors up to September 2016. For this work, only data regarding ADC min were included. Overall, 12 publications with 317 patients were identified. Spearman's correlation coefficient was used to analyze associations between ADC min and cellularity. The reported Pearson correlation coefficients in some publications were converted into Spearman correlation coefficients. The pooled correlation coefficient for all included studies was ρ=-0.59 (95% confidence interval (CI)=-0.72 to -0.45), heterogeneity Tau 2 =0.04 (p<0.0001), I 2 =73%, test for overall effect Z=8.67 (p<0.00001). ADC min correlated moderately with tumor cellularity. The calculated correlation coefficient is not stronger in comparison to the reported coefficient for ADC mean and, therefore, ADC min does not represent a better means to reflect cellularity. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Correlation of human papillomavirus status with apparent diffusion coefficient of diffusion-weighted MRI in head and neck squamous cell carcinomas.

PubMed

Driessen, Juliette P; van Bemmel, Alexander J M; van Kempen, Pauline M W; Janssen, Luuk M; Terhaard, Chris H J; Pameijer, Frank A; Willems, Stefan M; Stegeman, Inge; Grolman, Wilko; Philippens, Marielle E P

2016-04-01

Identification of prognostic patient characteristics in head and neck squamous cell carcinoma (HNSCC) is of great importance. Human papillomavirus (HPV)-positive HNSCCs have favorable response to (chemo)radiotherapy. Apparent diffusion coefficient, derived from diffusion-weighted MRI, has also shown to predict treatment response. The purpose of this study was to evaluate the correlation between HPV status and apparent diffusion coefficient. Seventy-three patients with histologically proven HNSCC were retrospectively analyzed. Mean pretreatment apparent diffusion coefficient was calculated by delineation of total tumor volume on diffusion-weighted MRI. HPV status was analyzed and correlated to apparent diffusion coefficient. Six HNSCCs were HPV-positive. HPV-positive HNSCC showed significantly lower apparent diffusion coefficient compared to HPV-negative. This correlation was independent of other patient characteristics. In HNSCC, positive HPV status correlates with low mean apparent diffusion coefficient. The favorable prognostic value of low pretreatment apparent diffusion coefficient might be partially attributed to patients with a positive HPV status. © 2015 Wiley Periodicals, Inc. Head Neck 38: E613-E618, 2016. © 2015 Wiley Periodicals, Inc.

Public Figure Attacks in the United States, 1995-2015.

PubMed

Meloy, J Reid; Amman, Molly

2016-09-01

An archival descriptive study of public figure attackers in the United States between 1995 and 2015 was undertaken. Fifty-six incidents were identified, primarily through exhaustive internet searches, composed of 58 attackers and 58 victims. A code book was developed which focused upon victims, offenders, pre-attack behaviors including direct threats, attack characteristics, post-offense and other outcomes, motivations and psychological abstracts. The average interrater agreement for coding of bivariate variables was 0.835 (intraclass correlation coefficient). The three most likely victim categories were politicians, judges, and athletes. Attackers were males, many with a psychiatric disorder, most were grandiose, and most had both a violent and nonviolent criminal history. The known motivations for the attacks were often angry and personal, the most common being dissatisfaction with a judicial or other governmental process (23%). In only one case was the primary motivation to achieve notoriety. Lethality risk during an attack was 55%. Collateral injury or death occurred in 29% of the incidents. Only 5% communicated a direct threat to the target beforehand. The term "publicly intimate figure" is introduced to describe the sociocultural blurring of public and private lives among the targets, and its possible role in some attackers' perceptions and motivations. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Professional Success and Gender in Family Medicine: Design of Scales and Examination of Gender Differences in Subjective and Objective Success Among Family Physicians.

PubMed

Delgado, Ana; Saletti-Cuesta, Lorena; López-Fernández, Luis Andrés; Toro-Cárdenas, Silvia; Luna del Castillo, Juan de Dios

2016-03-01

Two components of professional success have been defined: objective career success (OCS) and subjective career success (SCS). Despite the increasing number of women practicing medicine, gender inequalities persist. The objectives of this descriptive, cross-sectional, and multicenter study were (a) to construct and validate OCS and SCS scales, (b) to determine the relationships between OCS and SCS and between each scale and professional/family characteristics, and (c) to compare these associations between male and female family physicians (FPs). The study sample comprised 250 female and 250 male FPs from urban health centers in Andalusia (Spain). Data were gathered over 6 months on gender, age, care load, professional/family variables, and family-work balance, using a self-administered questionnaire. OSC and SCS scales were examined by using exploratory factorial analysis and Cronbach's α, and scores were compared by gender-stratified bivariate and multiple regression analyses. Intraclass correlation coefficients were calculated using a multilevel analysis. The response rate was 73.6%. We identified three OCS factors and two SCS factors. Lower scores were obtained by female versus male FPs in the OCS dimensions, but there were no gender differences in either SCS dimension. © The Author(s) 2014.

Agreement of Axillary and Auricular Temperature with Rectal Temperature in Systemically Healthy Dogs Undergoing Surgery.

PubMed

Cichocki, Brandy; Dugat, Danielle; Payton, Mark

Obtaining a patient's temperature is an important part of a patient's physical examination. As human medicine transitions to noninvasive temperature measurements, so does veterinary medicine. Historically, temperature measurement has been obtained from rectal readings; however, alternative methods, such as axillary and auricular temperatures, are increasing in popularity. The purpose of the study was to compare these alternative techniques to the gold standard of rectal temperature. Temperatures were obtained three ways for each patient: rectal, axillary, and auricular. Results indicated a positive linear relationship between rectal and axillary temperatures (bivariate correlation coefficient [r] = 0.65, P < .001) and axillary and auricular temperatures (r = 0.55, P < .001). Agreement was strongest between rectal and auricular temperatures (r = 0.80, P < .001). The average discrepancy between axillary and rectal temperature was 1.2°C [2.1°F] with the highest difference being 4.0°C [7.3°F]. The average discrepancy between auricular and rectal temperature was 0.6°C [1.2°F] with the highest difference being 2.2°C [4.1°F]. Despite auricular temperatures having stronger agreement, Bland-Altman Limits of Agreement testing revealed that it was a poor predictor of rectal temperature. Based on these results, axillary and auricular temperatures should not be substituted for rectal temperature.

Similarity analysis between chromosomes of Homo sapiens and monkeys with correlation coefficient, rank correlation coefficient and cosine similarity measures

PubMed Central

Someswara Rao, Chinta; Viswanadha Raju, S.

2016-01-01

In this paper, we consider correlation coefficient, rank correlation coefficient and cosine similarity measures for evaluating similarity between Homo sapiens and monkeys. We used DNA chromosomes of genome wide genes to determine the correlation between the chromosomal content and evolutionary relationship. The similarity among the H. sapiens and monkeys is measured for a total of 210 chromosomes related to 10 species. The similarity measures of these different species show the relationship between the H. sapiens and monkey. This similarity will be helpful at theft identification, maternity identification, disease identification, etc. PMID:26981409

Similarity analysis between chromosomes of Homo sapiens and monkeys with correlation coefficient, rank correlation coefficient and cosine similarity measures.

PubMed

Someswara Rao, Chinta; Viswanadha Raju, S

2016-03-01

In this paper, we consider correlation coefficient, rank correlation coefficient and cosine similarity measures for evaluating similarity between Homo sapiens and monkeys. We used DNA chromosomes of genome wide genes to determine the correlation between the chromosomal content and evolutionary relationship. The similarity among the H. sapiens and monkeys is measured for a total of 210 chromosomes related to 10 species. The similarity measures of these different species show the relationship between the H. sapiens and monkey. This similarity will be helpful at theft identification, maternity identification, disease identification, etc.

The Validity of Left Ventricular Mass as a Surrogate End Point for All-Cause and Cardiovascular Mortality Outcomes in People With CKD: A Systematic Review and Meta-analysis.

PubMed

Badve, Sunil V; Palmer, Suetonia C; Strippoli, Giovanni F M; Roberts, Matthew A; Teixeira-Pinto, Armando; Boudville, Neil; Cass, Alan; Hawley, Carmel M; Hiremath, Swapnil S; Pascoe, Elaine M; Perkovic, Vlado; Whalley, Gillian A; Craig, Jonathan C; Johnson, David W

2016-10-01

Left ventricular mass (LVM) is a widely used surrogate end point in randomized trials involving people with chronic kidney disease (CKD) because treatment-induced LVM reductions are assumed to lower cardiovascular risk. The aim of this study was to assess the validity of LVM as a surrogate end point for all-cause and cardiovascular mortality in CKD. Systematic review and meta-analysis. Participants with any stages of CKD. Randomized controlled trials with 3 or more months' follow-up that reported LVM data. Any pharmacologic or nonpharmacologic intervention. The surrogate outcome of interest was LVM change from baseline to last measurement, and clinical outcomes of interest were all-cause and cardiovascular mortality. Standardized mean differences (SMDs) of LVM change and relative risk for mortality were estimated using pairwise random-effects meta-analysis. Correlations between surrogate and clinical outcomes were summarized across all interventions combined using bivariate random-effects Bayesian models, and 95% credible intervals were computed. 73 trials (6,732 participants) covering 25 intervention classes were included in the meta-analysis. Overall, risk of bias was uncertain or high. Only 3 interventions reduced LVM: erythropoiesis-stimulating agents (9 trials; SMD, -0.13; 95% CI, -0.23 to -0.03), renin-angiotensin-aldosterone system inhibitors (13 trials; SMD, -0.28; 95% CI, -0.45 to -0.12), and isosorbide mononitrate (2 trials; SMD, -0.43; 95% CI, -0.72 to -0.14). All interventions had uncertain effects on all-cause and cardiovascular mortality. There were weak and imprecise associations between the effects of interventions on LVM change and all-cause (32 trials; 5,044 participants; correlation coefficient, 0.28; 95% credible interval, -0.13 to 0.59) and cardiovascular mortality (13 trials; 2,327 participants; correlation coefficient, 0.30; 95% credible interval, -0.54 to 0.76). Limited long-term data, suboptimal quality of included studies. There was no clear and consistent association between intervention-induced LVM change and mortality. Evidence for LVM as a valid surrogate end point in CKD is currently lacking. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

Recurrent major depression and right hippocampal volume: A bivariate linkage and association study.

PubMed

Mathias, Samuel R; Knowles, Emma E M; Kent, Jack W; McKay, D Reese; Curran, Joanne E; de Almeida, Marcio A A; Dyer, Thomas D; Göring, Harald H H; Olvera, Rene L; Duggirala, Ravi; Fox, Peter T; Almasy, Laura; Blangero, John; Glahn, David C

2016-01-01

Previous work has shown that the hippocampus is smaller in the brains of individuals suffering from major depressive disorder (MDD) than those of healthy controls. Moreover, right hippocampal volume specifically has been found to predict the probability of subsequent depressive episodes. This study explored the utility of right hippocampal volume as an endophenotype of recurrent MDD (rMDD). We observed a significant genetic correlation between the two traits in a large sample of Mexican American individuals from extended pedigrees (ρg = -0.34, p = 0.013). A bivariate linkage scan revealed a significant pleiotropic quantitative trait locus on chromosome 18p11.31-32 (LOD = 3.61). Bivariate association analysis conducted under the linkage peak revealed a variant (rs574972) within an intron of the gene SMCHD1 meeting the corrected significance level (χ(2) = 19.0, p = 7.4 × 10(-5)). Univariate association analyses of each phenotype separately revealed that the same variant was significant for right hippocampal volume alone, and also revealed a suggestively significant variant (rs12455524) within the gene DLGAP1 for rMDD alone. The results implicate right-hemisphere hippocampal volume as a possible endophenotype of rMDD, and in so doing highlight a potential gene of interest for rMDD risk. © 2015 Wiley Periodicals, Inc.

Correlates of early pregnancy serum brain-derived neurotrophic factor in a Peruvian population.

PubMed

Yang, Na; Levey, Elizabeth; Gelaye, Bizu; Zhong, Qiu-Yue; Rondon, Marta B; Sanchez, Sixto E; Williams, Michelle A

2017-12-01

Knowledge about factors that influence serum brain-derived neurotrophic factor (BDNF) concentrations during early pregnancy is lacking. The aim of the study is to examine the correlates of early pregnancy serum BDNF concentrations. A total of 982 women attending prenatal care clinics in Lima, Peru, were recruited in early pregnancy. Pearson's correlation coefficient was calculated to evaluate the relation between BDNF concentrations and continuous covariates. Analysis of variance and generalized linear models were used to compare the unadjusted and adjusted BDNF concentrations according to categorical variables. Multivariable linear regression models were applied to determine the factors that influence early pregnancy serum BDNF concentrations. In bivariate analysis, early pregnancy serum BDNF concentrations were positively associated with maternal age (r = 0.16, P < 0.001) and early pregnancy body mass index (BMI) (r = 0.17, P < 0.001), but inversely correlated with gestational age at sample collection (r = -0.21, P < 0.001) and C-reactive protein (CRP) concentrations (r = -0.07, P < 0.05). In the multivariable linear regression model, maternal age (β = 0.11, P = 0.001), early pregnancy BMI (β = 1.58, P < 0.001), gestational age at blood collection (β = -0.33, P < 0.001), and serum CRP concentrations (β = -0.57, P = 0.002) were significantly associated with early pregnancy serum BDNF concentrations. Participants with moderate antepartum depressive symptoms (Patient Health Questionnaire-9 (PHQ-9) score ≥ 10) had lower serum BDNF concentrations compared with participants with no/mild antepartum depressive symptoms (PHQ-9 score < 10). Maternal age, early pregnancy BMI, gestational age, and the presence of moderate antepartum depressive symptoms were statistically significantly associated with early pregnancy serum BDNF concentrations in low-income Peruvian women. Biological changes of CRP during pregnancy may affect serum BDNF concentrations.

Community pharmacy in Lebanon: A societal perspective.

PubMed

Iskandar, Katia; Hallit, Souheil; Raad, Etwal Bou; Droubi, Fida; Layoun, Nelly; Salameh, Pascale

2017-01-01

To assess patients' attitudes towards the community pharmacist's role and determine their negative and positive reactions towards community pharmacists in Lebanon. A cross-sectional study, conducted between January and April 2016, was designed to assess the general public satisfaction with the services provided by the community pharmacies. It was carried out, using a proportionate random sampling of Lebanese community pharmacies from each district. Two sided statistical tests were used to compare between group percentages, Wilcoxon test for quantitative variables with non-homogeneous variances or non-normal distribution, and Student's t-test for quantitative variables of normal distribution and homogeneous variances. The ANOVA test was used to compare between three groups or more, and Pearson correlation coefficient were used to correlate between quantitative variables. a total of 565 participants completely answered the survey questions with a response rate of 94%. The bivariate analysis showed that the patient perception index was positively and significantly correlated with the patient level of expectation index, the overall pharmacy experience and the patient's reason for visiting the pharmacy (p<0.001 for all 3 variables) but was negatively correlated with the barriers for asking questions significantly (p=0.032). On the other hand, this perception index was significantly and positively associated with the number of pharmacy visits, the age categories, the level of education and the family monthly income (p<0.05 for all variables). Public perception and attitude toward community pharmacist in Lebanon is poor despite highly qualified pharmacists. Aspects of pharmacy services most relevant to patients were respect, empathy, a friendly staff, listening carefully, giving quality time, responding quickly to their needs and respecting their privacy. The ministry of Health in Lebanon, along with the Lebanese Order of Pharmacists should educate the pharmacist about working on the different issues patients are complaining about in order to play a more important role in the society and become the number one trusted health care professional.

Community pharmacy in Lebanon: A societal perspective

PubMed Central

Droubi, Fida

2016-01-01

Objective: To assess patients’ attitudes towards the community pharmacist’s role and determine their negative and positive reactions towards community pharmacists in Lebanon. Methods: A cross-sectional study, conducted between January and April 2016, was designed to assess the general public satisfaction with the services provided by the community pharmacies. It was carried out, using a proportionate random sampling of Lebanese community pharmacies from each district. Two sided statistical tests were used to compare between group percentages, Wilcoxon test for quantitative variables with non-homogeneous variances or non-normal distribution, and Student’s t-test for quantitative variables of normal distribution and homogeneous variances. The ANOVA test was used to compare between three groups or more, and Pearson correlation coefficient were used to correlate between quantitative variables. Results: a total of 565 participants completely answered the survey questions with a response rate of 94%. The bivariate analysis showed that the patient perception index was positively and significantly correlated with the patient level of expectation index, the overall pharmacy experience and the patient’s reason for visiting the pharmacy (p<0.001 for all 3 variables) but was negatively correlated with the barriers for asking questions significantly (p=0.032). On the other hand, this perception index was significantly and positively associated with the number of pharmacy visits, the age categories, the level of education and the family monthly income (p<0.05 for all variables). Conclusion: Public perception and attitude toward community pharmacist in Lebanon is poor despite highly qualified pharmacists. Aspects of pharmacy services most relevant to patients were respect, empathy, a friendly staff, listening carefully, giving quality time, responding quickly to their needs and respecting their privacy. The ministry of Health in Lebanon, along with the Lebanese Order of Pharmacists should educate the pharmacist about working on the different issues patients are complaining about in order to play a more important role in the society and become the number one trusted health care professional. PMID:28690690

Modifiable Psychosocial Constructs Associated With Physical Activity Participation in People With Multiple Sclerosis: A Systematic Review and Meta-Analysis.

PubMed

Casey, Blathin; Coote, Susan; Shirazipour, Celina; Hannigan, Ailish; Motl, Robert; Martin Ginis, Kathleen; Latimer-Cheung, Amy

2017-07-01

To synthesize current knowledge of the modifiable psychosocial constructs associated with physical activity (PA) participation in people with multiple sclerosis. A search was conducted through October 2015 in 8 electronic databases: CINAHL, PubMed, SPORTDiscus, Web of Knowledge, MEDLINE, EMBASE, Cochrane Database of Systematic Reviews, and PsycINFO. Cohort and intervention studies were included if they (1) included an objective or subjective measure of PA; (2) measured at least 1 modifiable psychosocial construct; and (3) reported bivariate correlations (or these could be extracted) between the PA and psychosocial construct measures. A total of 13,867 articles were screened for inclusion, and 26 were included in the final analysis. Meta-analyses of correlations were conducted using the Hedges-Olkin method. Where a meta-analysis was not possible, results were reported descriptively. Meta-analyses indicated a pooled correlation coefficient between (1) objective PA and self-efficacy (n=7) of r=.30 (P<.0001), indicating a moderate, positive association; (2) subjective PA and self-efficacy (n=7) of r=.34 (P<.0001), indicating a moderate, positive association; (3) subjective PA and goal-setting (n=5) of r=.44 (P<.0001), indicating a moderate-to-large positive association; and 4) subjective PA and outcome expectancies (n=4) (physical: r=.13, P=.11; social: r=.19, P<.0001; self-evaluative: r=.27, P<.0001), indicating small-moderate positive associations. Other constructs such as measures of health beliefs, enjoyment, social support, and perceived benefits and barriers were reported to be significantly correlated with PA in individual studies, but the number of studies was not sufficient for a meta-analysis. Future PA interventions should continue to focus on the psychosocial constructs of self-efficacy and goal-setting. However, there is a need to explore the associations between other constructs outside those reported in this review. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

A Statistical Method for Synthesizing Mediation Analyses Using the Product of Coefficient Approach Across Multiple Trials

PubMed Central

Huang, Shi; MacKinnon, David P.; Perrino, Tatiana; Gallo, Carlos; Cruden, Gracelyn; Brown, C Hendricks

2016-01-01

Mediation analysis often requires larger sample sizes than main effect analysis to achieve the same statistical power. Combining results across similar trials may be the only practical option for increasing statistical power for mediation analysis in some situations. In this paper, we propose a method to estimate: 1) marginal means for mediation path a, the relation of the independent variable to the mediator; 2) marginal means for path b, the relation of the mediator to the outcome, across multiple trials; and 3) the between-trial level variance-covariance matrix based on a bivariate normal distribution. We present the statistical theory and an R computer program to combine regression coefficients from multiple trials to estimate a combined mediated effect and confidence interval under a random effects model. Values of coefficients a and b, along with their standard errors from each trial are the input for the method. This marginal likelihood based approach with Monte Carlo confidence intervals provides more accurate inference than the standard meta-analytic approach. We discuss computational issues, apply the method to two real-data examples and make recommendations for the use of the method in different settings. PMID:28239330

Correlation coefficient measurement of the mode-locked laser tones using four-wave mixing.

PubMed

Anthur, Aravind P; Panapakkam, Vivek; Vujicic, Vidak; Merghem, Kamel; Lelarge, Francois; Ramdane, Abderrahim; Barry, Liam P

2016-06-01

We use four-wave mixing to measure the correlation coefficient of comb tones in a quantum-dash mode-locked laser under passive and active locked regimes. We study the uncertainty in the measurement of the correlation coefficient of the proposed method.

Challenge of assessing symptoms in seriously ill intensive care unit patients: can proxy reporters help?

PubMed

Puntillo, Kathleen A; Neuhaus, John; Arai, Shoshana; Paul, Steven M; Gropper, Michael A; Cohen, Neal H; Miaskowski, Christine

2012-10-01

Determine levels of agreement among intensive care unit patients and their family members, nurses, and physicians (proxies) regarding patients' symptoms and compare levels of mean intensity (i.e., the magnitude of a symptom sensation) and distress (i.e., the degree of emotionality that a symptom engenders) of symptoms among patients and proxy reporters. Prospective study of proxy reporters of symptoms in seriously ill patients. Two intensive care units in a tertiary medical center in the Western United States. Two hundred and forty-five intensive care unit patients, 243 family members, 103 nurses, and 92 physicians. None. On the basis of the magnitude of intraclass correlation coefficients, where coefficients from .35 to .78 are considered to be appropriately robust, correlation coefficients between patients' and family members' ratings met this criterion (≥.35) for intensity in six of ten symptoms. No intensity ratings between patients and nurses had intraclass correlation coefficients >.32. Three symptoms had intensity correlation coefficients of ≥.36 between patients' and physicians' ratings. Correlation coefficients between patients and family members were >.40 for five symptom-distress ratings. No symptoms had distress correlation coefficients of ≥.28 between patients' and nurses' ratings. Two symptoms had symptom-distress correlation coefficients between patients' and physicians' ratings at >.39. Family members, nurses, and physicians reported higher symptom-intensity scores than patients did for 80%, 60%, and 60% of the symptoms, respectively. Family members, nurses, and physicians reported higher symptom-distress scores than patients did for 90%, 70%, and 80% of the symptoms, respectively. Patient-family intraclass correlation coefficients were sufficiently close for us to consider using family members to help assess intensive care unit patients' symptoms. Relatively low intraclass correlation coefficients between intensive care unit clinicians' and patients' symptom ratings indicate that some proxy raters overestimate whereas others underestimate patients' symptoms. Proxy overestimation of patients' symptom scores warrants further study because this may influence decisions about treating patients' symptoms.

Empirical correlations for axial dispersion coefficient and Peclet number in fixed-bed columns.

PubMed

Rastegar, Seyed Omid; Gu, Tingyue

2017-03-24

In this work, a new correlation for the axial dispersion coefficient was obtained using experimental data in the literature for axial dispersion in fixed-bed columns packed with particles. The Chung and Wen correlation, the De Ligny correlation are two popular empirical correlations. However, the former lacks the molecular diffusion term and the latter does not consider bed voidage. The new axial dispersion coefficient correlation in this work was based on additional experimental data in the literature by considering both molecular diffusion and bed voidage. It is more comprehensive and accurate. The Peclet number correlation from the new axial dispersion coefficient correlation on the average leads to 12% lower Peclet number values compared to the values from the Chung and Wen correlation, and in many cases much smaller than those from the De Ligny correlation. Copyright © 2017 Elsevier B.V. All rights reserved.

Released fraction of polychlorinated biphenyls from soil-biosolid system using a leaching procedure and its comparison with bioavailable fraction determined by wheat plant uptake.

PubMed

Jachero, Lourdes; Leiva, Claudio; Ahumada, Inés; Richter, Pablo

2017-11-01

The bioavailability of polychlorinated biphenyls (PCBs) in soils amended with biosolids was estimated using an aqueous leaching process of the compounds combined with rotating disk sorptive extraction (RDSE), and compared with bioavailability determined through of PCB absorption in wheat plants growing in the same soil-biosolid matrix. The matrices consisted of soil amended with biosolids at doses of 30, 90, and 200 Mg/ha, which increase concomitantly the organic matter content of the matrix. Considering that PCBs were natively absent in both the biosolids and soil used, the compounds were spiked in the biosolids and aged for 10 days. For each biosolid dose, the aqueous leaching profile was studied and equilibrium time was calculated to be 33 h. The leaching fractions determined by RDSE, considering total PCBs studied, were 12, 7, and 6% and the bioavailable fractions absorbed by the wheat root were found to be 0.5, 0.3, and 0.2% for 30, 90, and 200 Mg/ha doses, respectively. Both fractions leachable and bioavailable decrease with both increasing hydrophobicity of the compound (Kow) and increasing in the biosolid dose. It was found that both fractions (leaching and bioavailable) correlated according to the bivariate least squares regression, represented by a coefficient of correlation of 0.86. Therefore, the application of the chemical method involving a leaching procedure is an alternative to estimate the bioavailable fraction of PCBs in wheat plants in a simpler and in a shorter time.

Estimating dim light melatonin onset (DLMO) phase in adolescents using summer or school-year sleep/wake schedules.

PubMed

Crowley, Stephanie J; Acebo, Christine; Fallone, Gahan; Carskadon, Mary A

2006-12-01

This analysis examined associations between the salivary dim light melatonin onset (DLMO) phase and self-selected sleep/ wake schedules in groups of children and adolescents during summer vacation and during the school year to determine the degree to which sleep/wake patterns can estimate salivary DLMO phase. Participants slept at home on self-selected schedules for 5 consecutive nights and reported their bedtime and wake-up time via daily telephone messages. Salivary melatonin was sampled in the laboratory on one evening every 30 minutes in dim light (< 50 lux) to determine DLMO phase. Within group bivariate regressions between sleep pattern measures (bedtime, wake-up time, and midsleep time) and DLMO phase were computed. One group, ages 9 to 17 years (mean age = 12.5, SD = 2.3 years, 74 males, 75 females) contributed 149 DLMO phase and sleep/wake pattern measures while on a school year schedule ("school group"). A separate group, ages 9 to 16 years (mean age = 13.1, SD = 1.3 years, 30 males, 29 females) contributed 59 DLMO phase and sleep/wake pattern measures while on a summer schedule ("summer group"). Bedtime, midsleep time, and wake-up time were positively correlated with DLMO phase in both groups. Although all correlation coefficients for the summer group were statistically greater compared to the school group, the regression equations predicted DLMO phase within +/- 1 hour of the measured DLMO phase in approximately 80% for both groups. DLMO phase can be estimated using self-selected sleep/wake patterns during the school year or summer vacation in healthy children and adolescents.

Multivariate longitudinal data analysis with mixed effects hidden Markov models.

PubMed

Raffa, Jesse D; Dubin, Joel A

2015-09-01

Multiple longitudinal responses are often collected as a means to capture relevant features of the true outcome of interest, which is often hidden and not directly measurable. We outline an approach which models these multivariate longitudinal responses as generated from a hidden disease process. We propose a class of models which uses a hidden Markov model with separate but correlated random effects between multiple longitudinal responses. This approach was motivated by a smoking cessation clinical trial, where a bivariate longitudinal response involving both a continuous and a binomial response was collected for each participant to monitor smoking behavior. A Bayesian method using Markov chain Monte Carlo is used. Comparison of separate univariate response models to the bivariate response models was undertaken. Our methods are demonstrated on the smoking cessation clinical trial dataset, and properties of our approach are examined through extensive simulation studies. © 2015, The International Biometric Society.

Behavioral and Molecular Genetics of Reading-Related AM and FM Detection Thresholds.

PubMed

Bruni, Matthew; Flax, Judy F; Buyske, Steven; Shindhelm, Amber D; Witton, Caroline; Brzustowicz, Linda M; Bartlett, Christopher W

2017-03-01

Auditory detection thresholds for certain frequencies of both amplitude modulated (AM) and frequency modulated (FM) dynamic auditory stimuli are associated with reading in typically developing and dyslexic readers. We present the first behavioral and molecular genetic characterization of these two auditory traits. Two extant extended family datasets were given reading tasks and psychoacoustic tasks to determine FM 2 Hz and AM 20 Hz sensitivity thresholds. Univariate heritabilities were significant for both AM (h 2  = 0.20) and FM (h 2  = 0.29). Bayesian posterior probability of linkage (PPL) analysis found loci for AM (12q, PPL = 81 %) and FM (10p, PPL = 32 %; 20q, PPL = 65 %). Bivariate heritability analyses revealed that FM is genetically correlated with reading, while AM was not. Bivariate PPL analysis indicates that FM loci (10p, 20q) are not also associated with reading.

A tutorial on Bayesian bivariate meta-analysis of mixed binary-continuous outcomes with missing treatment effects.

PubMed

Gajic-Veljanoski, Olga; Cheung, Angela M; Bayoumi, Ahmed M; Tomlinson, George

2016-05-30

Bivariate random-effects meta-analysis (BVMA) is a method of data synthesis that accounts for treatment effects measured on two outcomes. BVMA gives more precise estimates of the population mean and predicted values than two univariate random-effects meta-analyses (UVMAs). BVMA also addresses bias from incomplete reporting of outcomes. A few tutorials have covered technical details of BVMA of categorical or continuous outcomes. Limited guidance is available on how to analyze datasets that include trials with mixed continuous-binary outcomes where treatment effects on one outcome or the other are not reported. Given the advantages of Bayesian BVMA for handling missing outcomes, we present a tutorial for Bayesian BVMA of incompletely reported treatment effects on mixed bivariate outcomes. This step-by-step approach can serve as a model for our intended audience, the methodologist familiar with Bayesian meta-analysis, looking for practical advice on fitting bivariate models. To facilitate application of the proposed methods, we include our WinBUGS code. As an example, we use aggregate-level data from published trials to demonstrate the estimation of the effects of vitamin K and bisphosphonates on two correlated bone outcomes, fracture, and bone mineral density. We present datasets where reporting of the pairs of treatment effects on both outcomes was 'partially' complete (i.e., pairs completely reported in some trials), and we outline steps for modeling the incompletely reported data. To assess what is gained from the additional work required by BVMA, we compare the resulting estimates to those from separate UVMAs. We discuss methodological findings and make four recommendations. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Testing the Difference of Correlated Agreement Coefficients for Statistical Significance

ERIC Educational Resources Information Center

Gwet, Kilem L.

2016-01-01

This article addresses the problem of testing the difference between two correlated agreement coefficients for statistical significance. A number of authors have proposed methods for testing the difference between two correlated kappa coefficients, which require either the use of resampling methods or the use of advanced statistical modeling…

Possible antecedents and consequences of self-esteem in persons with multiple sclerosis: preliminary evidence from a cross-sectional analysis.

PubMed

Dlugonski, Deirdre; Motl, Robert W

2012-02-01

Persons with multiple sclerosis (MS) have consistently reported lower levels of self-esteem compared with the general population. Despite this, very little is known about the antecedents and consequences of self-esteem in persons with MS. To examine (1) physical activity and social support as potentially modifiable correlates (i.e., antecedents) of self-esteem and (2) physical and psychological health-related quality of life as possible consequences of self-esteem in persons with MS. Participants (N = 46) wore an Actigraph accelerometer for 7 days and then completed a battery of questionnaires, including the Rosenberg Self-Esteem Scale (RSES), Multiple Sclerosis Impact Scale (MSIS-29), and Social Provisions Scale (SPS). The data were analyzed using PASW Statistics 18. Bivariate correlation analysis indicated that average daily step counts (r = .298, p = .026) and social support (r = .366, p = .007) were significantly correlated with self-esteem. Multiple linear regression analysis indicated that only social support was a significant predictor of self-esteem scores (β = .411, p = .004); pedometer steps approached significance as a predictor of self-esteem (β = .178, p = .112). Bivariate correlation analysis further indicated significant negative associations between self-esteem and physical (r = -.391, p = .004) and psychological (r = -.540, p = .0001) domains of health-related quality of life (HRQOL), indicating that higher self-esteem was associated with more positive HRQOL. Social support is a potentially modifiable variable that may be important to target when designing interventions to improve self-esteem and this might have implications for improving physical and psychological HRQOL in persons with MS.

Physiological correlates of 2-mile run performance as determined using a novel on-demand treadmill.

PubMed

Tolfrey, Keith; Hansen, Simon A; Dutton, Katie; McKee, Tom; Jones, Andrew M

2009-08-01

The purpose of this study was to assess the reproducibility of an on-demand motorised treadmill to measure 2-mile (3.2 km) race performance and to examine the physiological variables that best predict this free-running performance in active men. Twelve men (mean (SD): age, 28 (9) years; stature, 1.79 (0.05) m; body mass, 72 (9) kg) completed the study in which maximum oxygen uptake (VO2 max), running economy, and running speedin the abstract section. They appear in the rest of the paper.), running economy, and running speed at VO2 max (vVO2 max), lactate threshold (vLT), and 4 mmol.L-1 fixed blood lactate concentration (v4) were measured. Subsequently, the maximal lactate steady state (MLSS) was identified using a series of 30-min treadmill runs. Finally, each participant completed a 2-mile running performance trial on 2 separate occasions, using an on-demand treadmill that adjusts belt speed according to the participant's position on the moving belt. The average 2-mile run speed was 15.7 (SD, 1.9) km.h-1, with small individual differences between repeat-performance trials (intraclass correlation coefficient = 0.99, 95% CI 0.953 to 0.996; standard error of measurement as coefficient of variation = 1.5%, 95% CI 1.0% to 2.5%). Bivariate regression analyses identified VO2 max, vVO2 max, VO2 (mL.kg-1.min-1) at MLSS, vLT, v4, and velocity at MLSS (vMLSS) as the strongest individual predictor variables (r2 = 0.69 to 0.87; standard error of the estimate = 1.08 to 0.72 km.h-1) for 2-mile running performance. The vLT and vMLSS explained 85% and 87% of the variance in running performance, respectively, suggesting that there is considerable shared variance between these parameters. In conclusion, the on-demand treadmill system provided a reliable measure of distance running performance. Both vLT and vMLSS were strong predictors of 2-mile running performance, with vMLSS explaining marginally more of the variance.

Genetic and Environmental Influences on Pulmonary Function and Muscle Strength: The Chinese Twin Study of Aging.

PubMed

Tian, Xiaocao; Xu, Chunsheng; Wu, Yili; Sun, Jianping; Duan, Haiping; Zhang, Dongfeng; Jiang, Baofa; Pang, Zengchang; Li, Shuxia; Tan, Qihua

2017-02-01

Genetic and environmental influences on predictors of decline in daily functioning, including forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), handgrip, and five-times-sit-to-stand test (FTSST), have not been addressed in the aging Chinese population. We performed classical twin modeling on FEV1, FVC, handgrip, and FTSST in 379 twin pairs (240 MZ and 139 DZ) with median age of 50 years (40-80 years). Data were analyzed by fitting univariate and bivariate twin models to estimate the genetic and environmental influences on these measures of physical function. Heritability was moderate for FEV1, handgrip, and FTSST (55-60%) but insignificant for FVC. Only FVC showed moderate control, with shared environmental factors accounting for about 50% of the total variance. In contrast, all measures of pulmonary function and muscle strength showed modest influences from the unique environment (40-50%). Bivariate analysis showed highly positive genetic correlations between FEV1 and FVC (r G = 1.00), and moderately negative genetic correlations between FTSST and FEV1 (r G = -0.33) and FVC (r G = -0.42). FEV1 and FVC, as well as FEV1 and handgrip, displayed high common environmental correlations (r C = 1.00), and there were moderate correlations between FVC and handgrip (r C = 0.44). FEV1 and FVC showed high unique environmental correlations (r E = 0.76) and low correlations between handgrip and FEV1 (r E = 0.17), FVC (r E = 0.14), and FTSST (r E = -0.13) with positive or negative direction. We conclude that genetic factors contribute significantly to the individual differences in common indicators of daily functioning (FEV1, handgrip, and FTSST). FEV1 and FVC were genetically and environmentally correlated. Pulmonary function and FTSST may share similar sets of genes but in the negative direction. Pulmonary function and muscle strength may have a shared environmental background.

Estimating Seven Coefficients of Pairwise Relatedness Using Population-Genomic Data

PubMed Central

Ackerman, Matthew S.; Johri, Parul; Spitze, Ken; Xu, Sen; Doak, Thomas G.; Young, Kimberly; Lynch, Michael

2017-01-01

Population structure can be described by genotypic-correlation coefficients between groups of individuals, the most basic of which are the pairwise relatedness coefficients between any two individuals. There are nine pairwise relatedness coefficients in the most general model, and we show that these can be reduced to seven coefficients for biallelic loci. Although all nine coefficients can be estimated from pedigrees, six coefficients have been beyond empirical reach. We provide a numerical optimization procedure that estimates all seven reduced coefficients from population-genomic data. Simulations show that the procedure is nearly unbiased, even at 3× coverage, and errors in five of the seven coefficients are statistically uncorrelated. The remaining two coefficients have a negative correlation of errors, but their sum provides an unbiased assessment of the overall correlation of heterozygosity between two individuals. Application of these new methods to four populations of the freshwater crustacean Daphnia pulex reveal the occurrence of half siblings in our samples, as well as a number of identical individuals that are likely obligately asexual clone mates. Statistically significant negative estimates of these pairwise relatedness coefficients, including inbreeding coefficients that were typically negative, underscore the difficulties that arise when interpreting genotypic correlations as estimations of the probability that alleles are identical by descent. PMID:28341647

Attenuation of the Squared Canonical Correlation Coefficient under Varying Estimates of Score Reliability

ERIC Educational Resources Information Center

Wilson, Celia M.

2010-01-01

Research pertaining to the distortion of the squared canonical correlation coefficient has traditionally been limited to the effects of sampling error and associated correction formulas. The purpose of this study was to compare the degree of attenuation of the squared canonical correlation coefficient under varying conditions of score reliability.…

Thin and Slow Smoke Detection by Using Frequency Image

NASA Astrophysics Data System (ADS)

Zheng, Guang; Oe, Shunitiro

In this paper, a new method to detect thin and slow smoke for early fire alarm by using frequency image has been proposed. The correlation coefficient of the frequency image between the current stage and the initial stage are calculated, so are the gray image correlation coefficient of the color image. When the thin smoke close to transparent enters into the camera view, the correlation coefficient of the frequency image becomes small, while the gray image correlation coefficient of the color image hardly change and keep large. When something which is not transparent, like human beings, etc., enters into the camera view, the correlation coefficient of the frequency image becomes small, as well as that of color image. Based on the difference of correlation coefficient between frequency image and color image in different situations, the thin smoke can be detected. Also, considering the movement of the thin smoke, miss detection caused by the illustration change or noise can be avoided. Several experiments in different situations are carried out, and the experimental results show the effect of the proposed method.

Statistical Study of Turbulence: Spectral Functions and Correlation Coefficients

NASA Technical Reports Server (NTRS)

Frenkiel, Francois N.

1958-01-01

In reading the publications on turbulence of different authors, one often runs the risk of confusing the various correlation coefficients and turbulence spectra. We have made a point of defining, by appropriate concepts, the differences which exist between these functions. Besides, we introduce in the symbols a few new characteristics of turbulence. In the first chapter, we study some relations between the correlation coefficients and the different turbulence spectra. Certain relations are given by means of demonstrations which could be called intuitive rather than mathematical. In this way we demonstrate that the correlation coefficients between the simultaneous turbulent velocities at two points are identical, whether studied in Lagrange's or in Euler's systems. We then consider new spectra of turbulence, obtained by study of the simultaneous velocities along a straight line of given direction. We determine some relations between these spectra and the correlation coefficients. Examining the relation between the spectrum of the turbulence measured at a fixed point and the longitudinal-correlation curve given by G. I. Taylor, we find that this equation is exact only when the coefficient is very small.

[Electroencephalogram Feature Selection Based on Correlation Coefficient Analysis].

PubMed

Zhou, Jinzhi; Tang, Xiaofang

2015-08-01

In order to improve the accuracy of classification with small amount of motor imagery training data on the development of brain-computer interface (BCD systems, we proposed an analyzing method to automatically select the characteristic parameters based on correlation coefficient analysis. Throughout the five sample data of dataset IV a from 2005 BCI Competition, we utilized short-time Fourier transform (STFT) and correlation coefficient calculation to reduce the number of primitive electroencephalogram dimension, then introduced feature extraction based on common spatial pattern (CSP) and classified by linear discriminant analysis (LDA). Simulation results showed that the average rate of classification accuracy could be improved by using correlation coefficient feature selection method than those without using this algorithm. Comparing with support vector machine (SVM) optimization features algorithm, the correlation coefficient analysis can lead better selection parameters to improve the accuracy of classification.

Combining cow and bull reference populations to increase accuracy of genomic prediction and genome-wide association studies.

PubMed

Calus, M P L; de Haas, Y; Veerkamp, R F

2013-10-01

Genomic selection holds the promise to be particularly beneficial for traits that are difficult or expensive to measure, such that access to phenotypes on large daughter groups of bulls is limited. Instead, cow reference populations can be generated, potentially supplemented with existing information from the same or (highly) correlated traits available on bull reference populations. The objective of this study, therefore, was to develop a model to perform genomic predictions and genome-wide association studies based on a combined cow and bull reference data set, with the accuracy of the phenotypes differing between the cow and bull genomic selection reference populations. The developed bivariate Bayesian stochastic search variable selection model allowed for an unbalanced design by imputing residuals in the residual updating scheme for all missing records. The performance of this model is demonstrated on a real data example, where the analyzed trait, being milk fat or protein yield, was either measured only on a cow or a bull reference population, or recorded on both. Our results were that the developed bivariate Bayesian stochastic search variable selection model was able to analyze 2 traits, even though animals had measurements on only 1 of 2 traits. The Bayesian stochastic search variable selection model yielded consistently higher accuracy for fat yield compared with a model without variable selection, both for the univariate and bivariate analyses, whereas the accuracy of both models was very similar for protein yield. The bivariate model identified several additional quantitative trait loci peaks compared with the single-trait models on either trait. In addition, the bivariate models showed a marginal increase in accuracy of genomic predictions for the cow traits (0.01-0.05), although a greater increase in accuracy is expected as the size of the bull population increases. Our results emphasize that the chosen value of priors in Bayesian genomic prediction models are especially important in small data sets. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Psychosocial correlates of adolescent cannabis use: data from the Italian subsample of the second International Self-Reported Delinquency study.

PubMed

Maniglio, Roberto; Innamorati, Marco

2014-01-01

To provide a comprehensive picture of the whole spectrum of psychosocial factors potentially associated with adolescent cannabis use, bivariate and multivariate analyses were used to assess a variety of social, demographic, psychological, and behavioral correlates of last-month cannabis use and age of first use among 6,838 students. Results showed that only family problems, alcohol and/or other drug use/misuse, deviant behavior, and victimization were independently associated with either recent cannabis use or early onset of cannabis use when multiple, interacting factors were considered. Certain family and behavioral factors might be more important than other psychosocial correlates of adolescent cannabis use.

Quantifying colocalization by correlation: the Pearson correlation coefficient is superior to the Mander's overlap coefficient.

PubMed

Adler, Jeremy; Parmryd, Ingela

2010-08-01

The Pearson correlation coefficient (PCC) and the Mander's overlap coefficient (MOC) are used to quantify the degree of colocalization between fluorophores. The MOC was introduced to overcome perceived problems with the PCC. The two coefficients are mathematically similar, differing in the use of either the absolute intensities (MOC) or of the deviation from the mean (PCC). A range of correlated datasets, which extend to the limits of the PCC, only evoked a limited response from the MOC. The PCC is unaffected by changes to the offset while the MOC increases when the offset is positive. Both coefficients are independent of gain. The MOC is a confusing hybrid measurement, that combines correlation with a heavily weighted form of co-occurrence, favors high intensity combinations, downplays combinations in which either or both intensities are low and ignores blank pixels. The PCC only measures correlation. A surprising finding was that the addition of a second uncorrelated population can substantially increase the measured correlation, demonstrating the importance of excluding background pixels. Overall, since the MOC is unresponsive to substantial changes in the data and is hard to interpret, it is neither an alternative to nor a useful substitute for the PCC. The MOC is not suitable for making measurements of colocalization either by correlation or co-occurrence.

Can Imaging Parameters Provide Information Regarding Histopathology in Head and Neck Squamous Cell Carcinoma? A Meta-Analysis.

PubMed

Surov, Alexey; Meyer, Hans Jonas; Wienke, Andreas

2018-04-01

Our purpose was to provide data regarding relationships between different imaging and histopathological parameters in HNSCC. MEDLINE library was screened for associations between different imaging parameters and histopathological features in HNSCC up to December 2017. Only papers containing correlation coefficients between different imaging parameters and histopathological findings were acquired for the analysis. Associations between 18 F-FDG positron emission tomography (PET) and KI 67 were reported in 8 studies (236 patients). The pooled correlation coefficient was 0.20 (95% CI = [-0.04; 0.44]). Furthermore, in 4 studies (64 patients), associations between 18 F-fluorothymidine PET and KI 67 were analyzed. The pooled correlation coefficient between SUV max and KI 67 was 0.28 (95% CI = [-0.06; 0.94]). In 2 studies (23 patients), relationships between KI 67 and dynamic contrast-enhanced magnetic resonance imaging were reported. The pooled correlation coefficient between K trans and KI 67 was -0.68 (95% CI = [-0.91; -0.44]). Two studies (31 patients) investigated correlation between apparent diffusion coefficient (ADC) and KI 67. The pooled correlation coefficient was -0.61 (95% CI = [-0.84; -0.38]). In 2 studies (117 patients), relationships between 18 F-FDG PET and p53 were analyzed. The pooled correlation coefficient was 0.0 (95% CI = [-0.87; 0.88]). There were 3 studies (48 patients) that investigated associations between ADC and tumor cell count in HNSCC. The pooled correlation coefficient was -0.53 (95% CI = [-0.74; -0.32]). Associations between 18 F-FDG PET and HIF-1α were investigated in 3 studies (72 patients). The pooled correlation coefficient was 0.44 (95% CI = [-0.20; 1.08]). ADC may predict cell count and proliferation activity, and SUV max may predict expression of HIF-1α in HNSCC. SUV max cannot be used as surrogate marker for expression of KI 67 and p53. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

A novel coefficient for detecting and quantifying asymmetry of California electricity market based on asymmetric detrended cross-correlation analysis.

PubMed

Wang, Fang

2016-06-01

In order to detect and quantify asymmetry of two time series, a novel cross-correlation coefficient is proposed based on recent asymmetric detrended cross-correlation analysis (A-DXA), which we called A-DXA coefficient. The A-DXA coefficient, as an important extension of DXA coefficient ρDXA, contains two directional asymmetric cross-correlated indexes, describing upwards and downwards asymmetric cross-correlations, respectively. By using the information of directional covariance function of two time series and directional variance function of each series itself instead of power-law between the covariance function and time scale, the proposed A-DXA coefficient can well detect asymmetry between the two series no matter whether the cross-correlation is significant or not. By means of the proposed A-DXA coefficient conducted over the asymmetry for California electricity market, we found that the asymmetry between the prices and loads is not significant for daily average data in 1999 yr market (before electricity crisis) but extremely significant for those in 2000 yr market (during the crisis). To further uncover the difference of asymmetry between the years 1999 and 2000, a modified H statistic (MH) and ΔMH statistic are proposed. One of the present contributions is that the high MH values calculated for hourly data exist in majority months in 2000 market. Another important conclusion is that the cross-correlation with downwards dominates over the whole 1999 yr in contrast to the cross-correlation with upwards dominates over the 2000 yr.

Detecting PM2.5's Correlations between Neighboring Cities Using a Time-Lagged Cross-Correlation Coefficient.

PubMed

Wang, Fang; Wang, Lin; Chen, Yuming

2017-08-31

In order to investigate the time-dependent cross-correlations of fine particulate (PM2.5) series among neighboring cities in Northern China, in this paper, we propose a new cross-correlation coefficient, the time-lagged q-L dependent height crosscorrelation coefficient (denoted by p q (τ, L)), which incorporates the time-lag factor and the fluctuation amplitude information into the analogous height cross-correlation analysis coefficient. Numerical tests are performed to illustrate that the newly proposed coefficient ρ q (τ, L) can be used to detect cross-correlations between two series with time lags and to identify different range of fluctuations at which two series possess cross-correlations. Applying the new coefficient to analyze the time-dependent cross-correlations of PM2.5 series between Beijing and the three neighboring cities of Tianjin, Zhangjiakou, and Baoding, we find that time lags between the PM2.5 series with larger fluctuations are longer than those between PM2.5 series withsmaller fluctuations. Our analysis also shows that cross-correlations between the PM2.5 series of two neighboring cities are significant and the time lags between two PM2.5 series of neighboring cities are significantly non-zero. These findings providenew scientific support on the view that air pollution in neighboring cities can affect one another not simultaneously but with a time lag.

Limits of the memory coefficient in measuring correlated bursts

NASA Astrophysics Data System (ADS)

Jo, Hang-Hyun; Hiraoka, Takayuki

2018-03-01

Temporal inhomogeneities in event sequences of natural and social phenomena have been characterized in terms of interevent times and correlations between interevent times. The inhomogeneities of interevent times have been extensively studied, while the correlations between interevent times, often called correlated bursts, are far from being fully understood. For measuring the correlated bursts, two relevant approaches were suggested, i.e., memory coefficient and burst size distribution. Here a burst size denotes the number of events in a bursty train detected for a given time window. Empirical analyses have revealed that the larger memory coefficient tends to be associated with the heavier tail of the burst size distribution. In particular, empirical findings in human activities appear inconsistent, such that the memory coefficient is close to 0, while burst size distributions follow a power law. In order to comprehend these observations, by assuming the conditional independence between consecutive interevent times, we derive the analytical form of the memory coefficient as a function of parameters describing interevent time and burst size distributions. Our analytical result can explain the general tendency of the larger memory coefficient being associated with the heavier tail of burst size distribution. We also find that the apparently inconsistent observations in human activities are compatible with each other, indicating that the memory coefficient has limits to measure the correlated bursts.

Assessment of Technical Skills in Young Soccer Goalkeepers: Reliability and Validity of Two Goalkeeper-Specific Tests

PubMed Central

Rebelo-Gonçalves, Ricardo; Figueiredo, António J.; Coelho-e-Silva, Manuel J.; Tessitore, Antonio

2016-01-01

The purpose of this study was to evaluate the reproducibility and validity of two new tests designed to examine goalkeeper-specific technique. Twenty-six goalkeepers (14.49 ± 2.52 years old) completed two trial sessions, each separated by one week, to evaluate the reproducibility of the Sprint-Keeper Test (S-Keeper) and the Lateral Shuffle-Keeper Test (LS-Keeper). Construct validity was assessed among forty goalkeepers (14.49 ± 1.71 years old) by competitive level (elite versus non-elite), after controlling for chronological age. All participants were examined in vertical jump (CMJ and CMJ-free arms), acceleration (5-m and 10-m sprint) and goalkeeper-specific technique. The S-Keeper requires the goalkeeper to accelerate during 3 m and dive over a stationary ball after performing a change of direction in a total distance of 10 m. The LS-Keeper involves three changes of direction and a diving save over a stationary ball, in a total distance of 12.55 m. Performance was respectively measured as total time for the right and left sides in each protocol. Bivariate correlations between repeated measures were high and significant (r = 0.835 – 0.912). Test-retest results for the S-Keeper and LS-Keeper showed good reliability (reliability coefficients > 0.88, intra-class correlation coefficient > 0.908 and coefficients of variation < 4.37%), even though participants tended to improve performance when diving to their right side (p < 0.05). Both tests were able to detect significant differences between elite and non-elite goalkeepers, particularly to the left side (p < 0.05). These findings suggest that the S-Keeper and LS-Keeper are reliable and valid tests for assessing goalkeeper-specific technique. Both protocols can be used as a practical tool to provide relevant information about the influence of several components of performance in the overall execution of a diving save, particularly movement patterns, take-off movements and possible asymmetries. Key points The S-Keeper and LS-Keeper are reliable tools to assess goalkeeper-specific technique, even though a systematic bias was verified when goalkeepers dived to the right side. The S-Keeper and LS-Keeper were also able to discriminate young goalkeepers by competitive level, particularly when performed to the left side after controlling for chronological age. The proposed tests are recommended as practical instruments to assess and provide relevant information about the influence of several components of performance in the overall execution of a diving save (e.g. previous displacement, movement patterns, take-off movements and possible asymmetries). PMID:27803631

Depression in patients with chronic kidney disease on dialysis in Saudi Arabia.

PubMed

Al Zaben, Faten; Khalifa, Doaa Ahmed; Sehlo, Mohammad Gamal; Al Shohaib, Saad; Shaheen, Faisul; Alhozali, Hanadi; Hariri, Alferdose Osama; Ahmad, Riyadh Ghazi; Kabli, Moayad Reda; Koenig, Harold G

2014-12-01

Patients with chronic kidney disease on hemodialysis experience considerable psychological stress due to physical and social changes brought on by illness, increasing the risk of depressive disorder (DD). We examined the prevalence of DD and depressive symptoms, identified treatments for depression, and determined baseline demographic, social/behavioral, physical, and psychological correlates. A convenience sample of 310 dialysis patients in Jeddah, Saudi Arabia, was screened for DD using the Structured Clinical Interview for Depression and for depressive symptoms using the Hamilton Depression Rating Scale (HDRS). Established measures of psychosocial and physical health characteristics were administered, along with questions about current and past treatments. Bivariate and multivariate analyses identified independent correlates of DD and symptoms. The prevalence of DD was 6.8 % (major depression 3.2 %, minor depression 3.6 %), and significant depressive symptoms were present in 24.2 % (HDRS 8 or higher). No patients with DD were being treated with antidepressant medication, whereas 28.6 % (6 of 21) were receiving counseling. Being a Saudi national, married, in counseling, or having a history of antidepressant were associated with DD in bivariate analyses. Correlates of depressive symptoms HDRS in multivariate analyses were Saudi nationality, marital status, stressful life events, poor physical functioning, cognitive impairment, overall severity of medical illness, and history of family psychiatric problems. The prevalence of DD and depressive symptoms is lower in Saudi dialysis patients than in the rest of the world, largely untreated, and is associated with a distinct set of demographic, psychosocial, and physical health characteristics.

IDF relationships using bivariate copula for storm events in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Ariff, N. M.; Jemain, A. A.; Ibrahim, K.; Wan Zin, W. Z.

2012-11-01

SummaryIntensity-duration-frequency (IDF) curves are used in many hydrologic designs for the purpose of water managements and flood preventions. The IDF curves available in Malaysia are those obtained from univariate analysis approach which only considers the intensity of rainfalls at fixed time intervals. As several rainfall variables are correlated with each other such as intensity and duration, this paper aims to derive IDF points for storm events in Peninsular Malaysia by means of bivariate frequency analysis. This is achieved through utilizing the relationship between storm intensities and durations using the copula method. Four types of copulas; namely the Ali-Mikhail-Haq (AMH), Frank, Gaussian and Farlie-Gumbel-Morgenstern (FGM) copulas are considered because the correlation between storm intensity, I, and duration, D, are negative and these copulas are appropriate when the relationship between the variables are negative. The correlations are attained by means of Kendall's τ estimation. The analysis was performed on twenty rainfall stations with hourly data across Peninsular Malaysia. Using Akaike's Information Criteria (AIC) for testing goodness-of-fit, both Frank and Gaussian copulas are found to be suitable to represent the relationship between I and D. The IDF points found by the copula method are compared to the IDF curves yielded based on the typical IDF empirical formula of the univariate approach. This study indicates that storm intensities obtained from both methods are in agreement with each other for any given storm duration and for various return periods.

Correlation between presumed sinusitis-induced pain and paranasal sinus computed tomographic findings.

PubMed

Mudgil, Shikha P; Wise, Scott W; Hopper, Kenneth D; Kasales, Claudia J; Mauger, David; Fornadley, John A

2002-02-01

The correlation between facial and/or head pain in patients clinically suspected of having sinusitis and actual localized findings on sinus computed tomographic (CT) imaging are poorly understood. To prospectively evaluate the relationship of paranasal sinus pain symptoms with CT imaging. Two hundred consecutive patients referred by otolaryngologists and internists for CT of the paranasal sinuses participated by completing a questionnaire immediately before undergoing CT. Three radiologists blinded to the patients' responses scored the degree of air/fluid level, mucosal thickening, bony reaction, and mucus retention cysts using a graded scale of severity (0 to 3 points). The osteomeatal complexes and nasolacrimal ducts were also evaluated for patency. Bivariate analysis was performed to evaluate the relationship between patients' localized symptoms and CT findings in the respective sinus. One hundred sixty-three patients (82%) reported having some form of facial pain or headache. The right temple/forehead was the most frequently reported region of maximal pain. On CT imaging the maxillary sinus was the most frequently involved sinus. Bivariate analysis failed to show any relationship between patient symptoms and findings on CT. Patients with a normal CT reported a mean 5.88 sites of facial or head pain versus 5.45 sites for patients with an abnormal CT. Patient-based responses of sinonasal pain symptoms fail to correlate with findings in the respective sinuses. CT should therefore be reserved for delineating the anatomy and degree of sinus disease before surgical intervention.

Bivariate discrete beta Kernel graduation of mortality data.

PubMed

Mazza, Angelo; Punzo, Antonio

2015-07-01

Various parametric/nonparametric techniques have been proposed in literature to graduate mortality data as a function of age. Nonparametric approaches, as for example kernel smoothing regression, are often preferred because they do not assume any particular mortality law. Among the existing kernel smoothing approaches, the recently proposed (univariate) discrete beta kernel smoother has been shown to provide some benefits. Bivariate graduation, over age and calendar years or durations, is common practice in demography and actuarial sciences. In this paper, we generalize the discrete beta kernel smoother to the bivariate case, and we introduce an adaptive bandwidth variant that may provide additional benefits when data on exposures to the risk of death are available; furthermore, we outline a cross-validation procedure for bandwidths selection. Using simulations studies, we compare the bivariate approach proposed here with its corresponding univariate formulation and with two popular nonparametric bivariate graduation techniques, based on Epanechnikov kernels and on P-splines. To make simulations realistic, a bivariate dataset, based on probabilities of dying recorded for the US males, is used. Simulations have confirmed the gain in performance of the new bivariate approach with respect to both the univariate and the bivariate competitors.

Joint multifractal analysis based on wavelet leaders

NASA Astrophysics Data System (ADS)

Jiang, Zhi-Qiang; Yang, Yan-Hong; Wang, Gang-Jin; Zhou, Wei-Xing

2017-12-01

Mutually interacting components form complex systems and these components usually have long-range cross-correlated outputs. Using wavelet leaders, we propose a method for characterizing the joint multifractal nature of these long-range cross correlations; we call this method joint multifractal analysis based on wavelet leaders (MF-X-WL). We test the validity of the MF-X-WL method by performing extensive numerical experiments on dual binomial measures with multifractal cross correlations and bivariate fractional Brownian motions (bFBMs) with monofractal cross correlations. Both experiments indicate that MF-X-WL is capable of detecting cross correlations in synthetic data with acceptable estimating errors. We also apply the MF-X-WL method to pairs of series from financial markets (returns and volatilities) and online worlds (online numbers of different genders and different societies) and determine intriguing joint multifractal behavior.

Joint multifractal analysis based on the partition function approach: analytical analysis, numerical simulation and empirical application

NASA Astrophysics Data System (ADS)

Xie, Wen-Jie; Jiang, Zhi-Qiang; Gu, Gao-Feng; Xiong, Xiong; Zhou, Wei-Xing

2015-10-01

Many complex systems generate multifractal time series which are long-range cross-correlated. Numerous methods have been proposed to characterize the multifractal nature of these long-range cross correlations. However, several important issues about these methods are not well understood and most methods consider only one moment order. We study the joint multifractal analysis based on partition function with two moment orders, which was initially invented to investigate fluid fields, and derive analytically several important properties. We apply the method numerically to binomial measures with multifractal cross correlations and bivariate fractional Brownian motions without multifractal cross correlations. For binomial multifractal measures, the explicit expressions of mass function, singularity strength and multifractal spectrum of the cross correlations are derived, which agree excellently with the numerical results. We also apply the method to stock market indexes and unveil intriguing multifractality in the cross correlations of index volatilities.

Phenotypic and genetic associations between the big five and trait emotional intelligence.

PubMed

Vernon, Philip A; Villani, Vanessa C; Schermer, Julie Aitken; Petrides, K V

2008-10-01

This study reports the first behavioral genetic investigation of the extent to which genetic and/or environmental factors contribute to the relationship between the Big Five personality factors and trait emotional intelligence. 213 pairs of adult monozygotic twins and 103 pairs of same-sex dizygotic twins completed the NEO-PI-R and the Trait Emotional Intelligence Questionnaire (TEIQue). Replicating previous non-twin studies, many significant phenotypic correlations were found between the Big Five factors - especially Neuroticism, Extraversion, and Conscientiousness - and the facets, factors, and global scores derived from the TEIQue. Bivariate behavioral genetic model-fitting analyses revealed that these phenotypic correlations were primarily attributable to correlated genetic factors and secondarily to correlated non-shared environmental factors. The results support the feasibility of incorporating EI as a trait within existing personality taxonomies.

Bayesian bivariate meta-analysis of correlated effects: Impact of the prior distributions on the between-study correlation, borrowing of strength, and joint inferences

PubMed Central

Bujkiewicz, Sylwia; Riley, Richard D

2016-01-01

Multivariate random-effects meta-analysis allows the joint synthesis of correlated results from multiple studies, for example, for multiple outcomes or multiple treatment groups. In a Bayesian univariate meta-analysis of one endpoint, the importance of specifying a sensible prior distribution for the between-study variance is well understood. However, in multivariate meta-analysis, there is little guidance about the choice of prior distributions for the variances or, crucially, the between-study correlation, ρB; for the latter, researchers often use a Uniform(−1,1) distribution assuming it is vague. In this paper, an extensive simulation study and a real illustrative example is used to examine the impact of various (realistically) vague prior distributions for ρB and the between-study variances within a Bayesian bivariate random-effects meta-analysis of two correlated treatment effects. A range of diverse scenarios are considered, including complete and missing data, to examine the impact of the prior distributions on posterior results (for treatment effect and between-study correlation), amount of borrowing of strength, and joint predictive distributions of treatment effectiveness in new studies. Two key recommendations are identified to improve the robustness of multivariate meta-analysis results. First, the routine use of a Uniform(−1,1) prior distribution for ρB should be avoided, if possible, as it is not necessarily vague. Instead, researchers should identify a sensible prior distribution, for example, by restricting values to be positive or negative as indicated by prior knowledge. Second, it remains critical to use sensible (e.g. empirically based) prior distributions for the between-study variances, as an inappropriate choice can adversely impact the posterior distribution for ρB, which may then adversely affect inferences such as joint predictive probabilities. These recommendations are especially important with a small number of studies and missing data. PMID:26988929

Correlates of anxiety and depression among patients with type 2 diabetes mellitus.

PubMed

Balhara, Yatan Pal Singh; Sagar, Rajesh

2011-07-01

Research has established the relation between diabetes and depression. Both diabetes and anxiety/depression are independently associated with increased morbidity and mortality. The present study aims at assessing the prevalence of anxiety/depression among outpatients receiving treatment for type 2 diabetes. The study was conducted in the endocrinology outpatient department of an urban tertiary care center. The instruments used included a semi-structured questionnaire, HbA1c levels, fasting blood glucose and postprandial blood glucose, Brief Patient Health Questionnaire, and Hospital Anxiety and Depression Scale (HADS). Analysis was carried out using the SPSS version 16.0. Pearson's correlation coefficient was calculated to find out the correlations. ANOVA was carried out for the in between group comparisons. There was a significant correlation between the HADS-Anxiety scale and Body Mass Index (BMI) with a correlation coefficient of 0.34 (P = 0.008). Also, a significant correlation existed between HADS-Depression scale and BMI (correlation coefficient, 0.36; P = 0.004). Significant correlation were observed between the duration of daily physical exercise and HADS-Anxiety (coefficient of correlation, -0.25; P = 0.04) scores. HADS-Anxiety scores were found to be related to HbA1c levels (correlation-coefficient, 0.41; P = 0.03) and postprandial blood glucose levels (correlation-coefficient, 0.51; P = 0.02). Monitoring of biochemical parameters like HbA1c and postprandial blood glucose levels and BMI could be a guide to development of anxiety in these patients. Also, physical exercise seems to have a protective effect on anxiety in those with type 2 diabetes mellitus.

Word Reading Fluency: Role of Genome-Wide Single-Nucleotide Polymorphisms in Developmental Stability and Correlations with Print Exposure

ERIC Educational Resources Information Center

Harlaar, Nicole; Trzaskowski, Maciej; Dale, Philip S.; Plomin, Robert

2014-01-01

The genetic effects on individual differences in reading development were examined using genome-wide complex trait analysis (GCTA) in a twin sample. In unrelated individuals (one twin per pair, n = 2,942), the GCTA-based heritability of reading fluency was ~20%-29% at ages 7 and 12. GCTA bivariate results showed that the phenotypic stability of…

Prediction of friction coefficients for gases

NASA Technical Reports Server (NTRS)

Taylor, M. F.

1969-01-01

Empirical relations are used for correlating laminar and turbulent friction coefficients for gases, with large variations in the physical properties, flowing through smooth tubes. These relations have been used to correlate friction coefficients for hydrogen, helium, nitrogen, carbon dioxide and air.

Exploring moderators of the relationship between physical activity behaviors and television viewing in elementary school children.

PubMed

Smith, Nicole E I; Rhodes, Ryan E; Naylor, Patti-Jean; McKay, Heather A

2008-01-01

Previous research suggests that there is limited evidence to support a negative association between physical activity (PA) behaviors and television (TV) viewing time in children. The purpose of this study was to extend the research involving PA-TV viewing relationships and to explore potential moderators, including gender, ethnicity, weekday/ weekend behaviors, structured/unstructured activities, and seasonal variability. A 9-month longitudinal design, across one school year, with assessments every 3 months. Elementary schools in the Vancouver and Richmond districts of British Columbia, Canada. Subjects. Subjects (N = 344; 47% female) were 9- to 11-year-old children who participated in a school-based PA initiative from September 2003 to June 2004. Not applicable. Assessments of PA were measured using the Physical Activity Questionnaire for Children. TV viewing time and structured PA were measured using a self-report questionnaire. Basic descriptives, Pearson r bivariate correlations and moderated multiple regressions with mean centered variables. No significant interaction effects were found for any of the proposed moderators. Null bivariate correlations are supportive of findings in previous literature. Our results did not find support for PA-TV viewing relations, regardless of gender, ethnicity, structured PA, and seasonal variability. PA interventions aimed at modifying sedentary behaviors, such as TV viewing, may not be warranted.

Investigating the relationship between costs and outcomes for English mental health providers: a bi-variate multi-level regression analysis.

PubMed

Moran, Valerie; Jacobs, Rowena

2018-06-01

Provider payment systems for mental health care that incentivize cost control and quality improvement have been a policy focus in a number of countries. In England, a new prospective provider payment system is being introduced to mental health that should encourage providers to control costs and improve outcomes. The aim of this research is to investigate the relationship between costs and outcomes to ascertain whether there is a trade-off between controlling costs and improving outcomes. The main data source is the Mental Health Minimum Data Set (MHMDS) for the years 2011/12 and 2012/13. Costs are calculated using NHS reference cost data while outcomes are measured using the Health of the Nation Outcome Scales (HoNOS). We estimate a bivariate multi-level model with costs and outcomes simultaneously. We calculate the correlation and plot the pairwise relationship between residual costs and outcomes at the provider level. After controlling for a range of demographic, need, social, and treatment variables, residual variation in costs and outcomes remains at the provider level. The correlation between residual costs and outcomes is negative, but very small, suggesting that cost-containment efforts by providers should not undermine outcome-improving efforts under the new payment system.

QSPR modeling of octanol/water partition coefficient of antineoplastic agents by balance of correlations.

PubMed

Toropov, Andrey A; Toropova, Alla P; Raska, Ivan; Benfenati, Emilio

2010-04-01

Three different splits into the subtraining set (n = 22), the set of calibration (n = 21), and the test set (n = 12) of 55 antineoplastic agents have been examined. By the correlation balance of SMILES-based optimal descriptors quite satisfactory models for the octanol/water partition coefficient have been obtained on all three splits. The correlation balance is the optimization of a one-variable model with a target function that provides both the maximal values of the correlation coefficient for the subtraining and calibration set and the minimum of the difference between the above-mentioned correlation coefficients. Thus, the calibration set is a preliminary test set. Copyright (c) 2009 Elsevier Masson SAS. All rights reserved.

The Robustness of Designs for Trials with Nested Data against Incorrect Initial Intracluster Correlation Coefficient Estimates

ERIC Educational Resources Information Center

Korendijk, Elly J. H.; Moerbeek, Mirjam; Maas, Cora J. M.

2010-01-01

In the case of trials with nested data, the optimal allocation of units depends on the budget, the costs, and the intracluster correlation coefficient. In general, the intracluster correlation coefficient is unknown in advance and an initial guess has to be made based on published values or subject matter knowledge. This initial estimate is likely…

An Affine Invariant Bivariate Version of the Sign Test.

DTIC Science & Technology

1987-06-01

words: affine invariance, bivariate quantile, bivariate symmetry, model,. generalized median, influence function , permutation test, normal efficiency...calculate a bivariate version of the influence function , and the resulting form is bounded, as is the case for the univartate sign test, and shows the...terms of a blvariate analogue of IHmpel’s (1974) influence function . The latter, though usually defined as a von-Mises derivative of certain

Dynamics analysis of SIR epidemic model with correlation coefficients and clustering coefficient in networks.

PubMed

Zhang, Juping; Yang, Chan; Jin, Zhen; Li, Jia

2018-07-14

In this paper, the correlation coefficients between nodes in states are used as dynamic variables, and we construct SIR epidemic dynamic models with correlation coefficients by using the pair approximation method in static networks and dynamic networks, respectively. Considering the clustering coefficient of the network, we analytically investigate the existence and the local asymptotic stability of each equilibrium of these models and derive threshold values for the prevalence of diseases. Additionally, we obtain two equivalent epidemic thresholds in dynamic networks, which are compared with the results of the mean field equations. Copyright © 2018 Elsevier Ltd. All rights reserved.

A novel coefficient for detecting and quantifying asymmetry of California electricity market based on asymmetric detrended cross-correlation analysis

NASA Astrophysics Data System (ADS)

Wang, Fang

2016-06-01

In order to detect and quantify asymmetry of two time series, a novel cross-correlation coefficient is proposed based on recent asymmetric detrended cross-correlation analysis (A-DXA), which we called A-DXA coefficient. The A-DXA coefficient, as an important extension of DXA coefficient ρ D X A , contains two directional asymmetric cross-correlated indexes, describing upwards and downwards asymmetric cross-correlations, respectively. By using the information of directional covariance function of two time series and directional variance function of each series itself instead of power-law between the covariance function and time scale, the proposed A-DXA coefficient can well detect asymmetry between the two series no matter whether the cross-correlation is significant or not. By means of the proposed A-DXA coefficient conducted over the asymmetry for California electricity market, we found that the asymmetry between the prices and loads is not significant for daily average data in 1999 yr market (before electricity crisis) but extremely significant for those in 2000 yr market (during the crisis). To further uncover the difference of asymmetry between the years 1999 and 2000, a modified H statistic (MH) and ΔMH statistic are proposed. One of the present contributions is that the high MH values calculated for hourly data exist in majority months in 2000 market. Another important conclusion is that the cross-correlation with downwards dominates over the whole 1999 yr in contrast to the cross-correlation with upwards dominates over the 2000 yr.

Evaluation of the Correlation Coefficient of Polyethylene Glycol Treated and Direct Prolactin Results and Comparability with Different Assay System Results.

PubMed

Pal, Shyamali

2017-12-01

The presence of Macro prolactin is a significant cause of elevated prolactin resulting in misdiagnosis in all automated systems. Poly ethylene glycol (PEG) pretreatment is the preventive process but such process includes the probability of loss of a fraction of bioactive prolactin. Surprisingly, PEG treated EQAS & IQAS samples in Cobas e 411 are found out to be correlating with direct results of at least 3 immunoassay systems and treated and untreated Cobas e 411 results are comparable by a correlation coefficient. Comparison of EQAS, IQAS and patient samples were done to find out the trueness of such correlation factor. Study with patient's results have established the correlation coefficient is valid for very small concentration of prolactin also. EQAS, IQAS and 150 patient samples were treated with PEG and prolactin results of treated and untreated samples obtained from Roche Cobas e 411. 25 patient's results (treated) were compared with direct results in Advia Centaur, Architect I & Access2 systems. Correlation coefficient was obtained from trend line of the treated and untreated results. Two tailed p-value obtained from regression coefficient(r) and sample size. The correlation coefficient is in the range (0.761-0.771). Reverse correlation range is (1.289-1.301). r value of two sets of calculated results were 0.995. Two tailed p- value is zero approving dismissal of null hypothesis. The z-score of EQAS does not always assure authenticity of resultsPEG precipitation is correlated by the factor 0.761 even in very small concentrationsAbbreviationsGFCgel filtration chromatographyPEGpolyethylene glycolEQASexternal quality assurance systemM-PRLmacro prolactinPRLprolactinECLIAelectro-chemiluminescence immunoassayCLIAclinical laboratory improvement amendmentsIQASinternal quality assurance systemrregression coefficient.

Statistical Association Criteria in Forensic Psychiatry–A criminological evaluation of casuistry

PubMed Central

Gheorghiu, V; Buda, O; Popescu, I; Trandafir, MS

2011-01-01

Purpose. Identification of potential shared primary psychoprophylaxis and crime prevention is measured by analyzing the rate of commitments for patients–subjects to forensic examination. Material and method. The statistic trial is a retrospective, document–based study. The statistical lot consists of 770 initial examination reports performed and completed during the whole year 2007, primarily analyzed in order to summarize the data within the National Institute of Forensic Medicine, Bucharest, Romania (INML), with one of the group variables being ‘particularities of the psychiatric patient history’, containing the items ‘forensic onset’, ‘commitments within the last year prior to the examination’ and ‘absence of commitments within the last year prior to the examination’. The method used was the Kendall bivariate correlation. For this study, the authors separately analyze only the two items regarding commitments by other correlation alternatives and by modern, elaborate statistical analyses, i.e. recording of the standard case study variables, Kendall bivariate correlation, cross tabulation, factor analysis and hierarchical cluster analysis. Results. The results are varied, from theoretically presumed clinical nosography (such as schizophrenia or manic depression), to non–presumed (conduct disorders) or unexpected behavioral acts, and therefore difficult to interpret. Conclusions. One took into consideration the features of the batch as well as the results of the previous standard correlation of the whole statistical lot. The authors emphasize the role of medical security measures that are actually applied in the therapeutic management in general and in risk and second offence management in particular, as well as the role of forensic psychiatric examinations in the detection of certain aspects related to the monitoring of mental patients. PMID:21505571

Anthropometry of Women of the U.S. Army--1977. Report Number 4. Correlation Coefficients

DTIC Science & Technology

1980-02-01

S.... •, 0 76 x:. ADo5 //64 ! TECHNICAL REPORT NATICK/TR-80/016 (/ II ANTHROPOMETRY OF WOMEN OF THE U.S. ARMY-1977 Report No. 4 Correlation...NUMBER NATICK/TR-80/016 4. TITLE (and Subtitle) 5. TYPE OF REPORT & PERIOD COVERED ANTHROPOMETRY OF WOMEN OF THE U.S. ARMY--1977 Technical Report REPORT NO... Anthropometry Survey(s) Coefficients of correlation Measurement(s) U.S. Army Correlation coefficients Body size Military personnel Equation(s) Sizes

Perceived treatment effectiveness, medication compliance, and complementary and alternative medicine use among veterans with bipolar disorder.

PubMed

Jarman, Christopher N; Perron, Brian E; Kilbourne, Amy M; Teh, Carrie Farmer

2010-03-01

Recent research shows a high rate of complementary and alternative medicine (CAM) use among persons with mental disorders, although correlates and patterns of CAM use are relatively unknown. This study tested whether CAM use is associated with perceived effectiveness of conventional treatment (i.e., psychotropic medication and psychotherapy) and medication compliance among persons with bipolar disorder. Patients with bipolar disorder (n = 435) were included as part of a naturalistic cohort study. Measures of CAM utilization, medication compliance, and perceptions of the effectiveness of psychotropic medications and psychotherapy were based on previously established questionnaires. Associations were tested using bivariate and multivariate analyses. Bivariate analyses showed that patients who did not perceive psychotherapy as effective at improving social, family, or job functioning reported greater CAM use. However, medication compliance was not significantly associated with use of CAM. Patients who used oral (e.g., herbal therapies) or cognitive (e.g., meditation) CAM were more likely to report that their medications were not effective at relieving manic or depressive symptoms. Users of cognitive CAM were more likely to report that their medications did not help with social, job, or family functioning, and that they did not prevent recurrences of manic or depressive episodes. None of the bivariate associations remained significant in multivariate analyses. Prior research has suggested that persons who are dissatisfied with treatment for medical conditions are more likely to use CAM therapies. However, the results of this study do not show CAM therapies to be associated with perceived effectiveness of treatments for mental health problems among this sample of persons with serious mental illnesses. This suggests that motivations for CAM use may vary by population and condition. Because few correlates of CAM use among persons with serious mental illnesses are known, providers should conduct routine assessments of CAM use.

DCCA cross-correlation coefficients reveals the change of both synchronization and oscillation in EEG of Alzheimer disease patients

NASA Astrophysics Data System (ADS)

Chen, Yingyuan; Cai, Lihui; Wang, Ruofan; Song, Zhenxi; Deng, Bin; Wang, Jiang; Yu, Haitao

2018-01-01

Alzheimer's disease (AD) is a degenerative disorder of neural system that affects mainly the older population. Recently, many researches show that the EEG of AD patients can be characterized by EEG slowing, enhanced complexity of the EEG signals, and EEG synchrony. In order to examine the neural synchrony at multi scales, and to find a biomarker that help detecting AD in diagnosis, detrended cross-correlation analysis (DCCA) of EEG signals is applied in this paper. Several parameters, namely DCCA coefficients in the whole brain, DCCA coefficients at a specific scale, maximum DCCA coefficient over the span of all time scales and the corresponding scale of such coefficients, were extracted to examine the synchronization, respectively. The results show that DCCA coefficients have a trend of increase as scale increases, and decreases as electrode distance increases. Comparing DCCA coefficients in AD patients with healthy controls, a decrease of synchronization in the whole brain, and a bigger scale corresponding to maximum correlation is discovered in AD patients. The change of max-correlation scale may relate to the slowing of oscillatory activities. Linear combination of max DCCA coefficient and max-correlation scale reaches a classification accuracy of 90%. From the above results, it is reasonable to conclude that DCCA coefficient reveals the change of both oscillation and synchrony in AD, and thus is a powerful tool to differentiate AD patients from healthy elderly individuals.

No association between gender inequality and peak HIV prevalence in developing countries - an ecological study.

PubMed

Kenyon, Chris R; Buyze, Jozefien

2015-01-01

The prevalence of both gender inequality and HIV prevalence vary considerably both within all developing countries and within those in sub-Saharan Africa. We test the hypothesis that the extent of gender inequality is associated with national peak HIV prevalence. Linear regression was used to test the association between national peak HIV prevalence and three markers of gender equality - the gender-related development index (GDI), the gender empowerment measure (GEM), and the gender inequality index (GII). No evidence was found of a positive relationship between gender inequality and HIV prevalence, either in the analyses of all developing countries or those limited to Africa. In the bivariate analyses limited to Africa, there was a positive association between the two measures of gender "equality" and peak HIV prevalence (GDI: coefficient 28, 95% confidence interval (CI) 9.1-46.8; GEM: coefficient 54.8, 95% CI 20.5-89.1). There was also a negative association between the marker of gender "inequality" and peak HIV prevalence (GII: coefficient -66.9, 95% CI -112.8 to -21.0). These associations all disappeared on multivariate analyses. We could not find any evidence to support the hypothesis that variations in the extent of gender inequality explain variations in HIV prevalence in developing countries.

Statistics corner: A guide to appropriate use of correlation coefficient in medical research.

PubMed

Mukaka, M M

2012-09-01

Correlation is a statistical method used to assess a possible linear association between two continuous variables. It is simple both to calculate and to interpret. However, misuse of correlation is so common among researchers that some statisticians have wished that the method had never been devised at all. The aim of this article is to provide a guide to appropriate use of correlation in medical research and to highlight some misuse. Examples of the applications of the correlation coefficient have been provided using data from statistical simulations as well as real data. Rule of thumb for interpreting size of a correlation coefficient has been provided.

[Correlation of molecular weight and nanofiltration mass transfer coefficient of phenolic acid composition from Salvia miltiorrhiza].

PubMed

Li, Cun-Yu; Wu, Xin; Gu, Jia-Mei; Li, Hong-Yang; Peng, Guo-Ping

2018-04-01

Based on the molecular sieving and solution-diffusion effect in nanofiltration separation, the correlation between initial concentration and mass transfer coefficient of three typical phenolic acids from Salvia miltiorrhiza was fitted to analyze the relationship among mass transfer coefficient, molecular weight and concentration. The experiment showed a linear relationship between operation pressure and membrane flux. Meanwhile, the membrane flux was gradually decayed with the increase of solute concentration. On the basis of the molecular sieving and solution-diffusion effect, the mass transfer coefficient and initial concentration of three phenolic acids showed a power function relationship, and the regression coefficients were all greater than 0.9. The mass transfer coefficient and molecular weight of three phenolic acids were negatively correlated with each other, and the order from high to low is protocatechualdehyde >rosmarinic acid> salvianolic acid B. The separation mechanism of nanofiltration for phenolic acids was further clarified through the analysis of the correlation of molecular weight and nanofiltration mass transfer coefficient. The findings provide references for nanofiltration separation, especially for traditional Chinese medicine with phenolic acids. Copyright© by the Chinese Pharmaceutical Association.

Biostatistics Series Module 6: Correlation and Linear Regression.

PubMed

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient ( r ). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P < 0.05. A 95% confidence interval of the correlation coefficient can also be calculated for an idea of the correlation in the population. The value r 2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation ( y = a + bx ), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous.

Biostatistics Series Module 6: Correlation and Linear Regression

PubMed Central

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient (r). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P < 0.05. A 95% confidence interval of the correlation coefficient can also be calculated for an idea of the correlation in the population. The value r2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation (y = a + bx), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous. PMID:27904175

A comparison of confidence interval methods for the intraclass correlation coefficient in community-based cluster randomization trials with a binary outcome.

PubMed

Braschel, Melissa C; Svec, Ivana; Darlington, Gerarda A; Donner, Allan

2016-04-01

Many investigators rely on previously published point estimates of the intraclass correlation coefficient rather than on their associated confidence intervals to determine the required size of a newly planned cluster randomized trial. Although confidence interval methods for the intraclass correlation coefficient that can be applied to community-based trials have been developed for a continuous outcome variable, fewer methods exist for a binary outcome variable. The aim of this study is to evaluate confidence interval methods for the intraclass correlation coefficient applied to binary outcomes in community intervention trials enrolling a small number of large clusters. Existing methods for confidence interval construction are examined and compared to a new ad hoc approach based on dividing clusters into a large number of smaller sub-clusters and subsequently applying existing methods to the resulting data. Monte Carlo simulation is used to assess the width and coverage of confidence intervals for the intraclass correlation coefficient based on Smith's large sample approximation of the standard error of the one-way analysis of variance estimator, an inverted modified Wald test for the Fleiss-Cuzick estimator, and intervals constructed using a bootstrap-t applied to a variance-stabilizing transformation of the intraclass correlation coefficient estimate. In addition, a new approach is applied in which clusters are randomly divided into a large number of smaller sub-clusters with the same methods applied to these data (with the exception of the bootstrap-t interval, which assumes large cluster sizes). These methods are also applied to a cluster randomized trial on adolescent tobacco use for illustration. When applied to a binary outcome variable in a small number of large clusters, existing confidence interval methods for the intraclass correlation coefficient provide poor coverage. However, confidence intervals constructed using the new approach combined with Smith's method provide nominal or close to nominal coverage when the intraclass correlation coefficient is small (<0.05), as is the case in most community intervention trials. This study concludes that when a binary outcome variable is measured in a small number of large clusters, confidence intervals for the intraclass correlation coefficient may be constructed by dividing existing clusters into sub-clusters (e.g. groups of 5) and using Smith's method. The resulting confidence intervals provide nominal or close to nominal coverage across a wide range of parameters when the intraclass correlation coefficient is small (<0.05). Application of this method should provide investigators with a better understanding of the uncertainty associated with a point estimator of the intraclass correlation coefficient used for determining the sample size needed for a newly designed community-based trial. © The Author(s) 2015.

Snapping Sharks, Maddening Mindreaders, and Interactive Images: Teaching Correlation.

ERIC Educational Resources Information Center

Mitchell, Mark L.

Understanding correlation coefficients is difficult for students. A free computer program that helps introductory psychology students distinguish between positive and negative correlation, and which also teaches them to understand the differences between correlation coefficients of different size is described in this paper. The program is…

40 CFR 53.34 - Test procedure for methods for PM10 and Class I methods for PM2.5.

Code of Federal Regulations, 2011 CFR

2011-07-01

... linear regression parameters (slope, intercept, and correlation coefficient) describing the relationship... correlation coefficient. (2) To pass the test for comparability, the slope, intercept, and correlation...

[Prediction of soil adsorption coefficients of organic compounds in a wide range of soil types by soil column liquid chromatography].

PubMed

Guo, Rongbo; Chen, Jiping; Zhang, Qing; Wu, Wenzhong; Liang, Xinmiao

2004-01-01

Using the methanol-water mixtures as mobile phases of soil column liquid chromatography (SCLC), prediction of soil adsorption coefficients (K(d)) by SCLC was validated in a wide range of soil types. The correlations between the retention factors measured by SCLC and soil adsorption coefficients measured by batch experiments were studied for five soils with different properties, i.e., Eurosoil 1#, 2#, 3#, 4# and 5#. The results show that good correlations existed between the retention factors and soil adsorption coefficients for Eurosoil 1#, 2#, 3# and 4#. For Eurosoil 5# which has a pH value of near 3, the correlation between retention factors and soil adsorption coefficients was unsatisfactory using methanol-water as mobile phase of SCLC. However, a good correlation was obtained using a methanol-buffer mixture with pH 3 as the mobile phase. This study proved that the SCLC is suitable for the prediction of soil adsorption coefficients.

eHealth literacy in chronic disease patients: An item response theory analysis of the eHealth literacy scale (eHEALS).

PubMed

Paige, Samantha R; Krieger, Janice L; Stellefson, Michael; Alber, Julia M

2017-02-01

Chronic disease patients are affected by low computer and health literacy, which negatively affects their ability to benefit from access to online health information. To estimate reliability and confirm model specifications for eHealth Literacy Scale (eHEALS) scores among chronic disease patients using Classical Test (CTT) and Item Response Theory techniques. A stratified sample of Black/African American (N=341) and Caucasian (N=343) adults with chronic disease completed an online survey including the eHEALS. Item discrimination was explored using bi-variate correlations and Cronbach's alpha for internal consistency. A categorical confirmatory factor analysis tested a one-factor structure of eHEALS scores. Item characteristic curves, in-fit/outfit statistics, omega coefficient, and item reliability and separation estimates were computed. A 1-factor structure of eHEALS was confirmed by statistically significant standardized item loadings, acceptable model fit indices (CFI/TLI>0.90), and 70% variance explained by the model. Item response categories increased with higher theta levels, and there was evidence of acceptable reliability (ω=0.94; item reliability=89; item separation=8.54). eHEALS scores are a valid and reliable measure of self-reported eHealth literacy among Internet-using chronic disease patients. Providers can use eHEALS to help identify patients' eHealth literacy skills. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Interobserver Variability in Histologic Evaluation of Liver Fibrosis Using Categorical and Quantitative Scores.

PubMed

Pavlides, Michael; Birks, Jacqueline; Fryer, Eve; Delaney, David; Sarania, Nikita; Banerjee, Rajarshi; Neubauer, Stefan; Barnes, Eleanor; Fleming, Kenneth A; Wang, Lai Mun

2017-04-01

The aim of the study was to investigate the interobserver agreement for categorical and quantitative scores of liver fibrosis. Sixty-five consecutive biopsy specimens from patients with mixed liver disease etiologies were assessed by three pathologists using the Ishak and nonalcoholic steatohepatitis Clinical Research Network (NASH CRN) scoring systems, and the fibrosis area (collagen proportionate area [CPA]) was estimated by visual inspection (visual-CPA). A subset of 20 biopsy specimens was analyzed using digital imaging analysis (DIA) for the measurement of CPA (DIA-CPA). The bivariate weighted κ between any two pathologists ranged from 0.57 to 0.67 for Ishak staging and from 0.47 to 0.57 for the NASH CRN staging. Bland-Altman analysis showed poor agreement between all possible pathologist pairings for visual-CPA but good agreement between all pathologist pairings for DIA-CPA. There was good agreement between the two pathologists who assessed biopsy specimens by visual-CPA and DIA-CPA. The intraclass correlation coefficient, which is equivalent to the κ statistic for continuous variables, was 0.78 for visual-CPA and 0.97 for DIA-CPA. These results suggest that DIA-CPA is the most robust method for assessing liver fibrosis followed by visual-CPA. Categorical scores perform less well than both the quantitative CPA scores assessed here. © American Society for Clinical Pathology, 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

The Development and Psychometric Properties of the Immigration Law Concerns Scale (ILCS) for HIV Testing.

PubMed

Lechuga, Julia; Galletly, Carol L; Broaddus, Michelle R; Dickson-Gomez, Julia B; Glasman, Laura R; McAuliffe, Timothy L; Vega, Miriam Y; LeGrand, Sarah; Mena, Carla A; Barlow, Morgan L; Valera, Erik; Montenegro, Judith I

2017-11-08

To develop, pilot test, and conduct psychometric analyses of an innovative scale measuring the influence of perceived immigration laws on Latino migrants' HIV-testing behavior. The Immigration Law Concerns Scale (ILCS) was developed in three phases: Phase 1 involved a review of law and literature, generation of scale items, consultation with project advisors, and subsequent revision of the scale. Phase 2 involved systematic translation- back translation and consensus-based editorial processes conducted by members of a bilingual and multi-national study team. In Phase 3, 339 sexually active, HIV-negative Spanish-speaking, non-citizen Latino migrant adults (both documented and undocumented) completed the scale via audio computer-assisted self-interview. The psychometric properties of the scale were tested with exploratory factor analysis and estimates of reliability coefficients were generated. Bivariate correlations were conducted to test the discriminant and predictive validity of identified factors. Exploratory factor analysis revealed a three-factor, 17-item scale. subscale reliability ranged from 0.72 to 0.79. There were significant associations between the ILCS and the HIV-testing behaviors of participants. Results of the pilot test and psychometric analysis of the ILCS are promising. The scale is reliable and significantly associated with the HIV-testing behaviors of participants. Subscales related to unwanted government attention and concerns about meeting moral character requirements should be refined.

Temporal correlation coefficient for directed networks.

PubMed

Büttner, Kathrin; Salau, Jennifer; Krieter, Joachim

2016-01-01

Previous studies dealing with network theory focused mainly on the static aggregation of edges over specific time window lengths. Thus, most of the dynamic information gets lost. To assess the quality of such a static aggregation the temporal correlation coefficient can be calculated. It measures the overall possibility for an edge to persist between two consecutive snapshots. Up to now, this measure is only defined for undirected networks. Therefore, we introduce the adaption of the temporal correlation coefficient to directed networks. This new methodology enables the distinction between ingoing and outgoing edges. Besides a small example network presenting the single calculation steps, we also calculated the proposed measurements for a real pig trade network to emphasize the importance of considering the edge direction. The farm types at the beginning of the pork supply chain showed clearly higher values for the outgoing temporal correlation coefficient compared to the farm types at the end of the pork supply chain. These farm types showed higher values for the ingoing temporal correlation coefficient. The temporal correlation coefficient is a valuable tool to understand the structural dynamics of these systems, as it assesses the consistency of the edge configuration. The adaption of this measure for directed networks may help to preserve meaningful additional information about the investigated network that might get lost if the edge directions are ignored.

Correlation characteristics of phase and amplitude chimeras in an ensemble of nonlocally coupled maps

NASA Astrophysics Data System (ADS)

Vadivasova, T. E.; Strelkova, G. I.; Bogomolov, S. A.; Anishchenko, V. S.

2017-01-01

Correlation characteristics of chimera states have been calculated using the coefficient of mutual correlation of elements in a closed-ring ensemble of nonlocally coupled chaotic maps. Quantitative differences between the coefficients of mutual correlation for phase and amplitude chimeras are established for the first time.

Reliability Implications in Wood Systems of a Bivariate Gaussian-Weibull Distribution and the Associated Univariate Pseudo-truncated Weibull

Treesearch

Steve P. Verrill; James W. Evans; David E. Kretschmann; Cherilyn A. Hatfield

2014-01-01

Two important wood properties are the modulus of elasticity (MOE) and the modulus of rupture (MOR). In the past, the statistical distribution of the MOE has often been modeled as Gaussian, and that of the MOR as lognormal or as a two- or three-parameter Weibull distribution. It is well known that MOE and MOR are positively correlated. To model the simultaneous behavior...

Small Sample Properties of Asymptotically Efficient Estimators of the Parameters of a Bivariate Gaussian–Weibull Distribution

Treesearch

Steve P. Verrill; James W. Evans; David E. Kretschmann; Cherilyn A. Hatfield

2012-01-01

Two important wood properties are stiffness (modulus of elasticity or MOE) and bending strength (modulus of rupture or MOR). In the past, MOE has often been modeled as a Gaussian and MOR as a lognormal or a two or three parameter Weibull. It is well known that MOE and MOR are positively correlated. To model the simultaneous behavior of MOE and MOR for the purposes of...

Maximum likelihood estimation of the parameters of a bivariate Gaussian-Weibull distribution from machine stress-rated data

Treesearch

Steve P. Verrill; David E. Kretschmann; James W. Evans

2016-01-01

Two important wood properties are stiffness (modulus of elasticity, MOE) and bending strength (modulus of rupture, MOR). In the past, MOE has often been modeled as a Gaussian and MOR as a lognormal or a two- or threeparameter Weibull. It is well known that MOE and MOR are positively correlated. To model the simultaneous behavior of MOE and MOR for the purposes of wood...

Assessing characteristics related to the use of seatbelts and cell phones by drivers: application of a bivariate probit model.

PubMed

Russo, Brendan J; Kay, Jonathan J; Savolainen, Peter T; Gates, Timothy J

2014-06-01

The effects of cell phone use and safety belt use have been an important focus of research related to driver safety. Cell phone use has been shown to be a significant source of driver distraction contributing to substantial degradations in driver performance, while safety belts have been demonstrated to play a vital role in mitigating injuries to crash-involved occupants. This study examines the prevalence of cell phone use and safety belt non-use among the driving population through direct observation surveys. A bivariate probit model is developed to simultaneously examine the factors that affect cell phone and safety belt use among motor vehicle drivers. The results show that several factors may influence drivers' decision to use cell phones and safety belts, and that these decisions are correlated. Understanding the factors that affect both cell phone use and safety belt non-use is essential to targeting policy and programs that reduce such behavior. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Local Agreement Pattern Measure Based on Hazard Functions for Survival Outcomes

PubMed Central

Dai, Tian; Guo, Ying; Peng, Limin; Manatunga, Amita K.

2017-01-01

Summary Assessing agreement is often of interest in biomedical and clinical research when measurements are obtained on the same subjects by different raters or methods. Most classical agreement methods have been focused on global summary statistics, which cannot be used to describe various local agreement patterns. The objective of this work is to study the local agreement pattern between two continuous measurements subject to censoring. In this paper, we propose a new agreement measure based on bivariate hazard functions to characterize the local agreement pattern between two correlated survival outcomes. The proposed measure naturally accommodates censored observations, fully captures the dependence structure between bivariate survival times and provides detailed information on how the strength of agreement evolves over time. We develop a nonparametric estimation method for the proposed local agreement pattern measure and study theoretical properties including strong consistency and asymptotical normality. We then evaluate the performance of the estimator through simulation studies and illustrate the method using a prostate cancer data example. PMID:28724196

A local agreement pattern measure based on hazard functions for survival outcomes.

PubMed

Dai, Tian; Guo, Ying; Peng, Limin; Manatunga, Amita K

2018-03-01

Assessing agreement is often of interest in biomedical and clinical research when measurements are obtained on the same subjects by different raters or methods. Most classical agreement methods have been focused on global summary statistics, which cannot be used to describe various local agreement patterns. The objective of this work is to study the local agreement pattern between two continuous measurements subject to censoring. In this article, we propose a new agreement measure based on bivariate hazard functions to characterize the local agreement pattern between two correlated survival outcomes. The proposed measure naturally accommodates censored observations, fully captures the dependence structure between bivariate survival times and provides detailed information on how the strength of agreement evolves over time. We develop a nonparametric estimation method for the proposed local agreement pattern measure and study theoretical properties including strong consistency and asymptotical normality. We then evaluate the performance of the estimator through simulation studies and illustrate the method using a prostate cancer data example. © 2017, The International Biometric Society.

On the joint spectral density of bivariate random sequences. Thesis Technical Report No. 21

NASA Technical Reports Server (NTRS)

Aalfs, David D.

1995-01-01

For univariate random sequences, the power spectral density acts like a probability density function of the frequencies present in the sequence. This dissertation extends that concept to bivariate random sequences. For this purpose, a function called the joint spectral density is defined that represents a joint probability weighing of the frequency content of pairs of random sequences. Given a pair of random sequences, the joint spectral density is not uniquely determined in the absence of any constraints. Two approaches to constraining the sequences are suggested: (1) assume the sequences are the margins of some stationary random field, (2) assume the sequences conform to a particular model that is linked to the joint spectral density. For both approaches, the properties of the resulting sequences are investigated in some detail, and simulation is used to corroborate theoretical results. It is concluded that under either of these two constraints, the joint spectral density can be computed from the non-stationary cross-correlation.

Molecular genetic analysis of the F11 gene in 14 Turkish patients with factor XI deficiency: identification of novel and recurrent mutations and their inheritance within families.

PubMed

Colakoglu, Seyma; Bayhan, Turan; Tavil, Betül; Keskin, Ebru Yılmaz; Cakir, Volkan; Gümrük, Fatma; Çetin, Mualla; Aytaç, Selin; Berber, Ergul

2018-01-01

Factor XI (FXI) deficiency is an autosomal bleeding disease associated with genetic defects in the F11 gene which cause decreased FXI levels or impaired FXI function. An increasing number of mutations has been reported in the FXI mutation database, most of which affect the serine protease domain of the protein. FXI is a heterogeneous disorder associated with a variable bleeding tendency and a variety of causative F11 gene mutations. The molecular basis of FXI deficiency in 14 patients from ten unrelated families in Turkey was analysed to establish genotype-phenotype correlations and inheritance of the mutations in the patients' families. Fourteen index cases with a diagnosis of FXI deficiency and family members of these patients were enrolled into the study. The patients' F11 genes were amplified by polymerase chain reaction and subjected to direct DNA sequencing analysis. The findings were analysed statistically using bivariate correlations, Pearson's correlation coefficient and the nonparametric Mann-Whitney test. Direct DNA sequencing analysis of the F11 genes revealed that all of the 14 patients had a F11 gene mutation. Eight different mutations were identified in the apple 1, apple 2 or serine protease domains, except one which was a splice site mutation. Six of the mutations were recurrent. Two of the mutations were novel missense mutations, p.Val522Gly and p.Cys581Arg, within the catalytic domain. The p.Trp519Stop mutation was observed in two families whereas all the other mutations were specific to a single family. Identification of mutations confirmed the genetic heterogeneity of FXI deficiency. Most of the patients with mutations did not have any bleeding complications, whereas some had severe bleeding symptoms. Genetic screening for F11 gene mutations is important to decrease the mortality and morbidity rate associated with FXI deficiency, which can be life-threatening if bleeding occurs in tissues with high fibrinolytic activity.

Incidence of Temperature Inversion and their Impact on Air Quality: A Case Study of Delhi

NASA Astrophysics Data System (ADS)

Singh, V. P.

2016-12-01

In troposphere, an increase in temperature with the altitude produces stable atmosphere which prohibits the air pollutants dispersion. This study investigates the phenomenon of temperature inversion (TI), Lapse rate (LR) and its effects on air quality in respect of Ozone (O3), CO2, CO & PM2.5 over a megacity- Delhi (Study Time Period: 2006-2012). Because of huge population, urban sprawl and orographic location, this study can be very helpful for Delhi and cities like Delhi. Radiosonde observations for temperature was used for TI calculations over the region. Results indicate that TI generally occurs at 975-850 hPa. Also, the maximum number of inversions occur during winter months (December and January) especially at night time and early mornings. Furthermore, during winter months, the incidence of inversion is highest at both 00UTC and 12UTC while it is least during the monsoon months (July and August) at 00UTC. The LR is maximum in terms of magnitude (i.e. highly negative) during the summer months (May & June) every year indicating the strong heating effects that takes place during the day time in summer and also because the sensible heat flux from the surface to the atmosphere is significant even at 12UTC (i.e. around 5.30 P.M.) The bivariate correlation analysis for air quality variables reveals negative relationship of all air quality variables except O3 with rainfall. A positive relationship of LR with all air quality variables, except O3, was observed indicating the increase in pollutants' concentrations with an increase in LR. The correlation coefficient between LR and air pollutants CO, NO, NO2, PM2.5 were found to be 0.463, 0.346, 0.249 and 0.673 respectively. A negative correlation was found between wind speed and most of the air pollutants. Also, significantly, O3 had been the only air pollutant having a negative relationship with LR (both at 00UTC &12UTC).

Length of residence, age and patterns of medicinal plant knowledge and use among women in the urban Amazon

PubMed Central

2014-01-01

Background This paper explores patterns of women’s medicinal plant knowledge and use in an urban area of the Brazilian Amazon. Specifically, this paper examines the relationship between a woman’s age and her use and knowledge of medicinal plants. It also examines whether length of residence in three different areas of the Amazon is correlated with a woman’s use and knowledge of medicinal plants. Two of the areas where respondents may have resided, the jungle/seringal and farms/colonias, are classified as rural. The third area (which all of the respondents resided in) was urban. Methods This paper utilizes survey data collected in Rio Branco, Brazil. Researchers administered the survey to 153 households in the community of Bairro da Luz (a pseudonym). The survey collected data on phytotherapeutic knowledge, general phytotherapeutic practice, recent phytotherapeutic practice and demographic information on age and length of residence in the seringal, on a colonia, and in a city. Bivariate correlation coefficients were calculated to assess the inter-relationships among the key variables. Three dependent variables, two measuring general phytotherapeutic practice and one measuring phytotherapeutic knowledge were regressed on the demographic factors. Results The results demonstrate a relationship between a woman’s age and medicinal plant use, but not between age and plant knowledge. Additionally, length of residence in an urban area and on a colonia/farm are not related to medicinal plant knowledge or use. However, length of residence in the seringal/jungle is positively correlated with both medicinal plant knowledge and use. Conclusions The results reveal a vibrant tradition of medicinal plant use in Bairro da Luz. They also indicate that when it comes to place of residence and phytotherapy the meaningful distinction is not rural versus urban, it is seringal versus other locations. Finally, the results suggest that phytotherapeutic knowledge and use should be measured separately since one may not be an accurate proxy for the other. PMID:24565037

Comparison of RNFL thickness and RPE-normalized RNFL attenuation coefficient for glaucoma diagnosis

NASA Astrophysics Data System (ADS)

Vermeer, K. A.; van der Schoot, J.; Lemij, H. G.; de Boer, J. F.

2013-03-01

Recently, a method to determine the retinal nerve fiber layer (RNFL) attenuation coefficient, based on normalization on the retinal pigment epithelium, was introduced. In contrast to conventional RNFL thickness measures, this novel measure represents a scattering property of the RNFL tissue. In this paper, we compare the RNFL thickness and the RNFL attenuation coefficient on 10 normal and 8 glaucomatous eyes by analyzing the correlation coefficient and the receiver operator curves (ROCs). The thickness and attenuation coefficient showed moderate correlation (r=0.82). Smaller correlation coefficients were found within normal (r=0.55) and glaucomatous (r=0.48) eyes. The full separation between normal and glaucomatous eyes based on the RNFL attenuation coefficient yielded an area under the ROC (AROC) of 1.0. The AROC for the RNFL thickness was 0.9875. No statistically significant difference between the two measures was found by comparing the AROC. RNFL attenuation coefficients may thus replace current RNFL thickness measurements or be combined with it to improve glaucoma diagnosis.

[Use of bivariate survival curves for analyzing mortality of heart failure and sudden death in dilated cardiomiopathy].

PubMed

Gregori, Dario; Rosato, Rosalba; Zecchin, Massimo; Di Lenarda, Andrea

2005-01-01

This paper discusses the use of bivariate survival curves estimators within the competing risk framework. Competing risks models are used for the analysis of medical data with more than one cause of death. The case of dilated cardiomiopathy is explored. Bivariate survival curves plot the conjoint mortality processes. The different graphic representation of bivariate survival analysis is the major contribute of this methodology to the competing risks analysis.

Channel correlation of free space optical communication systems with receiver diversity in non-Kolmogorov atmospheric turbulence

NASA Astrophysics Data System (ADS)

Ma, Jing; Fu, Yulong; Tan, Liying; Yu, Siyuan; Xie, Xiaolong

2018-05-01

Spatial diversity as an effective technique to mitigate the turbulence fading has been widely utilized in free space optical (FSO) communication systems. The received signals, however, will suffer from channel correlation due to insufficient spacing between component antennas. In this paper, the new expressions of the channel correlation coefficient and specifically its components (the large- and small-scale channel correlation coefficients) for a plane wave with aperture effects are derived for horizontal link in moderate-to-strong turbulence, using a non-Kolmogorov spectrum that has a generalized power law in the range of 3-4 instead of the fixed classical Kolmogorov power law of 11/3. And then the influence of power law variations on the channel correlation coefficient and its components are analysed. The numerical results indicated that various value of the power law lead to varying effects on the channel correlation coefficient and its components. This work will help with the further investigation on the fading correlation in spatial diversity systems.

The etiology of mathematical and reading (dis)ability covariation in a sample of Dutch twins.

PubMed

Markowitz, Ezra M; Willemsen, Gonneke; Trumbetta, Susan L; van Beijsterveldt, Toos C E M; Boomsma, Dorret I

2005-12-01

The genetic etiology of mathematical and reading (dis)ability has been studied in a number of distinct samples, but the true nature of the relationship between the two remains unclear. Data from the Netherlands Twin Register was used to determine the etiology of the relationship between mathematical and reading (dis)ability in adolescent twins. Ratings of mathematical and reading problems were obtained from parents of over 1500 twin pairs. Results of bivariate structural equation modeling showed a genetic correlation around .60, which explained over 90% of the phenotypic correlation between mathematical and reading ability. The genetic model was the same for males and females.

The Physical Significance of the Synthetic Running Correlation Coefficient and Its Applications in Oceanic and Atmospheric Studies

NASA Astrophysics Data System (ADS)

Zhao, Jinping; Cao, Yong; Wang, Xin

2018-06-01

In order to study the temporal variations of correlations between two time series, a running correlation coefficient (RCC) could be used. An RCC is calculated for a given time window, and the window is then moved sequentially through time. The current calculation method for RCCs is based on the general definition of the Pearson product-moment correlation coefficient, calculated with the data within the time window, which we call the local running correlation coefficient (LRCC). The LRCC is calculated via the two anomalies corresponding to the two local means, meanwhile, the local means also vary. It is cleared up that the LRCC reflects only the correlation between the two anomalies within the time window but fails to exhibit the contributions of the two varying means. To address this problem, two unchanged means obtained from all available data are adopted to calculate an RCC, which is called the synthetic running correlation coefficient (SRCC). When the anomaly variations are dominant, the two RCCs are similar. However, when the variations of the means are dominant, the difference between the two RCCs becomes obvious. The SRCC reflects the correlations of both the anomaly variations and the variations of the means. Therefore, the SRCCs from different time points are intercomparable. A criterion for the superiority of the RCC algorithm is that the average value of the RCC should be close to the global correlation coefficient calculated using all data. The SRCC always meets this criterion, while the LRCC sometimes fails. Therefore, the SRCC is better than the LRCC for running correlations. We suggest using the SRCC to calculate the RCCs.

Area and volume ratios for prediction of visual outcome in idiopathic macular hole.

PubMed

Geng, Xing-Yun; Wu, Hui-Qun; Jiang, Jie-Hui; Jiang, Kui; Zhu, Jun; Xu, Yi; Dong, Jian-Cheng; Yan, Zhuang-Zhi

2017-01-01

To predict the visual outcome in patients undergoing macular hole surgery by two novel three-dimensional morphological parameters on optical coherence tomography (OCT): area ratio factor (ARF) and volume ratio factor (VRF). A clinical case series was conducted, including 54 eyes of 54 patients with an idiopathic macular hole (IMH). Each patient had an OCT examination before and after surgery. Morphological parameters of the macular hole, such as minimum diameter, base diameter, and height were measured. Then, the macular hole index (MHI), tractional hole index (THI), and hole form factor (HFF) were calculated. Meanwhile, novel postoperative macular hole (MH) factors, ARF and VRF were calculated by three-dimensional morphology. Bivariate correlations were performed to acquire asymptotic significance values between the steady best corrected visual acuity (BCVA) after surgery and 2D/3D arguments of MH by the Pearson method with two-tailed test. All significant factors were analyzed by the receiver operating characteristic (ROC) curve analysis of SPSS software which were responsible for vision recovery. ROC curves analyses were performed to further discuss the different parameters on the prediction of visual outcome. The mean and standard deviation values of patients' age, symptoms duration, and follow-up time were 64.8±8.9y (range: 28-81), 18.6±11.5d (range: 2-60), and 11.4±0.4mo (range: 6-24), respectively. Steady-post-BCVA analyzed with bivariate correlations was found to be significantly correlated with base diameter ( r =0.521, P <0.001), minimum diameter ( r =0.514, P <0.001), MHI ( r =-0.531, P <0.001), THI ( r =-0.386, P =0.004), HFF ( r =-0.508, P <0.001), and ARF ( r =-0.532, P <0.001). Other characteristic parameters such as age, duration of surgery, height, diameter hole index, and VRF were not statistically significant with steady-post-BCVA. According to area under the curve (AUC) values, values of ARF, MHI, HFF, minimum diameter, THI, and base diameter are 0.806, 0.772, 0.750, 0.705, 0.690, and 0.686, respectively. However, Steady-post-BCVA analysis with bivariate correlations for VRF was no statistical significance. Results of ROC curve analysis indicated that the MHI value, HFF, and ARF was greater than 0.427, 1.027 and 1.558 respectively which could correlate with better visual acuity. Compared with MHI and HFF, ARF could effectively express three-dimensional characteristics of macular hole and achieve better sensitivity and specificity. Thus, ARF could be the most effective parameter to predict the visual outcome in macular hole surgery.

Observed intra-cluster correlation coefficients in a cluster survey sample of patient encounters in general practice in Australia

PubMed Central

Knox, Stephanie A; Chondros, Patty

2004-01-01

Background Cluster sample study designs are cost effective, however cluster samples violate the simple random sample assumption of independence of observations. Failure to account for the intra-cluster correlation of observations when sampling through clusters may lead to an under-powered study. Researchers therefore need estimates of intra-cluster correlation for a range of outcomes to calculate sample size. We report intra-cluster correlation coefficients observed within a large-scale cross-sectional study of general practice in Australia, where the general practitioner (GP) was the primary sampling unit and the patient encounter was the unit of inference. Methods Each year the Bettering the Evaluation and Care of Health (BEACH) study recruits a random sample of approximately 1,000 GPs across Australia. Each GP completes details of 100 consecutive patient encounters. Intra-cluster correlation coefficients were estimated for patient demographics, morbidity managed and treatments received. Intra-cluster correlation coefficients were estimated for descriptive outcomes and for associations between outcomes and predictors and were compared across two independent samples of GPs drawn three years apart. Results Between April 1999 and March 2000, a random sample of 1,047 Australian general practitioners recorded details of 104,700 patient encounters. Intra-cluster correlation coefficients for patient demographics ranged from 0.055 for patient sex to 0.451 for language spoken at home. Intra-cluster correlations for morbidity variables ranged from 0.005 for the management of eye problems to 0.059 for management of psychological problems. Intra-cluster correlation for the association between two variables was smaller than the descriptive intra-cluster correlation of each variable. When compared with the April 2002 to March 2003 sample (1,008 GPs) the estimated intra-cluster correlation coefficients were found to be consistent across samples. Conclusions The demonstrated precision and reliability of the estimated intra-cluster correlations indicate that these coefficients will be useful for calculating sample sizes in future general practice surveys that use the GP as the primary sampling unit. PMID:15613248

Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification

PubMed Central

Wang, Yun; Huang, Fangzhou

2018-01-01

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC2), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible. PMID:29666661

Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification.

PubMed

Xu, Jiucheng; Mu, Huiyu; Wang, Yun; Huang, Fangzhou

2018-01-01

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC 2 ), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible.

Infection prevention efforts of pulmonary tuberculosis patients in the local government clinic of Kuta Baro Aceh Besar

NASA Astrophysics Data System (ADS)

Andika, Fauziah; Syahputra, Muhammad Yusrizal; Marniati

2017-09-01

Pulmonary tuberculosis is one of the infectious diseases that has been known and is still the leading cause of death in the world. It is an old disease which is a global problem in the world and estimated that a third of the world's population has been infected by this bacterium. The purpose of this study was to determine the factors related with the infection prevention efforts of pulmonary tuberculosis patients in the local goverment clinic of Kuta Baro Aceh Besar. This research is descriptive analytic survey using cross sectional design. It used univariate analysis to see the frequency distribution and the percentage of each variable. Meanwhile, the bivariate analysis used chi square test with CI (Confident Interval) of 95%. The samples in this study are 34 people. The research results obtained with good infection prevention efforts of pulmonary tuberculosis is 41.2%, 5.9% for teenagers, 47.1% for knowledgeable people, 17.6% for people who do not work and 44.1% for those who have a positive behavior. The results of the bivariate obtained there is correlation between the prevention of pulmonary tuberculosis infection with age (p = 0.087), Occupation (p = 0.364), knowledge (p = 0.006) and behavior (p = 0.020). To conclude, there is a correlation between knowledge and behaviors with the infection prevention efforts of pulmonary tuberculosis patients and there is no correlation between age and occupation with infection prevention efforts of pulmonary tuberculosis patients. It is expected that the respondents to hold consultations to health officials about a mechanism of prevention to avoid the disease.

Overlap and specificity of genetic and environmental influences on mathematics and reading disability in 10-year-old twins

PubMed Central

Kovas, Y.; Haworth, C.M.A.; Harlaar, N.; Petrill, S.A.; Dale, P.S.; Plomin, R.

2009-01-01

Background To what extent do genetic and environmental influences on reading disability overlap with those on mathematics disability? Multivariate genetic research on the normal range of variation in unselected samples has led to a Generalist Genes Hypothesis which posits that the same genes largely affect individual differences in these abilities in the normal range. However, little is known about the etiology of co-morbidity for the disability extremes of reading and mathematics. Method From 2596 pairs of 10-year-old monozygotic and dizygotic twins assessed on a web-based battery of reading and mathematics tests, we selected the lowest 15% on reading and on mathematics. We conducted bivariate DeFries–Fulker (DF) extremes analyses to assess overlap and specificity of genetic and environmental influences on reading and mathematics disability defined by a 15% cut-off. Results Both reading and mathematics disability are moderately heritable (47% and 43%, respectively) and show only modest shared environmental influence (16% and 20%). There is substantial phenotypic co-morbidity between reading and mathematics disability. Bivariate DF extremes analyses yielded a genetic correlation of .67 between reading disability and mathematics disability, suggesting that they are affected largely by the same genetic factors. The shared environmental correlation is .96 and the non-shared environmental correlation is .08. Conclusions In line with the Generalist Genes Hypothesis, the same set of generalist genes largely affects mathematical and reading disabilities. The dissociation between the disabilities occurs largely due to independent non-shared environmental influences. PMID:17714376

Prediction and Predictability of the Madden Julian Oscillation in the NASA GEOS-5 Seasonal-to-Subseasonal System

NASA Technical Reports Server (NTRS)

Achuthavarier, Deepthi; Koster, Randal; Marshak, Jelena; Schubert, Siegfried; Molod, Andrea

2018-01-01

In this study, we examine the prediction skill and predictability of the Madden Julian Oscillation (MJO) in a recent version of the NASA GEOS-5 atmosphere-ocean coupled model run at at 1/2 degree horizontal resolution. The results are based on a suite of hindcasts produced as part of the NOAA SubX project, consisting of seven ensemble members initialized every 5 days for the period 1999-2015. The atmospheric initial conditions were taken from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and the ocean and the sea ice were taken from a GMAO ocean analysis. The land states were initialized from the MERRA-2 land output, which is based on observation-corrected precipitation fields. We investigated the MJO prediction skill in terms of the bivariate correlation coefficient for the real-time multivariate MJO (RMM) indices. The correlation coefficient stays at or above 0.5 out to forecast lead times of 26-36 days, with a pronounced increase in skill for forecasts initialized from phase 3, when the MJO convective anomaly is located in the central tropical Indian Ocean. A corresponding estimate of the upper limit of the predictability is calculated by considering a single ensemble member as the truth and verifying the ensemble mean of the remaining members against that. The predictability estimates fall between 35-37 days (taken as forecast lead when the correlation reaches 0.5) and are rather insensitive to the initial MJO phase. The model shows slightly higher skill when the initial conditions contain strong MJO events compared to weak events, although the difference in skill is evident only from lead 1 to 20. Similar to other models, the RMM-index-based skill arises mostly from the circulation components of the index. The skill of the convective component of the index drops to 0.5 by day 20 as opposed to day 30 for circulation fields. The propagation of the MJO anomalies over the Maritime Continent does not appear problematic in the GEOS-5 hindcasts implying that the Maritime Continent predictability barrier may not be a major concern in this model. Finally, the MJO prediction skill in this version of GEOS-5 is superior to that of the current seasonal prediction system at the GMAO; this could be partly attributed to a slightly better representation of the MJO in the free running version of this model and partly to the improved atmospheric initialization from MERRA-2.

Bivariate extreme value distributions

NASA Technical Reports Server (NTRS)

Elshamy, M.

1992-01-01

In certain engineering applications, such as those occurring in the analyses of ascent structural loads for the Space Transportation System (STS), some of the load variables have a lower bound of zero. Thus, the need for practical models of bivariate extreme value probability distribution functions with lower limits was identified. We discuss the Gumbel models and present practical forms of bivariate extreme probability distributions of Weibull and Frechet types with two parameters. Bivariate extreme value probability distribution functions can be expressed in terms of the marginal extremel distributions and a 'dependence' function subject to certain analytical conditions. Properties of such bivariate extreme distributions, sums and differences of paired extremals, as well as the corresponding forms of conditional distributions, are discussed. Practical estimation techniques are also given.

Epicardial adipose tissue volume a diagnostic study for independent predicting disorder of circadian rhythm of blood pressure in patients with essential hypertension.

PubMed

Zhou, L; Deng, Y; Gong, J; Chen, X; Zhang, Q; Wang, J

2016-05-30

The aim of the study was to determine whether epicardial adipose tissue volume (EATV), a new cardiometabolic risk factor, is associated with circadian changes of blood pressure (BP) in patients with newly diagnosed essential hypertension. Ninety patients with newly diagnosed essential hypertension underwent ambulatory blood pressure monitoring for 24 h. EATV was measured using cardiac computed tomography. These patients were categorized into three groups according to their BP patterns (group 1, n=46, dipper hypertension, also called normal pattern; group 2, n=24, non-dipper hypertension; group 3, n=20, anti-dipper hypertension; group 2 and 3 are also called abnormal pattern). Data were collected retrospectively and compared between hypertensive patients with normal pattern and abnormal pattern. The normal pattern hypertensive patient had significant lower mean EATV and BP ((EATV, 91.3±29.4 cm3) than those of abnormal pattern patients including group 2 (EATV, 116.2±31.06cm3, <0.01) and group 3 (EATV, 124.8±28.5cm3, P<0.01). Mean systolic BP over 24 h (BPs24) and mean diastolic BP over 24 h (BPd24) of group 1 (BPs24, 135.7 ± 12.6 mmHg; BPd24, 83.6 ± 10.6 mmHg) were significantly lower than those of group 2 (BPs24, 150.1± 17.6 mmHg, P<0.01; BPd24, 93.2 ± 16.5 mmHg, P<0.01) and group 3 (BPs24, 154.1 ± 16.6mmHg, P<0.01; BPd24, 93.8 ± 17.5 mmHg; P<0.01). Bivariate correlation analysis showed that correlation coefficient of EATV with abnormal blood pressure mode was 0.500 (p<0.001), partial correlation coefficient after adjustment for waist circumference and body mass index was 0.469 (p<0.001). When multivariate backward logistic regression analysis was performed to assess the correlation of BP pattern with EAT volume, it showed that the prevalence of abnormal BP pattern (non-dipper and anti-dipper BP pattern) increased by 1.54 times after adjusting for age and gender per additional 10 cm3 of EAT volume. Receiver operating characteristic curve for EAT alone indicated that the cutoff value of 95.17cm3 had the best performance in predicting abnormal BP pattern with a sensitivity of 75.0% and a specificity of 72.7%. EATV was elevated in newly diagnosed and untreated patients with non-dipper hypertension and anti-dipper hypertension. EATV measured by cardiac computed tomography can be used to indicate the increased risk of circadian rhythm of blood pressure.

Two-Way Gene Interaction From Microarray Data Based on Correlation Methods.

PubMed

Alavi Majd, Hamid; Talebi, Atefeh; Gilany, Kambiz; Khayyer, Nasibeh

2016-06-01

Gene networks have generated a massive explosion in the development of high-throughput techniques for monitoring various aspects of gene activity. Networks offer a natural way to model interactions between genes, and extracting gene network information from high-throughput genomic data is an important and difficult task. The purpose of this study is to construct a two-way gene network based on parametric and nonparametric correlation coefficients. The first step in constructing a Gene Co-expression Network is to score all pairs of gene vectors. The second step is to select a score threshold and connect all gene pairs whose scores exceed this value. In the foundation-application study, we constructed two-way gene networks using nonparametric methods, such as Spearman's rank correlation coefficient and Blomqvist's measure, and compared them with Pearson's correlation coefficient. We surveyed six genes of venous thrombosis disease, made a matrix entry representing the score for the corresponding gene pair, and obtained two-way interactions using Pearson's correlation, Spearman's rank correlation, and Blomqvist's coefficient. Finally, these methods were compared with Cytoscape, based on BIND, and Gene Ontology, based on molecular function visual methods; R software version 3.2 and Bioconductor were used to perform these methods. Based on the Pearson and Spearman correlations, the results were the same and were confirmed by Cytoscape and GO visual methods; however, Blomqvist's coefficient was not confirmed by visual methods. Some results of the correlation coefficients are not the same with visualization. The reason may be due to the small number of data.

Factors associated with school-aged children's body mass index in Korean American families.

PubMed

Jang, Myoungock; Grey, Margaret; Sadler, Lois; Jeon, Sangchoon; Nam, Soohyun; Song, Hee-Jung; Whittemore, Robin

2017-08-01

To examine factors associated with children's body mass index and obesity-risk behaviours in Korean American families. Limited data are available about family factors related to overweight and obesity in Korean American children. A cross-sectional study. Convenient sampling was employed to recruit Korean American families in the Northeast of the United States between August 2014 and January 2015. Child, family and societal/demographic/community factors were measured with self-report questionnaires completed by mothers and children. Height and weight were measured to calculate body mass index. Data were analyzed using mixed effects models incorporating within-group correlation in siblings. The sample included 170 Korean American children and 137 mothers. In bivariate analyses, more child screen time, number of children in the household, greater parental underestimation of child's weight and children's participation in the school lunch program were significantly associated with higher child body mass index. In multivariate analyses that included variables showing significant bivariate relationship, no variable was associated with child body mass index. There were no child, family and societal/demographic/community factors related to child body mass index in Korean American families in the multivariate analysis, which is contrary to research in other racial/ethnic groups. In bivariate analyses, there is evidence that some factors were significantly related to child body mass index. Further research is needed to understand the unique behavioural, social and cultural features that contribute to childhood obesity in Korean American families. © 2017 John Wiley & Sons Ltd.

Impact of national income and inequality on sugar and caries relationship.

PubMed

Masood, M; Masood, Y; Newton, T

2012-01-01

The aim of this study was to examine the impact that national income and income inequality in high and low income countries have on the relationship between dental caries and sugar consumption. An ecological study design was used in this study of 73 countries. The mean decayed, missing, or filled permanent teeth (DMFT) for 12-year-old children were obtained from the WHO Oral Health Country/Area Profile Programme. United Nations Food and Agricultural Organization data were used for per capita sugar consumption. Gross national incomes per capita based on purchasing power parity and the Gini coefficient were obtained from World Bank data. Bivariate and multivariate linear regression analysis was performed to estimate the associations between mean DMFT and per capita sugar consumption in different income and income inequality countries. Bivariate and multivariate regression analysis showed that countries with a high national income and low income inequality have a strong negative association between sugar consumption and caries (B = -2.80, R2 = 0.17), whereas countries with a low income and high income inequality have a strong positive relationship between DMFT and per capita sugar consumption (B = -0.89, R2 = 0.20). The relationship between per capita consumption of sugar and dental caries is modified by the absolute level of income of the country, but not by the level of income inequality within a country. Copyright © 2012 S. Karger AG, Basel.

Quantized correlation coefficient for measuring reproducibility of ChIP-chip data.

PubMed

Peng, Shouyong; Kuroda, Mitzi I; Park, Peter J

2010-07-27

Chromatin immunoprecipitation followed by microarray hybridization (ChIP-chip) is used to study protein-DNA interactions and histone modifications on a genome-scale. To ensure data quality, these experiments are usually performed in replicates, and a correlation coefficient between replicates is used often to assess reproducibility. However, the correlation coefficient can be misleading because it is affected not only by the reproducibility of the signal but also by the amount of binding signal present in the data. We develop the Quantized correlation coefficient (QCC) that is much less dependent on the amount of signal. This involves discretization of data into set of quantiles (quantization), a merging procedure to group the background probes, and recalculation of the Pearson correlation coefficient. This procedure reduces the influence of the background noise on the statistic, which then properly focuses more on the reproducibility of the signal. The performance of this procedure is tested in both simulated and real ChIP-chip data. For replicates with different levels of enrichment over background and coverage, we find that QCC reflects reproducibility more accurately and is more robust than the standard Pearson or Spearman correlation coefficients. The quantization and the merging procedure can also suggest a proper quantile threshold for separating signal from background for further analysis. To measure reproducibility of ChIP-chip data correctly, a correlation coefficient that is robust to the amount of signal present should be used. QCC is one such measure. The QCC statistic can also be applied in a variety of other contexts for measuring reproducibility, including analysis of array CGH data for DNA copy number and gene expression data.

Correlation Between Geometric Similarity of Ice Shapes and the Resulting Aerodynamic Performance Degradation: A Preliminary Investigation Using WIND

NASA Technical Reports Server (NTRS)

Wright, William B.; Chung, James

1999-01-01

Aerodynamic performance calculations were performed using WIND on ten experimental ice shapes and the corresponding ten ice shapes predicted by LEWICE 2.0. The resulting data for lift coefficient and drag coefficient are presented. The difference in aerodynamic results between the experimental ice shapes and the LEWICE ice shapes were compared to the quantitative difference in ice shape geometry presented in an earlier report. Correlations were generated to determine the geometric features which have the most effect on performance degradation. Results show that maximum lift and stall angle can be correlated to the upper horn angle and the leading edge minimum thickness. Drag coefficient can be correlated to the upper horn angle and the frequency-weighted average of the Fourier coefficients. Pitching moment correlated with the upper horn angle and to a much lesser extent to the upper and lower horn thicknesses.

Confidence Intervals and "F" Tests for Intraclass Correlation Coefficients Based on Three-Way Mixed Effects Models

ERIC Educational Resources Information Center

Zhou, Hong; Muellerleile, Paige; Ingram, Debra; Wong, Seok P.

2011-01-01

Intraclass correlation coefficients (ICCs) are commonly used in behavioral measurement and psychometrics when a researcher is interested in the relationship among variables of a common class. The formulas for deriving ICCs, or generalizability coefficients, vary depending on which models are specified. This article gives the equations for…

Uses and Misuses of the Correlation Coefficient.

ERIC Educational Resources Information Center

Onwuegbuzie, Anthony J.; Daniel, Larry G.

The purpose of this paper is to provide an in-depth critical analysis of the use and misuse of correlation coefficients. Various analytical and interpretational misconceptions are reviewed, beginning with the egregious assumption that correlational statistics may be useful in inferring causality. Additional misconceptions, stemming from…

Evaluation of icing drag coefficient correlations applied to iced propeller performance prediction

NASA Technical Reports Server (NTRS)

Miller, Thomas L.; Shaw, R. J.; Korkan, K. D.

1987-01-01

Evaluation of three empirical icing drag coefficient correlations is accomplished through application to a set of propeller icing data. The various correlations represent the best means currently available for relating drag rise to various flight and atmospheric conditions for both fixed-wing and rotating airfoils, and the work presented here ilustrates and evaluates one such application of the latter case. The origins of each of the correlations are discussed, and their apparent capabilities and limitations are summarized. These correlations have been made to be an integral part of a computer code, ICEPERF, which has been designed to calculate iced propeller performance. Comparison with experimental propeller icing data shows generally good agreement, with the quality of the predicted results seen to be directly related to the radial icing extent of each case. The code's capability to properly predict thrust coefficient, power coefficient, and propeller efficiency is shown to be strongly dependent on the choice of correlation selected, as well as upon proper specificatioon of radial icing extent.

A Linear Empirical Model of Self-Regulation on Flourishing, Health, Procrastination, and Achievement, Among University Students

PubMed Central

Garzón-Umerenkova, Angélica; de la Fuente, Jesús; Amate, Jorge; Paoloni, Paola V.; Fadda, Salvatore; Pérez, Javier Fiz

2018-01-01

This research aimed to analyze the linear bivariate correlation and structural relations between self-regulation -as a central construct-, with flow, health, procrastination and academic performance, in an academic context. A total of 363 college students took part, 101 men (27.8%) and 262 women (72.2%). Participants had an average age of 22 years and were between the first and fifth year of studies. They were from five different programs and two universities in Bogotá city (Colombia). A validated ad hoc questionnaire of physical and psychological health was applied along with a battery of tests to measure self-regulation, procrastination, and flourishing. To establish an association relationship, Pearson bivariate correlations were performed using SPSS software (v. 22.0), and structural relationship predictive analysis was performed using an SEM on AMOS software (v. 22.0). Regarding this linear association, it was established that (1) self-regulation has a significant positive association on flourishing and overall health, and a negative effect on procrastination. Regarding the structural relation, it confirmed that (2) self-regulation is a direct and positive predictor of flourishing and health; (3) self-regulation predicts procrastination directly and negatively, and academic performance indirectly and positively; and (4) age and gender have a prediction effect on the analyzed variables. Implications, limitations and future research scope are discussed. PMID:29706922

A Linear Empirical Model of Self-Regulation on Flourishing, Health, Procrastination, and Achievement, Among University Students.

PubMed

Garzón-Umerenkova, Angélica; de la Fuente, Jesús; Amate, Jorge; Paoloni, Paola V; Fadda, Salvatore; Pérez, Javier Fiz

2018-01-01

This research aimed to analyze the linear bivariate correlation and structural relations between self-regulation -as a central construct-, with flow, health, procrastination and academic performance, in an academic context. A total of 363 college students took part, 101 men (27.8%) and 262 women (72.2%). Participants had an average age of 22 years and were between the first and fifth year of studies. They were from five different programs and two universities in Bogotá city (Colombia). A validated ad hoc questionnaire of physical and psychological health was applied along with a battery of tests to measure self-regulation, procrastination, and flourishing. To establish an association relationship, Pearson bivariate correlations were performed using SPSS software (v. 22.0), and structural relationship predictive analysis was performed using an SEM on AMOS software (v. 22.0). Regarding this linear association, it was established that (1) self-regulation has a significant positive association on flourishing and overall health, and a negative effect on procrastination. Regarding the structural relation, it confirmed that (2) self-regulation is a direct and positive predictor of flourishing and health; (3) self-regulation predicts procrastination directly and negatively, and academic performance indirectly and positively; and (4) age and gender have a prediction effect on the analyzed variables. Implications, limitations and future research scope are discussed.

Suicidal Ideation During the Postpartum Period.

PubMed

Bodnar-Deren, Susan; Klipstein, Kimberly; Fersh, Madeleine; Shemesh, Eyal; Howell, Elizabeth A

2016-12-01

To examine the association between suicidal ideation (SI), 3 weeks, 3 months, and 6 months postpartum with demographic, psychosocial, clinical factors, and depressive/anxiety symptoms (measured 24-48 hours after delivery), among a cohort of postpartum women. This study included 1,073 mothers who gave birth in a large tertiary New York City hospital (2009-2010). Later, self-report SI was assessed using the suicide measure from the Edinburgh Postnatal Depression Scale and from the Patient Health Questionnaire. Two percent of participants presented with SI during the first 6 months postpartum. In bivariate analyses, race/ethnicity, nativity, insurance, and language were significantly correlated with SI 3 weeks, 3 months, and 6 months postpartum. Screening positive for depression (p = 0.0245) and anxiety (0.0454), assessed 1-2 days postpartum, was significantly correlated with later SI in bivariate analyses, as were antepartum complications (p = 0.001), depressive history (0.001), and self-efficacy (0.045). In adjusted models, antepartum complications (OR = 4.681, 95% CI = 1.99-10.99) and depressive history (OR-3.780, 95% CI = 1.514-9.441) were significantly associated with later postpartum SI. Heightened self-efficacy reduced the odds of later SI (p = 0.050). Findings suggest that SI among a relatively healthy group of new mothers occurs with some frequency. Mothers with a history of depression and antepartum complications may be at increased risk.

Family Reintegration Experiences of Soldiers with Mild Traumatic Brain Injury

DTIC Science & Technology

2014-02-26

depression scores in the spouse. Weak within-couple correlation were indicated on the other measures. Table 3 presents the Spearman correlation matrix...separately. Table 2: Spearman Correlation Coefficients for Couples Spouse MAT Spouse Depression Spouse...Anxiety Soldier MAT -0.06 Soldier Depression -0.61 Soldier Anxiety -0.12 Table 3: Spearman Correlation Coefficients for Soldiers and

Correlation tests of the engine performance parameter by using the detrended cross-correlation coefficient

NASA Astrophysics Data System (ADS)

Dong, Keqiang; Gao, You; Jing, Liming

2015-02-01

The presence of cross-correlation in complex systems has long been noted and studied in a broad range of physical applications. We here focus on an aero-engine system as an example of a complex system. By applying the detrended cross-correlation (DCCA) coefficient method to aero-engine time series, we investigate the effects of the data length and the time scale on the detrended cross-correlation coefficients ρ DCCA ( T, s). We then show, for a twin-engine aircraft, that the engine fuel flow time series derived from the left engine and the right engine exhibit much stronger cross-correlations than the engine exhaust-gas temperature series derived from the left engine and the right engine do.

Variability and interaction of some egg physical and eggshell quality attributes during the entire laying hen cycle.

PubMed

Sirri, F; Zampiga, M; Berardinelli, A; Meluzzi, A

2018-05-01

The aim of this study was to investigate the variability and relationships between some egg physical (egg weight, width, length, shape index, and surface area) and eggshell parameters (weight and percentage, thickness, breaking strength, and L*, a*, and b* values) during the entire laying hen cycle. A total of 8,000 eggs was collected every 5 wk, from 30 to 81 wk of hen age (10 samplings of 400 eggs/house), in 2 identical poultry houses equipped with enriched cages. For the statistical analysis, ANOVA, Bivariate Correlation, Principal Component Analysis (PCA), and Hierarchical Cluster Analysis were used. An increase of egg weight, length, and eggshell lightness (L*) associated with a reduction of eggshell percentage, breaking strength, and redness (a*) was observed as the hen aged (P < 0.05). Overall, the coefficients of variation resulted in <5% in width, length, shape index, and egg surface area; from 5 to 10% of egg weight, shell weight, shell percentage, shell thickness, L*, and b*; and >10% of eggshell breaking strength and a*. According to the PCA, the highest changes during the laying cycle are related to egg physical parameters (32%) and to eggshell breaking strength, percentage, and thickness (26%). The egg physical parameters appeared to be strongly correlated to each other, whereas a slight correlation between eggshell breaking strength and color attributes were evidenced (-0.231 and 0.289, respectively, for L* and a*; P < 0.01). Hierarchical cluster analysis, based on principal components of the overall egg attributes, is hereby considered, and evidenced dissimilarities for eggs laid from peak production up for 39 wk of hen age from the eggs laid afterwards. The latter group could also be divided into 2 subgroups, one comprising eggs laid from 44 and 53 wk of hen age and the other from 58 wk to the end. In conclusion, the large dataset created in this study allowed to extrapolate some robust information regarding the variability and correlations of the egg physical and eggshell quality attributes throughout the entire laying hen cycle.

Prediction of Very High Reynolds Number Compressible Skin Friction

NASA Technical Reports Server (NTRS)

Carlson, John R.

1998-01-01

Flat plate skin friction calculations over a range of Mach numbers from 0.4 to 3.5 at Reynolds numbers from 16 million to 492 million using a Navier Stokes method with advanced turbulence modeling are compared with incompressible skin friction coefficient correlations. The semi-empirical correlation theories of van Driest; Cope; Winkler and Cha; and Sommer and Short T' are used to transform the predicted skin friction coefficients of solutions using two algebraic Reynolds stress turbulence models in the Navier-Stokes method PAB3D. In general, the predicted skin friction coefficients scaled well with each reference temperature theory though, overall the theory by Sommer and Short appeared to best collapse the predicted coefficients. At the lower Reynolds number 3 to 30 million, both the Girimaji and Shih, Zhu and Lumley turbulence models predicted skin-friction coefficients within 2% of the semi-empirical correlation skin friction coefficients. At the higher Reynolds numbers of 100 to 500 million, the turbulence models by Shih, Zhu and Lumley and Girimaji predicted coefficients that were 6% less and 10% greater, respectively, than the semi-empirical coefficients.

A Practical Theory of Micro-Solar Power Sensor Networks

DTIC Science & Technology

2009-04-20

Simulation Platform TOSSIM [LLWC03] ns-2 Matlab C++ AVRORA [TLP05] Reference Hardware Mica2 WINS, Medusa Mica Mica2, Medusa Mica2 Simulated Power Power...scale. From this raw data, we can 162 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 2 4 Correlation coefficient F re qu en cy Histogram of correlation...0.5 0.6 0.7 0.8 0.9 1 0 1 2 Correlation coefficient F re qu en cy Histogram of correlation coefficient with solar radiation measurement (Turbidity at

Multifractal Cross Wavelet Analysis

NASA Astrophysics Data System (ADS)

Jiang, Zhi-Qiang; Gao, Xing-Lu; Zhou, Wei-Xing; Stanley, H. Eugene

Complex systems are composed of mutually interacting components and the output values of these components usually exhibit long-range cross-correlations. Using wavelet analysis, we propose a method of characterizing the joint multifractal nature of these long-range cross correlations, a method we call multifractal cross wavelet analysis (MFXWT). We assess the performance of the MFXWT method by performing extensive numerical experiments on the dual binomial measures with multifractal cross correlations and the bivariate fractional Brownian motions (bFBMs) with monofractal cross correlations. For binomial multifractal measures, we find the empirical joint multifractality of MFXWT to be in approximate agreement with the theoretical formula. For bFBMs, MFXWT may provide spurious multifractality because of the wide spanning range of the multifractal spectrum. We also apply the MFXWT method to stock market indices, and in pairs of index returns and volatilities we find an intriguing joint multifractal behavior. The tests on surrogate series also reveal that the cross correlation behavior, particularly the cross correlation with zero lag, is the main origin of cross multifractality.

Personality correlates of the Five-Factor Model for a sample of business owners/managers: associations with scores on Self-Monitoring, Type A Behavior, Locus of Control, and Subjective Well-being.

PubMed

Morrison, K A

1997-02-01

Bivariate relationships were examined between scores on the Five-Factor Model of personality and four personality dimensions including Self-monitoring, Locus of Control, Type A Behavior, and Subjective Well-being. Data were collected from 307 franchise business owner/managers from four different industries. Scores for Self-monitoring were positively related to those on Extraversion; Self-monitoring was the only personality measure significantly correlated with scores on Openness to Experience. Scores for Type A Behavior, measured by the Jenkins Activity Survey, were negatively correlated with Agreeableness and positively correlated with those for Extraversion. Somewhat surprisingly, the score for Type A Behavior had a relatively low correlation with the score for Conscientiousness. Scores for Subjective Well-being and Locus of Control were most strongly correlated with the positive pole of Neuroticism (Emotional Stability), Conscientiousness, and Extraversion. Possible explanations for the observed relationships are discussed.

INLAND DISSOLVED SALT CHEMISTRY: STATISTICAL EVALUATION OF BIVARIATE AND TERNARY DIAGRAM MODELS FOR SURFACE AND SUBSURFACE WATERS

EPA Science Inventory

We compared the use of ternary and bivariate diagrams to distinguish the effects of atmospheric precipitation, rock weathering, and evaporation on inland surface and subsurface water chemistry. The three processes could not be statistically differentiated using bivariate models e...

An Examination of New Paradigms for Spline Approximations.

PubMed

Witzgall, Christoph; Gilsinn, David E; McClain, Marjorie A

2006-01-01

Lavery splines are examined in the univariate and bivariate cases. In both instances relaxation based algorithms for approximate calculation of Lavery splines are proposed. Following previous work Gilsinn, et al. [7] addressing the bivariate case, a rotationally invariant functional is assumed. The version of bivariate splines proposed in this paper also aims at irregularly spaced data and uses Hseih-Clough-Tocher elements based on the triangulated irregular network (TIN) concept. In this paper, the univariate case, however, is investigated in greater detail so as to further the understanding of the bivariate case.

A generalized right truncated bivariate Poisson regression model with applications to health data.

PubMed

Islam, M Ataharul; Chowdhury, Rafiqul I

2017-01-01

A generalized right truncated bivariate Poisson regression model is proposed in this paper. Estimation and tests for goodness of fit and over or under dispersion are illustrated for both untruncated and right truncated bivariate Poisson regression models using marginal-conditional approach. Estimation and test procedures are illustrated for bivariate Poisson regression models with applications to Health and Retirement Study data on number of health conditions and the number of health care services utilized. The proposed test statistics are easy to compute and it is evident from the results that the models fit the data very well. A comparison between the right truncated and untruncated bivariate Poisson regression models using the test for nonnested models clearly shows that the truncated model performs significantly better than the untruncated model.

A generalized right truncated bivariate Poisson regression model with applications to health data

PubMed Central

Islam, M. Ataharul; Chowdhury, Rafiqul I.

2017-01-01

A generalized right truncated bivariate Poisson regression model is proposed in this paper. Estimation and tests for goodness of fit and over or under dispersion are illustrated for both untruncated and right truncated bivariate Poisson regression models using marginal-conditional approach. Estimation and test procedures are illustrated for bivariate Poisson regression models with applications to Health and Retirement Study data on number of health conditions and the number of health care services utilized. The proposed test statistics are easy to compute and it is evident from the results that the models fit the data very well. A comparison between the right truncated and untruncated bivariate Poisson regression models using the test for nonnested models clearly shows that the truncated model performs significantly better than the untruncated model. PMID:28586344

Predonation Volume of Future Remnant Cortical Kidney Helps Predict Postdonation Renal Function in Live Kidney Donors.

PubMed

Fananapazir, Ghaneh; Benzl, Robert; Corwin, Michael T; Chen, Ling-Xin; Sageshima, Junichiro; Stewart, Susan L; Troppmann, Christoph

2018-07-01

Purpose To determine whether the predonation computed tomography (CT)-based volume of the future remnant kidney is predictive of postdonation renal function in living kidney donors. Materials and Methods This institutional review board-approved, retrospective, HIPAA-compliant study included 126 live kidney donors who had undergone predonation renal CT between January 2007 and December 2014 as well as 2-year postdonation measurement of estimated glomerular filtration rate (eGFR). The whole kidney volume and cortical volume of the future remnant kidney were measured and standardized for body surface area (BSA). Bivariate linear associations between the ratios of whole kidney volume to BSA and cortical volume to BSA were obtained. A linear regression model for 2-year postdonation eGFR that incorporated donor age, sex, and either whole kidney volume-to-BSA ratio or cortical volume-to-BSA ratio was created, and the coefficient of determination (R 2 ) for the model was calculated. Factors not statistically additive in assessing 2-year eGFR were removed by using backward elimination, and the coefficient of determination for this parsimonious model was calculated. Results Correlation was slightly better for cortical volume-to-BSA ratio than for whole kidney volume-to-BSA ratio (r = 0.48 vs r = 0.44, respectively). The linear regression model incorporating all donor factors had an R 2 of 0.66. The only factors that were significantly additive to the equation were cortical volume-to-BSA ratio and predonation eGFR (P = .01 and P < .01, respectively), and the final parsimonious linear regression model incorporating these two variables explained almost the same amount of variance (R 2 = 0.65) as did the full model. Conclusion The cortical volume of the future remnant kidney helped predict postdonation eGFR at 2 years. The cortical volume-to-BSA ratio should thus be considered for addition as an important variable to living kidney donor evaluation and selection guidelines. © RSNA, 2018.

Repeatability of chemical-shift-encoded water-fat MRI and diffusion-tensor imaging in lower extremity muscles in children.

PubMed

Ponrartana, Skorn; Andrade, Kristine E; Wren, Tishya A L; Ramos-Platt, Leigh; Hu, Houchun H; Bluml, Stefan; Gilsanz, Vicente

2014-06-01

The purpose of this study was to assess the repeatability of water-fat MRI and diffusion-tensor imaging (DTI) as quantitative biomarkers of pediatric lower extremity skeletal muscle. MRI at 3 T of a randomly selected thigh and lower leg of seven healthy children was studied using water-fat separation and DTI techniques. Muscle-fat fraction, apparent diffusion coefficient (ADC), and fractional anisotropy (FA) values were calculated. Test-retest and interrater repeatability were assessed by calculating the Pearson correlation coefficient, intraclass correlation coefficient, and Bland-Altman analysis. Bland-Altman plots show that the mean difference between test-retest and interrater measurements of muscle-fat fraction, ADC, and FA was near 0. The correlation coefficients and intraclass correlation coefficients were all between 0.88 and 0.99 (p < 0.05), suggesting excellent reliability of the measurements. Muscle-fat fraction measurements from water-fat MRI exhibited the highest intraclass correlation coefficient. Interrater agreement was consistently better than test-retest comparisons. Water-fat MRI and DTI measurements in lower extremity skeletal muscles are objective repeatable biomarkers in children. This knowledge should aid in the understanding of the number of participants needed in clinical trials when using these determinations as an outcome measure to noninvasively monitor neuromuscular disease.

Observations of copolar correlation coefficient through a bright band at vertical incidence

NASA Technical Reports Server (NTRS)

Zrnic, D. S.; Raghavan, R.; Chandrasekar, V.

1994-01-01

This paper discusses an application of polarimetric measurements at vertical incidence. In particular, the correlation coefficients between linear copolar components are examined, and measurements obtained with the National Severe Storms Laboratory (NSSL)'s and National Center for Atmospheric Research (NCAR)'s polarimetric radars are presented. The data are from two well-defined bright bands. A sharp decrease of the correlation coefficient, confined to a height interval of a few hundred meters, marks the bottom of the bright band.

Relationship of body mass index to percent body fat and waist circumference among schoolchildren in Japan--the influence of gender and obesity: a population-based cross-sectional study.

PubMed

Ochiai, Hirotaka; Shirasawa, Takako; Nishimura, Rimei; Morimoto, Aya; Shimada, Naoki; Ohtsu, Tadahiro; Kujirai, Emiko; Hoshino, Hiromi; Tajima, Naoko; Kokaze, Akatsuki

2010-08-18

Although the correlation coefficient between body mass index (BMI) and percent body fat (%BF) or waist circumference (WC) has been reported, studies conducted among population-based schoolchildren to date have been limited in Japan, where %BF and WC are not usually measured in annual health examinations at elementary schools or junior high schools. The aim of the present study was to investigate the relationship of BMI to %BF and WC and to examine the influence of gender and obesity on these relationships among Japanese schoolchildren. Subjects included 3,750 schoolchildren from the fourth and seventh grade in Ina-town, Saitama Prefecture, Japan between 2004 and 2008. Information about subject's age, sex, height, weight, %BF, and WC was collected from annual physical examinations. %BF was measured with a bipedal biometrical impedance analysis device. Obesity was defined by the following two criteria: the obese definition of the Centers for Disease Control and Prevention, and the definition of obesity for Japanese children. Pearson's correlation coefficients between BMI and %BF or WC were calculated separately for sex. Among fourth graders, the correlation coefficients between BMI and %BF were 0.74 for boys and 0.97 for girls, whereas those between BMI and WC were 0.94 for boys and 0.90 for girls. Similar results were observed in the analysis of seventh graders. The correlation coefficient between BMI and %BF varied by physique (obese or non-obese), with weaker correlations among the obese regardless of the definition of obesity; most correlation coefficients among obese boys were less than 0.5, whereas most correlations among obese girls were more than 0.7. On the other hand, the correlation coefficients between BMI and WC were more than 0.8 among boys and almost all coefficients were more than 0.7 among girls, regardless of physique. BMI was positively correlated with %BF and WC among Japanese schoolchildren. The correlations could be influenced by obesity as well as by gender. Accordingly, it is essential to consider gender and obesity when using BMI as a surrogate for %BF and WC for epidemiological use.

Semi-quantitative spectrographic analysis and rank correlation in geochemistry

USGS Publications Warehouse

Flanagan, F.J.

1957-01-01

The rank correlation coefficient, rs, which involves less computation than the product-moment correlation coefficient, r, can be used to indicate the degree of relationship between two elements. The method is applicable in situations where the assumptions underlying normal distribution correlation theory may not be satisfied. Semi-quantitative spectrographic analyses which are reported as grouped or partly ranked data can be used to calculate rank correlations between elements. ?? 1957.

Effect of inhibitory feedback on correlated firing of spiking neural network.

PubMed

Xie, Jinli; Wang, Zhijie

2013-08-01

Understanding the properties and mechanisms that generate different forms of correlation is critical for determining their role in cortical processing. Researches on retina, visual cortex, sensory cortex, and computational model have suggested that fast correlation with high temporal precision appears consistent with common input, and correlation on a slow time scale likely involves feedback. Based on feedback spiking neural network model, we investigate the role of inhibitory feedback in shaping correlations on a time scale of 100 ms. Notably, the relationship between the correlation coefficient and inhibitory feedback strength is non-monotonic. Further, computational simulations show how firing rate and oscillatory activity form the basis of the mechanisms underlying this relationship. When the mean firing rate holds unvaried, the correlation coefficient increases monotonically with inhibitory feedback, but the correlation coefficient keeps decreasing when the network has no oscillatory activity. Our findings reveal that two opposing effects of the inhibitory feedback on the firing activity of the network contribute to the non-monotonic relationship between the correlation coefficient and the strength of the inhibitory feedback. The inhibitory feedback affects the correlated firing activity by modulating the intensity and regularity of the spike trains. Finally, the non-monotonic relationship is replicated with varying transmission delay and different spatial network structure, demonstrating the universality of the results.

Robust Approximations to the Non-Null Distribution of the Product Moment Correlation Coefficient I: The Phi Coefficient.

ERIC Educational Resources Information Center

Edwards, Lynne K.; Meyers, Sarah A.

Correlation coefficients are frequently reported in educational and psychological research. The robustness properties and optimality among practical approximations when phi does not equal 0 with moderate sample sizes are not well documented. Three major approximations and their variations are examined: (1) a normal approximation of Fisher's Z,…

Correcting Coefficient Alpha for Correlated Errors: Is [alpha][K]a Lower Bound to Reliability?

ERIC Educational Resources Information Center

Rae, Gordon

2006-01-01

When errors of measurement are positively correlated, coefficient alpha may overestimate the "true" reliability of a composite. To reduce this inflation bias, Komaroff (1997) has proposed an adjusted alpha coefficient, ak. This article shows that ak is only guaranteed to be a lower bound to reliability if the latter does not include correlated…

Prediction of stream volatilization coefficients

USGS Publications Warehouse

Rathbun, Ronald E.

1990-01-01

Equations are developed for predicting the liquid-film and gas-film reference-substance parameters for quantifying volatilization of organic solutes from streams. Molecular weight and molecular-diffusion coefficients of the solute are used as correlating parameters. Equations for predicting molecular-diffusion coefficients of organic solutes in water and air are developed, with molecular weight and molal volume as parameters. Mean absolute errors of prediction for diffusion coefficients in water are 9.97% for the molecular-weight equation, 6.45% for the molal-volume equation. The mean absolute error for the diffusion coefficient in air is 5.79% for the molal-volume equation. Molecular weight is not a satisfactory correlating parameter for diffusion in air because two equations are necessary to describe the values in the data set. The best predictive equation for the liquid-film reference-substance parameter has a mean absolute error of 5.74%, with molal volume as the correlating parameter. The best equation for the gas-film parameter has a mean absolute error of 7.80%, with molecular weight as the correlating parameter.

Moral distress and burnout syndrome: are there relationships between these phenomena in nursing workers?

PubMed

Dalmolin, Graziele de Lima; Lunardi, Valéria Lerch; Lunardi, Guilherme Lerch; Barlem, Edison Luiz Devos; Silveira, Rosemary Silva da

2014-01-01

to identify relationships between moral distress and Burnout in the professional performance from the perceptions of the experiences of nursing workers. this is a survey type study with 375 nursing workers working in three different hospitals of southern Rio Grande do Sul, with the application of adaptations of the Moral Distress Scale and the Maslach Burnout Inventory, validated and standardized for use in Brazil. Data validation occurred through factor analysis and Cronbach's alpha. For the data analysis bivariate analysis using Pearson's correlation and multivariate analysis using multiple regression were performed. the existence of a weak correlation between moral distress and Burnout was verified. A possible positive correlation between Burnout and therapeutic obstinacy, and a negative correlation between professional fulfillment and moral distress were identified. the need was identified for further studies that include mediating and moderating variables that may explain more clearly the models studied.

Moral distress and Burnout syndrome: are there relationships between these phenomena in nursing workers?1

PubMed Central

Dalmolin, Graziele de Lima; Lunardi, Valéria Lerch; Lunardi, Guilherme Lerch; Barlem, Edison Luiz Devos; da Silveira, Rosemary Silva

2014-01-01

Objective to identify relationships between moral distress and Burnout in the professional performance from the perceptions of the experiences of nursing workers. Methods this is a survey type study with 375 nursing workers working in three different hospitals of southern Rio Grande do Sul, with the application of adaptations of the Moral Distress Scale and the Maslach Burnout Inventory, validated and standardized for use in Brazil. Data validation occurred through factor analysis and Cronbach's alpha. For the data analysis bivariate analysis using Pearson's correlation and multivariate analysis using multiple regression were performed. Results the existence of a weak correlation between moral distress and Burnout was verified. A possible positive correlation between Burnout and therapeutic obstinacy, and a negative correlation between professional fulfillment and moral distress were identified. Conclusion the need was identified for further studies that include mediating and moderating variables that may explain more clearly the models studied. PMID:24553701

Specification, testing, and interpretation of gene-by-measured-environment interaction models in the presence of gene-environment correlation

PubMed Central

Rathouz, Paul J.; Van Hulle, Carol A.; Lee Rodgers, Joseph; Waldman, Irwin D.; Lahey, Benjamin B.

2009-01-01

Purcell (2002) proposed a bivariate biometric model for testing and quantifying the interaction between latent genetic influences and measured environments in the presence of gene-environment correlation. Purcell’s model extends the Cholesky model to include gene-environment interaction. We examine a number of closely-related alternative models that do not involve gene-environment interaction but which may fit the data as well Purcell’s model. Because failure to consider these alternatives could lead to spurious detection of gene-environment interaction, we propose alternative models for testing gene-environment interaction in the presence of gene-environment correlation, including one based on the correlated factors model. In addition, we note mathematical errors in the calculation of effect size via variance components in Purcell’s model. We propose a statistical method for deriving and interpreting variance decompositions that are true to the fitted model. PMID:18293078

A Study of Effects of MultiCollinearity in the Multivariable Analysis

PubMed Central

Yoo, Wonsuk; Mayberry, Robert; Bae, Sejong; Singh, Karan; (Peter) He, Qinghua; Lillard, James W.

2015-01-01

A multivariable analysis is the most popular approach when investigating associations between risk factors and disease. However, efficiency of multivariable analysis highly depends on correlation structure among predictive variables. When the covariates in the model are not independent one another, collinearity/multicollinearity problems arise in the analysis, which leads to biased estimation. This work aims to perform a simulation study with various scenarios of different collinearity structures to investigate the effects of collinearity under various correlation structures amongst predictive and explanatory variables and to compare these results with existing guidelines to decide harmful collinearity. Three correlation scenarios among predictor variables are considered: (1) bivariate collinear structure as the most simple collinearity case, (2) multivariate collinear structure where an explanatory variable is correlated with two other covariates, (3) a more realistic scenario when an independent variable can be expressed by various functions including the other variables. PMID:25664257

A Study of Effects of MultiCollinearity in the Multivariable Analysis.

PubMed

Yoo, Wonsuk; Mayberry, Robert; Bae, Sejong; Singh, Karan; Peter He, Qinghua; Lillard, James W

2014-10-01

A multivariable analysis is the most popular approach when investigating associations between risk factors and disease. However, efficiency of multivariable analysis highly depends on correlation structure among predictive variables. When the covariates in the model are not independent one another, collinearity/multicollinearity problems arise in the analysis, which leads to biased estimation. This work aims to perform a simulation study with various scenarios of different collinearity structures to investigate the effects of collinearity under various correlation structures amongst predictive and explanatory variables and to compare these results with existing guidelines to decide harmful collinearity. Three correlation scenarios among predictor variables are considered: (1) bivariate collinear structure as the most simple collinearity case, (2) multivariate collinear structure where an explanatory variable is correlated with two other covariates, (3) a more realistic scenario when an independent variable can be expressed by various functions including the other variables.

Two-Way Gene Interaction From Microarray Data Based on Correlation Methods

PubMed Central

Alavi Majd, Hamid; Talebi, Atefeh; Gilany, Kambiz; Khayyer, Nasibeh

2016-01-01

Background Gene networks have generated a massive explosion in the development of high-throughput techniques for monitoring various aspects of gene activity. Networks offer a natural way to model interactions between genes, and extracting gene network information from high-throughput genomic data is an important and difficult task. Objectives The purpose of this study is to construct a two-way gene network based on parametric and nonparametric correlation coefficients. The first step in constructing a Gene Co-expression Network is to score all pairs of gene vectors. The second step is to select a score threshold and connect all gene pairs whose scores exceed this value. Materials and Methods In the foundation-application study, we constructed two-way gene networks using nonparametric methods, such as Spearman’s rank correlation coefficient and Blomqvist’s measure, and compared them with Pearson’s correlation coefficient. We surveyed six genes of venous thrombosis disease, made a matrix entry representing the score for the corresponding gene pair, and obtained two-way interactions using Pearson’s correlation, Spearman’s rank correlation, and Blomqvist’s coefficient. Finally, these methods were compared with Cytoscape, based on BIND, and Gene Ontology, based on molecular function visual methods; R software version 3.2 and Bioconductor were used to perform these methods. Results Based on the Pearson and Spearman correlations, the results were the same and were confirmed by Cytoscape and GO visual methods; however, Blomqvist’s coefficient was not confirmed by visual methods. Conclusions Some results of the correlation coefficients are not the same with visualization. The reason may be due to the small number of data. PMID:27621916

Python Waveform Cross-Correlation

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

Templeton, Dennise

PyWCC is a tool to compute seismic waveform cross-correlation coefficients on single-component or multiple-component seismic data across a network of seismic sensors. PyWCC compares waveform data templates with continuous seismic data, associates the resulting detections, identifies the template with the highest cross-correlation coefficient, and outputs a catalog of detections above a user-defined absolute cross-correlation threshold value.

Hadamard multimode optical imaging transceiver

DOEpatents

Cooke, Bradly J; Guenther, David C; Tiee, Joe J; Kellum, Mervyn J; Olivas, Nicholas L; Weisse-Bernstein, Nina R; Judd, Stephen L; Braun, Thomas R

2012-10-30

Disclosed is a method and system for simultaneously acquiring and producing results for multiple image modes using a common sensor without optical filtering, scanning, or other moving parts. The system and method utilize the Walsh-Hadamard correlation detection process (e.g., functions/matrix) to provide an all-binary structure that permits seamless bridging between analog and digital domains. An embodiment may capture an incoming optical signal at an optical aperture, convert the optical signal to an electrical signal, pass the electrical signal through a Low-Noise Amplifier (LNA) to create an LNA signal, pass the LNA signal through one or more correlators where each correlator has a corresponding Walsh-Hadamard (WH) binary basis function, calculate a correlation output coefficient for each correlator as a function of the corresponding WH binary basis function in accordance with Walsh-Hadamard mathematical principles, digitize each of the correlation output coefficient by passing each correlation output coefficient through an Analog-to-Digital Converter (ADC), and performing image mode processing on the digitized correlation output coefficients as desired to produce one or more image modes. Some, but not all, potential image modes include: multi-channel access, temporal, range, three-dimensional, and synthetic aperture.

Relative validity of an FFQ to estimate daily food and nutrient intakes for Chilean adults.

PubMed

Dehghan, Mahshid; Martinez, Solange; Zhang, Xiaohe; Seron, Pamela; Lanas, Fernando; Islam, Shofiqul; Merchant, Anwar T

2013-10-01

FFQ are commonly used to rank individuals by their food and nutrient intakes in large epidemiological studies. The purpose of the present study was to develop and validate an FFQ to rank individuals participating in an ongoing Prospective Urban and Rural Epidemiological (PURE) study in Chile. An FFQ and four 24 h dietary recalls were completed over 1 year. Pearson correlation coefficients, energy-adjusted and de-attenuated correlations and weighted kappa were computed between the dietary recalls and the FFQ. The level of agreement between the two dietary assessment methods was evaluated by Bland-Altman analysis. Temuco, Chile. Overall, 166 women and men enrolled in the present study. One hundred men and women participated in FFQ development and sixty-six individuals participated in FFQ validation. The FFQ consisted of 109 food items. For nutrients, the crude correlation coefficients between the dietary recalls and FFQ varied from 0.14 (protein) to 0.44 (fat). Energy adjustment and de-attenuation improved correlation coefficients and almost all correlation coefficients exceeded 0.40. Similar correlation coefficients were observed for food groups; the highest de-attenuated energy adjusted correlation coefficient was found for margarine and butter (0.75) and the lowest for potatoes (0.12). The FFQ showed moderate to high agreement for most nutrients and food groups, and can be used to rank individuals based on energy, nutrient and food intakes. The validation study was conducted in a unique setting and indicated that the tool is valid for use by adults in Chile.

[Habitat suitability index of larval Japanese Halfbeak (Hyporhamphus sajori) in Bohai Sea based on geographically weighted regression.

PubMed

Zhao, Yang; Zhang, Xue Qing; Bian, Xiao Dong

2018-01-01

To investigate the early supplementary processes of fishre sources in the Bohai Sea, the geographically weighted regression (GWR) was introduced to the habitat suitability index (HSI) model. The Bohai Sea larval Japanese Halfbeak HSI GWR model was established with four environmental variables, including sea surface temperature (SST), sea surface salinity (SSS), water depth (DEP), and chlorophyll a concentration (Chl a). Results of the simulation showed that the four variables had different performances in August 2015. SST and Chl a were global variables, and had little impacts on HSI, with the regression coefficients of -0.027 and 0.006, respectively. SSS and DEP were local variables, and had larger impacts on HSI, while the average values of absolute values of their regression coefficients were 0.075 and 0.129, respectively. In the central Bohai Sea, SSS showed a negative correlation with HSI, and the most negative correlation coefficient was -0.3. In contrast, SSS was correlated positively but weakly with HSI in the three bays of Bohai Sea, and the largest correlation coefficient was 0.1. In particular, DEP and HSI were negatively correlated in the entire Bohai Sea, while they were more negatively correlated in the three bays of Bohai than in the central Bohai Sea, and the most negative correlation coefficient was -0.16 in the three bays. The Poisson regression coefficient of the HSI GWR model was 0.705, consistent with field measurements. Therefore, it could provide a new method for the research on fish habitats in the future.

Psychometric properties of the modified RESIDE physical activity questionnaire among low-income overweight women.

PubMed

Jones, Sydney A; Evenson, Kelly R; Johnston, Larry F; Trost, Stewart G; Samuel-Hodge, Carmen; Jewell, David A; Kraschnewski, Jennifer L; Keyserling, Thomas C

2015-01-01

This study explored the criterion-related validity and test-retest reliability of the modified RESIDential Environment physical activity questionnaire and whether the instrument's validity varied by body mass index, education, race/ethnicity, or employment status. Validation study using baseline data collected for randomized trial of a weight loss intervention. Participants recruited from health departments wore an ActiGraph accelerometer and self-reported non-occupational walking, moderate and vigorous physical activity on the modified RESIDential Environment questionnaire. We assessed validity (n=152) using Spearman correlation coefficients, and reliability (n=57) using intraclass correlation coefficients. When compared to steps, moderate physical activity, and bouts of moderate/vigorous physical activity measured by accelerometer, these questionnaire measures showed fair evidence for validity: recreational walking (Spearman correlation coefficients 0.23-0.36), total walking (Spearman correlation coefficients 0.24-0.37), and total moderate physical activity (Spearman correlation coefficients 0.18-0.36). Correlations for self-reported walking and moderate physical activity were higher among unemployed participants and women with lower body mass indices. Generally no other variability in the validity of the instrument was found. Evidence for reliability of RESIDential Environment measures of recreational walking, total walking, and total moderate physical activity was substantial (intraclass correlation coefficients 0.56-0.68). Evidence for questionnaire validity and reliability varied by activity domain and was strongest for walking measures. The questionnaire may capture physical activity less accurately among women with higher body mass indices and employed participants. Capturing occupational activity, specifically walking at work, may improve questionnaire validity. Copyright © 2014 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Nonlinearity of the forward-backward correlation function in the model with string fusion

NASA Astrophysics Data System (ADS)

Vechernin, Vladimir

2017-12-01

The behavior of the forward-backward correlation functions and the corresponding correlation coefficients between multiplicities and transverse momenta of particles produced in high energy hadronic interactions is analyzed by analytical and MC calculations in the models with and without string fusion. The string fusion is taking into account in simplified form by introducing the lattice in the transverse plane. The results obtained with two alternative definitions of the forward-backward correlation coefficient are compared. It is shown that the nonlinearity of correlation functions increases with the width of observation windows, leading at small string density to a strong dependence of correlation coefficient value on the definition. The results of the modeling enable qualitatively to explain the experimentally observed features in the behavior of the correlation functions between multiplicities and mean transverse momenta at small and large multiplicities.

Some bivariate distributions for modeling the strength properties of lumber

Treesearch

Richard A. Johnson; James W. Evans; David W. Green

Accurate modeling of the joint stochastic nature of the strength properties of dimension lumber is essential to the determination of reliability-based design safety factors. This report reviews the major techniques for obtaining bivariate distributions and then discusses bivariate distributions whose marginal distributions suggest they might be useful for modeling the...

The relationship between the managerial skills and results of "performance evaluation "tool among nursing managers in teaching hospitals of Iran University of Medical Science.

PubMed

Isfahani, Haleh Mousavi; Aryankhesal, Aidin; Haghani, Hamid

2014-09-25

Performance of different organizations, such as hospitals is mainly influenced by their managers' performance. Nursing managers have an important role in hospital performance and their managerial skills can improve the quality of the services. Hence, the present study was conducted in order to assess the relationship between the managerial skills and the results of their performance evaluation in Teaching Hospitals of Iran University of Medical Science in 2013. The research used the cross sectional method in 2013. It was done by distributing a managerial skills assessment questionnaire, with close-ended questions in 5 choice Likert scale, among 181 managers and head nurses of hospitals of Iran university of Medical Sciences; among which 131 answered the questions. Another data collection tools was a forms to record evaluation marks from the personnel records. We used Pearson and Spearman correlation tests and SPSS for analysis and description (frequency, mean and standard deviation). Results showed that the managerial skills of the nursing mangers were fair (2.57 out of 5) and the results of the performance evaluation were in a good condition (98.44). The mangers' evaluation results and the managerial skills scores were not in a meaningful correlation (r=0.047 np=0.856). The research showed no correlation between different domains of managerial skills and the performance evaluation marks: decision making skills (r=0.074 and p=0.399), leadership (correlation coefficient 0.028 and p=0.654), motivation (correlation coefficient 0.118 and p=0.163), communication  (correlation coefficient 0.116 and p=0.122), systematic thinking  (correlation coefficient 0.028 and p=0.828), time management (correlation coefficient 0.077 and p=0.401) and strategic thinking  (correlation coefficient 0.041 and p=0.756). Lack of any correlation and relation between managers' managerial skills and their performance evaluation results shows need to a fundamental revision at managers' performance evaluation form.

Correlates of Persistent Smoking in Bars Subject to Smokefree Workplace Policy

PubMed Central

Moore, Roland S.; Lee, Juliet P.; Martin, Scott E.; Todd, Michael; Chu, Bong Chul

2009-01-01

This study’s goal was to characterize physical and social environments of stand-alone bars associated with indoor smoking despite California’s smokefree workplace law. In a random sample of 121 stand-alone bars in San Francisco, trained observers collected data on patrons, staff, neighborhood, indoor settings and smoking behaviors. Using bivariate (chi-square) and hierarchical linear modeling analyses, we identified four correlates of patrons’ indoor smoking: 1) bars serving predominantly Asian or Irish patrons, 2) ashtrays, 3) bartender smoking, and 4) female bartenders. Public health officials charged with enforcement of smokefree bar policies may need to attend to social practices within bars, and heighten perceptions of consistent enforcement of smokefree workplace laws. PMID:19440522

Pulmonary Catherization Data Correlate Poorly with Renal Function in Heart Failure.

PubMed

Masha, Luke; Stone, James; Stone, Danielle; Zhang, Jun; Sheng, Luo

2018-04-10

The mechanisms of renal dysfunction in heart failure are poorly understood. We chose to explore the relationship of cardiac filling pressures and cardiac index (CI) in relation to renal dysfunction in advanced heart failure. To determine the relationship between renal function and cardiac filling pressures using the United Network of Organ Sharing (UNOS) pulmonary artery catherization registry. Patients over the age of 18 years who were listed for single-organ heart transplantation were included. Exclusion criteria included a history of mechanical circulatory support, previous transplantation, any use of renal replacement therapy, prior history of malignancy, and cardiac surgery, amongst others. Correlations between serum creatinine (SCr) and CI, pulmonary capillary wedge pressure (PCWP), pulmonary artery systolic pressure (PASP), and pulmonary artery diastolic pressure (PADP) were assessed by Pearson correlation coefficients and simple linear regression coefficients. Pearson correlation coefficients between SCr and PCWP, PASP, and PADP were near zero with values of 0.1, 0.07, and 0.08, respectively (p < 0.0001). A weak negative correlation coefficient between SCr and CI was found (correlation coefficient, -0.045, p = 0.027). In a subgroup of young patients unlikely to have noncardiac etiologies, no significant correlations between these values were identified. These findings suggest that, as assessed by pulmonary artery catherization, none of the factors - PCWP, PASP, PADP, or CI - play a prominent role in cardiorenal syndromes. © 2018 S. Karger AG, Basel.

Apparent Diffusion Coefficient and Dynamic Contrast-Enhanced Magnetic Resonance Imaging in Pancreatic Cancer: Characteristics and Correlation With Histopathologic Parameters.

PubMed

Ma, Wanling; Li, Na; Zhao, Weiwei; Ren, Jing; Wei, Mengqi; Yang, Yong; Wang, Yingmei; Fu, Xin; Zhang, Zhuoli; Larson, Andrew C; Huan, Yi

2016-01-01

To clarify diffusion and perfusion abnormalities and evaluate correlation between apparent diffusion coefficient (ADC), MR perfusion and histopathologic parameters of pancreatic cancer (PC). Eighteen patients with PC underwent diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Parameters of DCE-MRI and ADC of cancer and non-cancerous tissue were compared. Correlation between the rate constant that represents transfer of contrast agent from the arterial blood into the extravascular extracellular space (K, volume of the extravascular extracellular space per unit volume of tissue (Ve), and ADC of PC and histopathologic parameters were analyzed. The rate constant that represents transfer of contrast agent from the extravascular extracellular space into blood plasma, K, tissue volume fraction occupied by vascular space, and ADC of PC were significantly lower than nontumoral pancreases. Ve of PC was significantly higher than that of nontumoral pancreas. Apparent diffusion coefficient and K values of PC were negatively correlated to fibrosis content and fibroblast activation protein staining score. Fibrosis content was positively correlated to Ve. Apparent diffusion coefficient values and parameters of DCE-MRI can differentiate PC from nontumoral pancreases. There are correlations between ADC, K, Ve, and fibrosis content of PC. Fibroblast activation protein staining score of PC is negatively correlated to ADC and K. Apparent diffusion coefficient, K, and Ve may be feasible to predict prognosis of PC.

An improved method for bivariate meta-analysis when within-study correlations are unknown.

PubMed

Hong, Chuan; D Riley, Richard; Chen, Yong

2018-03-01

Multivariate meta-analysis, which jointly analyzes multiple and possibly correlated outcomes in a single analysis, is becoming increasingly popular in recent years. An attractive feature of the multivariate meta-analysis is its ability to account for the dependence between multiple estimates from the same study. However, standard inference procedures for multivariate meta-analysis require the knowledge of within-study correlations, which are usually unavailable. This limits standard inference approaches in practice. Riley et al proposed a working model and an overall synthesis correlation parameter to account for the marginal correlation between outcomes, where the only data needed are those required for a separate univariate random-effects meta-analysis. As within-study correlations are not required, the Riley method is applicable to a wide variety of evidence synthesis situations. However, the standard variance estimator of the Riley method is not entirely correct under many important settings. As a consequence, the coverage of a function of pooled estimates may not reach the nominal level even when the number of studies in the multivariate meta-analysis is large. In this paper, we improve the Riley method by proposing a robust variance estimator, which is asymptotically correct even when the model is misspecified (ie, when the likelihood function is incorrect). Simulation studies of a bivariate meta-analysis, in a variety of settings, show a function of pooled estimates has improved performance when using the proposed robust variance estimator. In terms of individual pooled estimates themselves, the standard variance estimator and robust variance estimator give similar results to the original method, with appropriate coverage. The proposed robust variance estimator performs well when the number of studies is relatively large. Therefore, we recommend the use of the robust method for meta-analyses with a relatively large number of studies (eg, m≥50). When the sample size is relatively small, we recommend the use of the robust method under the working independence assumption. We illustrate the proposed method through 2 meta-analyses. Copyright © 2017 John Wiley & Sons, Ltd.

Catching ghosts with a coarse net: use and abuse of spatial sampling data in detecting synchronization

PubMed Central

2017-01-01

Synchronization of population dynamics in different habitats is a frequently observed phenomenon. A common mathematical tool to reveal synchronization is the (cross)correlation coefficient between time courses of values of the population size of a given species where the population size is evaluated from spatial sampling data. The corresponding sampling net or grid is often coarse, i.e. it does not resolve all details of the spatial configuration, and the evaluation error—i.e. the difference between the true value of the population size and its estimated value—can be considerable. We show that this estimation error can make the value of the correlation coefficient very inaccurate or even irrelevant. We consider several population models to show that the value of the correlation coefficient calculated on a coarse sampling grid rarely exceeds 0.5, even if the true value is close to 1, so that the synchronization is effectively lost. We also observe ‘ghost synchronization’ when the correlation coefficient calculated on a coarse sampling grid is close to 1 but in reality the dynamics are not correlated. Finally, we suggest a simple test to check the sampling grid coarseness and hence to distinguish between the true and artifactual values of the correlation coefficient. PMID:28202589

A comparison of two indices for the intraclass correlation coefficient.

PubMed

Shieh, Gwowen

2012-12-01

In the present study, we examined the behavior of two indices for measuring the intraclass correlation in the one-way random effects model: the prevailing ICC(1) (Fisher, 1938) and the corrected eta-squared (Bliese & Halverson, 1998). These two procedures differ both in their methods of estimating the variance components that define the intraclass correlation coefficient and in their performance of bias and mean squared error in the estimation of the intraclass correlation coefficient. In contrast with the natural unbiased principle used to construct ICC(1), in the present study it was analytically shown that the corrected eta-squared estimator is identical to the maximum likelihood estimator and the pairwise estimator under equal group sizes. Moreover, the empirical results obtained from the present Monte Carlo simulation study across various group structures revealed the mutual dominance relationship between their truncated versions for negative values. The corrected eta-squared estimator performs better than the ICC(1) estimator when the underlying population intraclass correlation coefficient is small. Conversely, ICC(1) has a clear advantage over the corrected eta-squared for medium and large magnitudes of population intraclass correlation coefficient. The conceptual description and numerical investigation provide guidelines to help researchers choose between the two indices for more accurate reliability analysis in multilevel research.

Factors associated to clinical learning in nursing students in primary health care: an analytical cross-sectional study

PubMed Central

Serrano-Gallardo, Pilar; Martínez-Marcos, Mercedes; Espejo-Matorrales, Flora; Arakawa, Tiemi; Magnabosco, Gabriela Tavares; Pinto, Ione Carvalho

2016-01-01

ABSTRACT Objective: to identify the students' perception about the quality of clinical placements and asses the influence of the different tutoring processes in clinical learning. Methods: analytical cross-sectional study on second and third year nursing students (n=122) about clinical learning in primary health care. The Clinical Placement Evaluation Tool and a synthetic index of attitudes and skills were computed to give scores to the clinical learning (scale 0-10). Univariate, bivariate and multivariate (multiple linear regression) analyses were performed. Results: the response rate was 91.8%. The most commonly identified tutoring process was "preceptor-professor" (45.2%). The clinical placement was assessed as "optimal" by 55.1%, relationship with team-preceptor was considered good by 80.4% of the cases and the average grade for clinical learning was 7.89. The multiple linear regression model with more explanatory capacity included the variables "Academic year" (beta coefficient = 1.042 for third-year students), "Primary Health Care Area (PHC)" (beta coefficient = 0.308 for Area B) and "Clinical placement perception" (beta coefficient = - 0.204 for a suboptimal perception). Conclusions: timeframe within the academic program, location and clinical placement perception were associated with students' clinical learning. Students' perceptions of setting quality were positive and a good team-preceptor relationship is a matter of relevance. PMID:27627124

Prediction of mass transfer coefficient in rotating bed contactor (Higee) using artificial neural network

NASA Astrophysics Data System (ADS)

Saha, Dipendu

2009-02-01

The feasibility of drastically reducing the contactor size in mass transfer processes utilizing centrifugal field has generated a lot of interest in rotating packed bed (Higee). Various investigators have proposed correlations to predict mass transfer coefficients in Higee, but, none of the correlations was more than 20-30% accurate. In this work, artificial neural network (ANN) is employed for predicting mass transfer coefficient data. Results show that ANN provides better estimation of mass transfer coefficient with accuracy 5-15%.

Intraclass Correlation Coefficients in Hierarchical Design Studies with Discrete Response Variables: A Note on a Direct Interval Estimation Procedure

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.

2015-01-01

A latent variable modeling procedure that can be used to evaluate intraclass correlation coefficients in two-level settings with discrete response variables is discussed. The approach is readily applied when the purpose is to furnish confidence intervals at prespecified confidence levels for these coefficients in setups with binary or ordinal…

Precancerous esophageal epithelia are associated with significantly increased scattering coefficients

PubMed Central

Su, Jing-Wei; Lin, Yang-Hsien; Chiang, Chun-Ping; Lee, Jang-Ming; Hsieh, Chao-Mao; Hsieh, Min-Shu; Yang, Pei-Wen; Wang, Chen-Ping; Tseng, Ping-Huei; Lee, Yi-Chia; Sung, Kung-Bin

2015-01-01

The progression of epithelial precancers into cancer is accompanied by changes of tissue and cellular structures in the epithelium. Correlations between the structural changes and scattering coefficients of esophageal epithelia were investigated using quantitative phase images and the scattering-phase theorem. An ex vivo study of 14 patients demonstrated that the average scattering coefficient of precancerous epithelia was 37.8% higher than that of normal epithelia from the same patient. The scattering coefficients were highly correlated with morphological features including the cell density and the nuclear-to-cytoplasmic ratio. A high interpatient variability in scattering coefficients was observed and suggests identifying precancerous lesions based on the relative change in scattering coefficients. PMID:26504630

Comparison between uroflowmetry and sonouroflowmetry in recording of urinary flow in healthy men.

PubMed

Krhut, Jan; Gärtner, Marcel; Sýkora, Radek; Hurtík, Petr; Burda, Michal; Luňáček, Libor; Zvarová, Katarína; Zvara, Peter

2015-08-01

To evaluate the accuracy of sonouroflowmetry in recording urinary flow parameters and voided volume. A total of 25 healthy male volunteers (age 18-63 years) were included in the study. All participants were asked to carry out uroflowmetry synchronous with recording of the sound generated by the urine stream hitting the water level in the urine collection receptacle, using a dedicated cell phone. From 188 recordings, 34 were excluded, because of voided volume <150 mL or technical problems during recording. Sonouroflowmetry recording was visualized in a form of a trace, representing sound intensity over time. Subsequently, the matching datasets of uroflowmetry and sonouroflowmetry were compared with respect to flow time, voided volume, maximum flow rate and average flow rate. Pearson's correlation coefficient was used to compare parameters recorded by uroflowmetry with those calculated based on sonouroflowmetry recordings. The flow pattern recorded by sonouroflowmetry showed a good correlation with the uroflowmetry trace. A strong correlation (Pearson's correlation coefficient 0.87) was documented between uroflowmetry-recorded flow time and duration of the sound signal recorded with sonouroflowmetry. A moderate correlation was observed in voided volume (Pearson's correlation coefficient 0.68) and average flow rate (Pearson's correlation coefficient 0.57). A weak correlation (Pearson's correlation coefficient 0.38) between maximum flow rate recorded using uroflowmetry and sonouroflowmetry-recorded peak sound intensity was documented. The present study shows that the basic concept utilizing sound analysis for estimation of urinary flow parameters and voided volume is valid. However, further development of this technology and standardization of recording algorithm are required. © 2015 The Japanese Urological Association.

Combinatorial Algorithms for Portfolio Optimization Problems - Case of Risk Moderate Investor

NASA Astrophysics Data System (ADS)

Juarna, A.

2017-03-01

Portfolio optimization problem is a problem of finding optimal combination of n stocks from N ≥ n available stocks that gives maximal aggregate return and minimal aggregate risk. In this paper given N = 43 from the IDX (Indonesia Stock Exchange) group of the 45 most-traded stocks, known as the LQ45, with p = 24 data of monthly returns for each stock, spanned over interval 2013-2014. This problem actually is a combinatorial one where its algorithm is constructed based on two considerations: risk moderate type of investor and maximum allowed correlation coefficient between every two eligible stocks. The main outputs resulted from implementation of the algorithms is a multiple curve of three portfolio’s attributes, e.g. the size, the ratio of return to risk, and the percentage of negative correlation coefficient for every two chosen stocks, as function of maximum allowed correlation coefficient between each two stocks. The output curve shows that the portfolio contains three stocks with ratio of return to risk at 14.57 if the maximum allowed correlation coefficient between every two eligible stocks is negative and contains 19 stocks with maximum allowed correlation coefficient 0.17 to get maximum ratio of return to risk at 25.48.

AN EMPIRICAL INVESTIGATION OF THE EFFECTS OF NONNORMALITY UPON THE SAMPLING DISTRIBUTION OF THE PROJECT MOMENT CORRELATION COEFFICIENT.

ERIC Educational Resources Information Center

HJELM, HOWARD; NORRIS, RAYMOND C.

THE STUDY EMPIRICALLY DETERMINED THE EFFECTS OF NONNORMALITY UPON SOME SAMPLING DISTRIBUTIONS OF THE PRODUCT MOMENT CORRELATION COEFFICIENT (PMCC). SAMPLING DISTRIBUTIONS OF THE PMCC WERE OBTAINED BY DRAWING NUMEROUS SAMPLES FROM CONTROL AND EXPERIMENTAL POPULATIONS HAVING VARIOUS DEGREES OF NONNORMALITY AND BY CALCULATING CORRELATION COEFFICIENTS…

Gender and Age Analyses of NIRS/STAI Pearson Correlation Coefficients at Resting State.

PubMed

Matsumoto, T; Fuchita, Y; Ichikawa, K; Fukuda, Y; Takemura, N; Sakatani, K

2016-01-01

According to the valence asymmetry hypothesis, the left/right asymmetry of PFC activity is correlated with specific emotional responses to mental stress and personality traits. In a previous study we measured spontaneous oscillation of oxy-Hb concentrations in the bilateral PFC at rest in normal adults employing two-channel portable NIRS and computed the laterality index at rest (LIR). We investigated the Pearson correlation coefficient between the LIR and anxiety levels evaluated by the State-Trait Anxiety Inventory (STAI) test. We found that subjects with right-dominant activity at rest showed higher STAI scores, while those with left dominant oxy-Hb changes at rest showed lower STAI scores such that the Pearson correlation coefficient between LIR and STAI was positive. This study performed Bootstrap analysis on the data and showed the following statistics of the target correlation coefficient: mean=0.4925 and lower confidence limit=0.177 with confidence level 0.05. Using the KS-test, we demonstrated that the correlation did not depend on age, whereas it did depend on gender.

Relationships between menstrual and menopausal attitudes and associated demographic and health characteristics: the Hilo Women's Health Study.

PubMed

Morrison, Lynn A; Sievert, Lynnette L; Brown, Daniel E; Rahberg, Nichole; Reza, Angela

2010-07-01

The objective of this study was to examine the relation of menstrual attitudes to menopausal attitudes and the demographic and health characteristics associated with each. This cross-sectional study consisted of a randomly selected sample of 1,824 respondents aged 16 to 100 years in multi-ethnic Hilo, Hawai'i. Women completed questionnaires for demographic and health information, such as age, ethnicity, education, residency in Hawai'i, menopausal status, exercise, and attitudes toward menstruation and menopause. Women more often chose positive terms, such as "natural," to describe menstruation (60.8%) and menopause (59.4%). In bivariate analyses, post-menopausal women were significantly more likely to have positive menstrual and menopausal attitudes than pre-menopausal women. Factor analyses were used to cluster attitudes followed by linear regression to identify demographic characteristics associated with factor scores. Asian-American ethnicity, higher education, reporting more exercise, and growing up outside of Hawai'i were associated with positive menstrual attitudes. Higher education, older age, post-menopausal status, growing up outside of Hawai'i and having hot flashes were associated with positive menopausal attitudes. Bivariate correlation analyses suggested significant associations between factor scores for menstrual and menopausal attitudes. Both negative and positive menstrual attitudes were positively correlated with the anticipation of menopause, although negative attitudes toward menstruation were negatively correlated with menopause as a positive, natural life event. Demographic variables, specifically education and where one grows up, influenced women's attitudes toward menstruation and menopause and should be considered for inclusion in subsequent multi-ethnic studies. Further research is also warranted in assessing the relationship between menstrual and menopausal attitudes.

Spatial correlations of Diceroprocta apache and its host plants: Evidence for a negative impact from Tamarix invasion

USGS Publications Warehouse

Ellingson, A.R.; Andersen, D.C.

2002-01-01

1. The hypothesis that the habitat-scale spatial distribution of the, Apache cicada Diceroprocta apache Davis is unaffected by the presence of the invasive exotic saltcedar Tamarix ramosissima was tested using data from 205 1-m2 quadrats placed within the flood-plain of the Bill Williams River, Arizona, U.S.A. Spatial dependencies within and between cicada density and habitat variables were estimated using Moran's I and its bivariate analogue to discern patterns and associations at spatial scales from 1 to 30 m. 2. Apache cicadas were spatially aggregated in high-density clusters averaging 3m in diameter. A positive association between cicada density, estimated by exuvial density, and the per cent canopy cover of a native tree, Goodding's willow Salix gooddingii, was detected in a non-spatial correlation analysis. No non-spatial association between cicada density and saltcedar canopy cover was detected. 3. Tests for spatial cross-correlation using the bivariate IYZ indicated the presence of a broad-scale negative association between cicada density and saltcedar canopy cover. This result suggests that large continuous stands of saltcedar are associated with reduced cicada density. In contrast, positive associations detected at spatial scales larger than individual quadrats suggested a spill-over of high cicada density from areas featuring Goodding's willow canopy into surrounding saltcedar monoculture. 4. Taken together and considered in light of the Apache cicada's polyphagous habits, the observed spatial patterns suggest that broad-scale factors such as canopy heterogeneity affect cicada habitat use more than host plant selection. This has implications for management of lower Colorado River riparian woodlands to promote cicada presence and density through maintenance or creation of stands of native trees as well as manipulation of the characteristically dense and homogeneous saltcedar canopies.

Spatial correlations of Diceroprocta apache and its host plants: Evidence for a negative impact from Tamarix invasion

USGS Publications Warehouse

Ellingson, A.R.; Andersen, D.C.

2002-01-01

1. The hypothesis that the habitat-scale spatial distribution of the Apache cicada Diceroprocta apache Davis is unaffected by the presence of the invasive exotic saltcedar Tamarix ramosissima was tested using data from 205 1-m2 quadrats placed within the flood-plain of the Bill Williams River, Arizona, U.S.A. Spatial dependencies within and between cicada density and habitat variables were estimated using Moran's I and its bivariate analogue to discern patterns and associations at spatial scales from 1 to 30 m.2. Apache cicadas were spatially aggregated in high-density clusters averaging 3 m in diameter. A positive association between cicada density, estimated by exuvial density, and the per cent canopy cover of a native tree, Goodding's willow Salix gooddingii, was detected in a non-spatial correlation analysis. No non-spatial association between cicada density and saltcedar canopy cover was detected.3. Tests for spatial cross-correlation using the bivariate IYZ indicated the presence of a broad-scale negative association between cicada density and saltcedar canopy cover. This result suggests that large continuous stands of saltcedar are associated with reduced cicada density. In contrast, positive associations detected at spatial scales larger than individual quadrats suggested a spill-over of high cicada density from areas featuring Goodding's willow canopy into surrounding saltcedar monoculture.4. Taken together and considered in light of the Apache cicada's polyphagous habits, the observed spatial patterns suggest that broad-scale factors such as canopy heterogeneity affect cicada habitat use more than host plant selection. This has implications for management of lower Colorado River riparian woodlands to promote cicada presence and density through maintenance or creation of stands of native trees as well as manipulation of the characteristically dense and homogeneous saltcedar canopies.

Occlusal force is correlated with cognitive function directly as well as indirectly via food intake in community-dwelling older Japanese: From the SONIC study.

PubMed

Ikebe, Kazunori; Gondo, Yasuyuki; Kamide, Kei; Masui, Yukie; Ishizaki, Taturo; Arai, Yasumichi; Inagaki, Hiroki; Nakagawa, Takeshi; Kabayama, Mai; Ryuno, Hirochika; Okubo, Hitomi; Takeshita, Hajime; Inomata, Chisato; Kurushima, Yuko; Mihara, Yusuke; Hatta, Kohdai; Fukutake, Motoyoshi; Enoki, Kaori; Ogawa, Taiji; Matsuda, Ken-Ichi; Sugimoto, Ken; Oguro, Ryosuke; Takami, Yoichi; Itoh, Norihisa; Takeya, Yasushi; Yamamoto, Koichi; Rakugi, Hiromi; Murakami, Shinya; Kitamura, Masahiro; Maeda, Yoshinobu

2018-01-01

Growing evidence suggests that oral health may be an important factor associated with cognitive function in aged populations. However, many previous studies on this topic used insensitive oral indicators or did not include certain essential covariates. Thus, we examined the association between occlusal force and cognitive function in a large sample of older adults, controlling for dietary intake, vascular risk factors, inflammatory biomarkers, depression, and genetic factors. In this cross-sectional study of older community-dwelling Japanese adults, we examined data collected from 994 persons aged 70 years and 968 persons aged 80 years. Cognitive function was measured using the Japanese version of the Montreal Cognitive Assessment (MoCA-J). Oral status and function were evaluated according to the number of remaining teeth, periodontal pocket depth, and maximal occlusal force. Associations between MoCA-J scores and occlusal force were investigated via bivariate and multivariate analyses. Education level, financial status, depression score, and intake of green and yellow vegetables, as well as number of teeth and occlusal force, were significantly correlated with MoCA-J scores in both age groups. Among individuals aged 80 years, CRP and periodontal status were weakly but significantly associated with MoCA-J score. After controlling for all significant variables via bivariate analyses, the correlation between maximal occlusal force and cognitive function persisted. A path analysis confirmed the hypothesis that cognitive function is associated with occlusal force directly as well as indirectly via food intake. After controlling for possible factors, maximal occlusal force was positively associated with cognitive function directly as well as indirectly through dietary intake.

Using bivariate signal analysis to characterize the epileptic focus: the benefit of surrogates.

PubMed

Andrzejak, R G; Chicharro, D; Lehnertz, K; Mormann, F

2011-04-01

The disease epilepsy is related to hypersynchronous activity of networks of neurons. While acute epileptic seizures are the most extreme manifestation of this hypersynchronous activity, an elevated level of interdependence of neuronal dynamics is thought to persist also during the seizure-free interval. In multichannel recordings from brain areas involved in the epileptic process, this interdependence can be reflected in an increased linear cross correlation but also in signal properties of higher order. Bivariate time series analysis comprises a variety of approaches, each with different degrees of sensitivity and specificity for interdependencies reflected in lower- or higher-order properties of pairs of simultaneously recorded signals. Here we investigate which approach is best suited to detect putatively elevated interdependence levels in signals recorded from brain areas involved in the epileptic process. For this purpose, we use the linear cross correlation that is sensitive to lower-order signatures of interdependence, a nonlinear interdependence measure that integrates both lower- and higher-order properties, and a surrogate-corrected nonlinear interdependence measure that aims to specifically characterize higher-order properties. We analyze intracranial electroencephalographic recordings of the seizure-free interval from 29 patients with an epileptic focus located in the medial temporal lobe. Our results show that all three approaches detect higher levels of interdependence for signals recorded from the brain hemisphere containing the epileptic focus as compared to signals recorded from the opposite hemisphere. For the linear cross correlation, however, these differences are not significant. For the nonlinear interdependence measure, results are significant but only of moderate accuracy with regard to the discriminative power for the focal and nonfocal hemispheres. The highest significance and accuracy is obtained for the surrogate-corrected nonlinear interdependence measure.

Determinants of job satisfaction for novice nurse managers employed in hospitals.

PubMed

Djukic, Maja; Jun, Jin; Kovner, Christine; Brewer, Carol; Fletcher, Jason

Numbering close to 300,000 nurse managers represent the largest segment of the health care management workforce. Their effectiveness is, in part, influenced by their job satisfaction. We examined factors associated with job satisfaction of novice frontline nurse managers. We used a cross-sectional, correlational survey design. The sample consisted of responders to the fifth wave of a multiyear study of new nurses in 2013 (N = 1,392; response rate of 69%) who reported working as managers (n = 209). The parent study sample consisted of registered nurses who were licensed for the first time by exam 6-18 months prior in 1 of 51 selected metropolitan statistical areas and 9 rural areas across 34 U.S. states and the District of Columbia. We examined bivariate correlations between job satisfaction and 31 personal and structural variables. All variables significantly related to job satisfaction in bivariate analysis were included in a multivariate linear regression model. In addition, we tested the interaction effects of procedural justice and negative affectivity, autonomy, and organizational constraints on job satisfaction. The Cronbach's alphas for all multi-item scales ranged from .74 to .96. In the multivariate analysis, negative affectivity (β = -.169; p = .006) and procedural justice (β = .210; p = .016) were significantly correlated with job satisfaction. The combination of predictors in the model accounted for half of the variability in job satisfaction ratings (R = .51, adjusted R = .47; p <. 001). Health care executives who want to cultivate an effective novice frontline nurse manager workforce can best ensure their satisfaction by creating an organization with strong procedural justice. This could be achieved by involving managers in decision-making processes and ensuring transparency about how decisions that affect nursing are made.

Using bivariate signal analysis to characterize the epileptic focus: The benefit of surrogates

NASA Astrophysics Data System (ADS)

Andrzejak, R. G.; Chicharro, D.; Lehnertz, K.; Mormann, F.

2011-04-01

The disease epilepsy is related to hypersynchronous activity of networks of neurons. While acute epileptic seizures are the most extreme manifestation of this hypersynchronous activity, an elevated level of interdependence of neuronal dynamics is thought to persist also during the seizure-free interval. In multichannel recordings from brain areas involved in the epileptic process, this interdependence can be reflected in an increased linear cross correlation but also in signal properties of higher order. Bivariate time series analysis comprises a variety of approaches, each with different degrees of sensitivity and specificity for interdependencies reflected in lower- or higher-order properties of pairs of simultaneously recorded signals. Here we investigate which approach is best suited to detect putatively elevated interdependence levels in signals recorded from brain areas involved in the epileptic process. For this purpose, we use the linear cross correlation that is sensitive to lower-order signatures of interdependence, a nonlinear interdependence measure that integrates both lower- and higher-order properties, and a surrogate-corrected nonlinear interdependence measure that aims to specifically characterize higher-order properties. We analyze intracranial electroencephalographic recordings of the seizure-free interval from 29 patients with an epileptic focus located in the medial temporal lobe. Our results show that all three approaches detect higher levels of interdependence for signals recorded from the brain hemisphere containing the epileptic focus as compared to signals recorded from the opposite hemisphere. For the linear cross correlation, however, these differences are not significant. For the nonlinear interdependence measure, results are significant but only of moderate accuracy with regard to the discriminative power for the focal and nonfocal hemispheres. The highest significance and accuracy is obtained for the surrogate-corrected nonlinear interdependence measure.

Relationships between menstrual and menopausal attitudes and associated demographic and health characteristics: The Hilo Women’s Health Study

PubMed Central

Sievert, Lynnette L.; Brown, Daniel E.; Rahberg, Nichole; Reza, Angela

2010-01-01

The objective of this study was to examine the relation of menstrual attitudes to menopausal attitudes and the demographic and health characteristics associated with each. This cross-sectional study consisted of a randomly selected sample of 1824 respondents aged 16 to 100 years in multi-ethnic Hilo, Hawai`i. Women completed questionnaires for demographic and health information, such as age, ethnicity, education, residency in Hawai`i, menopausal status, exercise, and attitudes toward menstruation and menopause. Women more often chose positive terms, such as “natural,” to describe menstruation (60.8%) and menopause (59.4%). In bivariate analyses, post-menopausal women were significantly more likely to have positive menstrual and menopausal attitudes than pre-menopausal women. Factor analyses were used to cluster attitudes followed by linear regression to identify demographic characteristics associated with factor scores. Asian-American ethnicity, higher education, reporting more exercise, and growing up outside of Hawai`i were associated with positive menstrual attitudes. Higher education, older age, post-menopausal status, growing up outside of Hawai`i and having hot flashes were associated with positive menopausal attitudes. Bivariate correlation analyses suggested significant associations between factor scores for menstrual and menopausal attitudes. Both negative and positive menstrual attitudes were positively correlated with the anticipation of menopause, although negative attitudes toward menstruation were negatively correlated with menopause as a positive, natural life event. Demographic variables, specifically education and where one grows up, influenced women’s attitudes toward menstruation and menopause and should be considered for inclusion in subsequent multi-ethnic studies. Further research is also warranted in assessing the relationship between menstrual and menopausal attitudes. PMID:20853216

Nuclear anxiety: a test-construction study

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

Braunstein, A.L.

1986-01-01

The Nuclear Anxiety Scale was administered to 263 undergraduate and graduate studies (on eight occasions in December, 1985 and January, 1986). (1) The obtained alpha coefficient was .91. This was significant at the .01 level, and demonstrated that the scale was internally homogeneous and consistent. (2) Item discrimination indices (point biserial correlation coefficients) computered for the thirty (30) items yielded a range of .25 to .64. All coefficients were significant at the .01 level, and all 30 items were retained as demonstrating significant discriminability. (3) The correlation between two administrations of the scale (with a 48-hour interval) was .83. Thismore » was significant at the .01 level, and demonstrated test-retest reliability and stability over time. (4) The point-biserial correlation coefficient between scores on the Nuclear Anxiety Scale, and the students' self-report of nuclear anxiety as being either a high or low ranked stressor, was .59. This was significant at the .01 level, and demonstrated concurrent validity. (5) The correlation coefficient between scores on the Nuclear Anxiety Scale and the Spielberger State-Trait Anxiety Inventory, A-Trait, (1970), was .41. This was significant at the .01 level, and demonstrated convergent validity. (6) The correlation coefficient between positively stated and negatively stated items (with scoring reversed) was .76. This was significant at the .01 level, and demonstrated freedom from response set bias.« less

Channel correlation and BER performance analysis of coherent optical communication systems with receive diversity over moderate-to-strong non-Kolmogorov turbulence.

PubMed

Fu, Yulong; Ma, Jing; Tan, Liying; Yu, Siyuan; Lu, Gaoyuan

2018-04-10

In this paper, new expressions of the channel-correlation coefficient and its components (the large- and small-scale channel-correlation coefficients) for a plane wave are derived for a horizontal link in moderate-to-strong non-Kolmogorov turbulence using a generalized effective atmospheric spectrum which includes finite-turbulence inner and outer scales and high-wave-number "bump". The closed-form expression of the average bit error rate (BER) of the coherent free-space optical communication system is derived using the derived channel-correlation coefficients and an α-μ distribution to approximate the sum of the square root of arbitrarily correlated Gamma-Gamma random variables. Analytical results are provided to investigate the channel correlation and evaluate the average BER performance. The validity of the proposed approximation is illustrated by Monte Carlo simulations. This work will help with further investigation of the fading correlation in spatial diversity systems.

Technical characterization of dialysis fluid flow and mass transfer rate in dialyzers with various filtration coefficients using dimensionless correlation equation.

PubMed

Fukuda, Makoto; Yoshimura, Kengo; Namekawa, Koki; Sakai, Kiyotaka

2017-06-01

The objective of the present study is to evaluate the effect of filtration coefficient and internal filtration on dialysis fluid flow and mass transfer coefficient in dialyzers using dimensionless mass transfer correlation equations. Aqueous solution of vitamin B 12 clearances were obtained for REXEED-15L as a low flux dialyzer, and APS-15EA and APS-15UA as high flux dialyzers. All the other design specifications were identical for these dialyzers except for filtration coefficient. The overall mass transfer coefficient was calculated, moreover, the exponents of Reynolds number (Re) and film mass transfer coefficient of the dialysis-side fluid (k D ) for each flow rate were derived from the Wilson plot and dimensionless correlation equation. The exponents of Re were 0.4 for the low flux dialyzer whereas 0.5 for the high flux dialyzers. Dialysis fluid of the low flux dialyzer was close to laminar flow because of its low filtration coefficient. On the other hand, dialysis fluid of the high flux dialyzers was assumed to be orthogonal flow. Higher filtration coefficient was associated with higher k D influenced by mass transfer rate through diffusion and internal filtration. Higher filtration coefficient of dialyzers and internal filtration affect orthogonal flow of dialysis fluid.

Influences of sampling size and pattern on the uncertainty of correlation estimation between soil water content and its influencing factors

NASA Astrophysics Data System (ADS)

Lai, Xiaoming; Zhu, Qing; Zhou, Zhiwen; Liao, Kaihua

2017-12-01

In this study, seven random combination sampling strategies were applied to investigate the uncertainties in estimating the hillslope mean soil water content (SWC) and correlation coefficients between the SWC and soil/terrain properties on a tea + bamboo hillslope. One of the sampling strategies is the global random sampling and the other six are the stratified random sampling on the top, middle, toe, top + mid, top + toe and mid + toe slope positions. When each sampling strategy was applied, sample sizes were gradually reduced and each sampling size contained 3000 replicates. Under each sampling size of each sampling strategy, the relative errors (REs) and coefficients of variation (CVs) of the estimated hillslope mean SWC and correlation coefficients between the SWC and soil/terrain properties were calculated to quantify the accuracy and uncertainty. The results showed that the uncertainty of the estimations decreased as the sampling size increasing. However, larger sample sizes were required to reduce the uncertainty in correlation coefficient estimation than in hillslope mean SWC estimation. Under global random sampling, 12 randomly sampled sites on this hillslope were adequate to estimate the hillslope mean SWC with RE and CV ≤10%. However, at least 72 randomly sampled sites were needed to ensure the estimated correlation coefficients with REs and CVs ≤10%. Comparing with all sampling strategies, reducing sampling sites on the middle slope had the least influence on the estimation of hillslope mean SWC and correlation coefficients. Under this strategy, 60 sites (10 on the middle slope and 50 on the top and toe slopes) were enough to ensure the estimated correlation coefficients with REs and CVs ≤10%. This suggested that when designing the SWC sampling, the proportion of sites on the middle slope can be reduced to 16.7% of the total number of sites. Findings of this study will be useful for the optimal SWC sampling design.

Variable-Domain Functional Regression for Modeling ICU Data.

PubMed

Gellar, Jonathan E; Colantuoni, Elizabeth; Needham, Dale M; Crainiceanu, Ciprian M

2014-12-01

We introduce a class of scalar-on-function regression models with subject-specific functional predictor domains. The fundamental idea is to consider a bivariate functional parameter that depends both on the functional argument and on the width of the functional predictor domain. Both parametric and nonparametric models are introduced to fit the functional coefficient. The nonparametric model is theoretically and practically invariant to functional support transformation, or support registration. Methods were motivated by and applied to a study of association between daily measures of the Intensive Care Unit (ICU) Sequential Organ Failure Assessment (SOFA) score and two outcomes: in-hospital mortality, and physical impairment at hospital discharge among survivors. Methods are generally applicable to a large number of new studies that record a continuous variables over unequal domains.

Improving runoff risk estimates: Formulating runoff as a bivariate process using the SCS curve number method

NASA Astrophysics Data System (ADS)

Shaw, Stephen B.; Walter, M. Todd

2009-03-01

The Soil Conservation Service curve number (SCS-CN) method is widely used to predict storm runoff for hydraulic design purposes, such as sizing culverts and detention basins. As traditionally used, the probability of calculated runoff is equated to the probability of the causative rainfall event, an assumption that fails to account for the influence of variations in soil moisture on runoff generation. We propose a modification to the SCS-CN method that explicitly incorporates rainfall return periods and the frequency of different soil moisture states to quantify storm runoff risks. Soil moisture status is assumed to be correlated to stream base flow. Fundamentally, this approach treats runoff as the outcome of a bivariate process instead of dictating a 1:1 relationship between causative rainfall and resulting runoff volumes. Using data from the Fall Creek watershed in western New York and the headwaters of the French Broad River in the mountains of North Carolina, we show that our modified SCS-CN method improves frequency discharge predictions in medium-sized watersheds in the eastern United States in comparison to the traditional application of the method.

Anodic microbial community diversity as a predictor of the power output of microbial fuel cells.

PubMed

Stratford, James P; Beecroft, Nelli J; Slade, Robert C T; Grüning, André; Avignone-Rossa, Claudio

2014-03-01

The relationship between the diversity of mixed-species microbial consortia and their electrogenic potential in the anodes of microbial fuel cells was examined using different diversity measures as predictors. Identical microbial fuel cells were sampled at multiple time-points. Biofilm and suspension communities were analysed by denaturing gradient gel electrophoresis to calculate the number and relative abundance of species. Shannon and Simpson indices and richness were examined for association with power using bivariate and multiple linear regression, with biofilm DNA as an additional variable. In simple bivariate regressions, the correlation of Shannon diversity of the biofilm and power is stronger (r=0.65, p=0.001) than between power and richness (r=0.39, p=0.076), or between power and the Simpson index (r=0.5, p=0.018). Using Shannon diversity and biofilm DNA as predictors of power, a regression model can be constructed (r=0.73, p<0.001). Ecological parameters such as the Shannon index are predictive of the electrogenic potential of microbial communities. Copyright © 2014 Elsevier Ltd. All rights reserved.

NT-pro-BNP levels in patients with acute pulmonary embolism are correlated to right but not left ventricular volume and function.

PubMed

Pasha, Sharif M; Klok, Frederikus A; van der Bijl, Noortje; de Roos, Albert; Kroft, Lucia J M; Huisman, Menno V

2012-08-01

N-terminal pro-Brain Natriuretic Peptide (NT-pro-BNP) is primarily secreted by left ventricular (LV) stretch and wall tension. Notably, NT-pro-BNP is a prognostic marker in acute pulmonary embolism (PE), which primarily stresses the right ventricle (RV). We sought to evaluate the relative contribution of the RV to NT-pro-BNP levels during PE. A post-hoc analysis of an observational prospective outcome study in 113 consecutive patients with computed tomography (CT)-proven PE and 226 patients in whom PE was clinically suspected but ruled out by CT. In all patients RV and LV function was established by assessing ECG-triggered-CT measured ventricular end-diastolic-volumes and ejection fraction (EF). NT-pro-BNP was assessed in all patients. The correlation between RV and LV end-diastolic-volumes and systolic function was evaluated by multiple linear regression corrected for known confounders. In the PE cohort increased RVEF (β-coefficient (95% confidence interval [CI]) -0.044 (± -0.011); p<0.001) and higher RV end-diastolic-volume (β-coefficient 0.005 (± 0.001); p<0.001) were significantly correlated to NT-pro-BNP, while no correlation was found with LVEF (β-coefficient 0.005 (± 0.010); p=0.587) and LV end-diastolic-volume (β-coefficient -0.003 (± 0.002); p=0.074). In control patients without PE we found a strong correlation between NT-pro-BNP levels and LVEF (β-coefficient -0.027 (± -0.006); p<0.001) although not LV end-diastolic-volume (β-coefficient 0.001 (± 0.001); p=0.418). RVEF (β-coefficient -0.002 (± -0.006); p=0.802) and RV end-diastolic-volume (β-coefficient <0.001 (± 0.001); p=0.730) were not correlated in patients without PE. In PE patients, lower RVEF and higher RV end-diastolic-volume were significantly correlated to NT-pro-BNP levels as compared to control patients without PE. These observations provide pathophysiological ground for the well-known prognostic value of NT-pro-BNP in acute PE.

Simple and Multivariate Relationships Between Spiritual Intelligence with General Health and Happiness.

PubMed

Amirian, Mohammad-Elyas; Fazilat-Pour, Masoud

2016-08-01

The present study examined simple and multivariate relationships of spiritual intelligence with general health and happiness. The employed method was descriptive and correlational. King's Spiritual Quotient scales, GHQ-28 and Oxford Happiness Inventory, are filled out by a sample consisted of 384 students, which were selected using stratified random sampling from the students of Shahid Bahonar University of Kerman. Data are subjected to descriptive and inferential statistics including correlations and multivariate regressions. Bivariate correlations support positive and significant predictive value of spiritual intelligence toward general health and happiness. Further analysis showed that among the Spiritual Intelligence' subscales, Existential Critical Thinking Predicted General Health and Happiness, reversely. In addition, happiness was positively predicted by generation of personal meaning and transcendental awareness. The findings are discussed in line with the previous studies and the relevant theoretical background.

Quantitative analysis of spatial variability of geotechnical parameters

NASA Astrophysics Data System (ADS)

Fang, Xing

2018-04-01

Geotechnical parameters are the basic parameters of geotechnical engineering design, while the geotechnical parameters have strong regional characteristics. At the same time, the spatial variability of geotechnical parameters has been recognized. It is gradually introduced into the reliability analysis of geotechnical engineering. Based on the statistical theory of geostatistical spatial information, the spatial variability of geotechnical parameters is quantitatively analyzed. At the same time, the evaluation of geotechnical parameters and the correlation coefficient between geotechnical parameters are calculated. A residential district of Tianjin Survey Institute was selected as the research object. There are 68 boreholes in this area and 9 layers of mechanical stratification. The parameters are water content, natural gravity, void ratio, liquid limit, plasticity index, liquidity index, compressibility coefficient, compressive modulus, internal friction angle, cohesion and SP index. According to the principle of statistical correlation, the correlation coefficient of geotechnical parameters is calculated. According to the correlation coefficient, the law of geotechnical parameters is obtained.

Historical and future drought in Bangladesh using copula-based bivariate regional frequency analysis

NASA Astrophysics Data System (ADS)

Mortuza, Md Rubayet; Moges, Edom; Demissie, Yonas; Li, Hong-Yi

2018-02-01

The study aims at regional and probabilistic evaluation of bivariate drought characteristics to assess both the past and future drought duration and severity in Bangladesh. The procedures involve applying (1) standardized precipitation index to identify drought duration and severity, (2) regional frequency analysis to determine the appropriate marginal distributions for both duration and severity, (3) copula model to estimate the joint probability distribution of drought duration and severity, and (4) precipitation projections from multiple climate models to assess future drought trends. Since drought duration and severity in Bangladesh are often strongly correlated and do not follow same marginal distributions, the joint and conditional return periods of droughts are characterized using the copula-based joint distribution. The country is divided into three homogeneous regions using Fuzzy clustering and multivariate discordancy and homogeneity measures. For given severity and duration values, the joint return periods for a drought to exceed both values are on average 45% larger, while to exceed either value are 40% less than the return periods from the univariate frequency analysis, which treats drought duration and severity independently. These suggest that compared to the bivariate drought frequency analysis, the standard univariate frequency analysis under/overestimate the frequency and severity of droughts depending on how their duration and severity are related. Overall, more frequent and severe droughts are observed in the west side of the country. Future drought trend based on four climate models and two scenarios showed the possibility of less frequent drought in the future (2020-2100) than in the past (1961-2010).

Genetic parameters of legendre polynomials for first parity lactation curves.

PubMed

Pool, M H; Janss, L L; Meuwissen, T H

2000-11-01

Variance components of the covariance function coefficients in a random regression test-day model were estimated by Legendre polynomials up to a fifth order for first-parity records of Dutch dairy cows using Gibbs sampling. Two Legendre polynomials of equal order were used to model the random part of the lactation curve, one for the genetic component and one for permanent environment. Test-day records from cows registered between 1990 to 1996 and collected by regular milk recording were available. For the data set, 23,700 complete lactations were selected from 475 herds sired by 262 sires. Because the application of a random regression model is limited by computing capacity, we investigated the minimum order needed to fit the variance structure in the data sufficiently. Predictions of genetic and permanent environmental variance structures were compared with bivariate estimates on 30-d intervals. A third-order or higher polynomial modeled the shape of variance curves over DIM with sufficient accuracy for the genetic and permanent environment part. Also, the genetic correlation structure was fitted with sufficient accuracy by a third-order polynomial, but, for the permanent environmental component, a fourth order was needed. Because equal orders are suggested in the literature, a fourth-order Legendre polynomial is recommended in this study. However, a rank of three for the genetic covariance matrix and of four for permanent environment allows a simpler covariance function with a reduced number of parameters based on the eigenvalues and eigenvectors.

Relationships among depression during pregnancy, social support and health locus of control among Iranian pregnant women.

PubMed

Moshki, Mahdi; Cheravi, Khadijeh

2016-03-01

Prenatal depression is a significant predictor of postpartum depression and is detrimental to fetal development. To examine whether depression during pregnancy is associated with social support and health locus of control (HLC). Data were collected from a sample of 208 Iranian pregnant women using a demographic questionnaire, the Edinburgh Postnatal Depression Scale, the multidimensional HLC Scale and the social support appraisals. Depression was experienced by 37% of participants. Overall, women reported higher level of family support (6.88 ± 1.15) than other supports (6.87 ± 1.29). Protective supports from other resources (6.87 ± 1.29) were higher than those from friends (5.94 ± 1.5). Internal, powerful others and chance beliefs had the highest mean scores. Social support and chance HLC significantly influenced the proposed mediator (depressive mood) in the linear regression model. Bivariate analysis showed significant associations between social support (friend, family and others) and depressive mood. Internal HLC had a significant association with social support and powerful others HLC. However, Pearson correlation coefficient was not significant between depressive mood and all dimensions of HLC. Clinicians could assess social support and chance HLC to identify and treat women at risk of prenatal depression. By providing support during pregnancy, depression levels in women and its effects on the fetus may be decreased, which could prevent postpartum depression. © The Author(s) 2015.

MJO prediction skill of the subseasonal-to-seasonal (S2S) prediction models

NASA Astrophysics Data System (ADS)

Son, S. W.; Lim, Y.; Kim, D.

2017-12-01

The Madden-Julian Oscillation (MJO), the dominant mode of tropical intraseasonal variability, provides the primary source of tropical and extratropical predictability on subseasonal to seasonal timescales. To better understand its predictability, this study conducts quantitative evaluation of MJO prediction skill in the state-of-the-art operational models participating in the subseasonal-to-seasonal (S2S) prediction project. Based on bivariate correlation coefficient of 0.5, the S2S models exhibit MJO prediction skill ranging from 12 to 36 days. These prediction skills are affected by both the MJO amplitude and phase errors, the latter becoming more important with forecast lead times. Consistent with previous studies, the MJO events with stronger initial amplitude are typically better predicted. However, essentially no sensitivity to the initial MJO phase is observed. Overall MJO prediction skill and its inter-model spread are further related with the model mean biases in moisture fields and longwave cloud-radiation feedbacks. In most models, a dry bias quickly builds up in the deep tropics, especially across the Maritime Continent, weakening horizontal moisture gradient. This likely dampens the organization and propagation of MJO. Most S2S models also underestimate the longwave cloud-radiation feedbacks in the tropics, which may affect the maintenance of the MJO convective envelop. In general, the models with a smaller bias in horizontal moisture gradient and longwave cloud-radiation feedbacks show a higher MJO prediction skill, suggesting that improving those processes would enhance MJO prediction skill.

Determination of apalcillin and its metabolites in human body fluids by high-pressure liquid chromatography.

PubMed Central

Borner, K; Lode, H; Elvers, A

1982-01-01

We describe two methods for the quantitative analysis of apalcillin and its metabolites in serum and urine by reverse-phase high-pressure liquid chromatography (HPLC), a fast isocratic method for the parent drug, and a gradient method that allows the simultaneous assay of two metabolites. Serum was deproteinized with acetonitrile, and urine was diluted with buffer solution. The detection limit was about 0.5 micrograms/ml at a detection wavelength of 254 nm and 1.5 micrograms/ml at 310 nm. Within-batch precision (coefficient of variation) varied from 10.2 to 1.1% for concentrations of 7.8 and 185.3 micrograms/ml of serum, respectively. Recovery rates of 95.1 and 97.7% were found in spiked sera. Results obtained by HPLC correlated well with those from a standard microbiological assay (agar diffusion test); the resulting bivariate regression equation for serum was y-bioassay = 2.5 micrograms/ml + 0.992 X xHPLC, and that for urine was ybioassay = 12.0 micrograms/ml + 1.009 X xHPLC. At a detection wavelength of 315 nm, no interferences were observed in 10 healthy volunteers. Healthy subjects who were given 2 g of apalcillin intravenously excreted 18% of the parent drug within 24 h in the urine. Two inactive compounds were furthermore identified in urine as the isomeric forms of the penicilloic acids. Their excretion within 24 h amounted to 6.9 and 11.2% of the dose. PMID:6818901

Some correlations between sugar maple tree characteristics and sap and sugar yields

Treesearch

Barton M. Blum

1971-01-01

Simple correlation coefficients between various characteristics of sugar maple trees and sap sugar concentration, sap volume yield, and total sugar production are given for the 1968 sap season. Correlation coefficients in general indicated that individual tree characteristics that express tree and crown size are significantly related to sap volume yield and total sugar...

Reducing Bias and Error in the Correlation Coefficient Due to Nonnormality

ERIC Educational Resources Information Center

Bishara, Anthony J.; Hittner, James B.

2015-01-01

It is more common for educational and psychological data to be nonnormal than to be approximately normal. This tendency may lead to bias and error in point estimates of the Pearson correlation coefficient. In a series of Monte Carlo simulations, the Pearson correlation was examined under conditions of normal and nonnormal data, and it was compared…

Relationship of body mass index to percent body fat and waist circumference among schoolchildren in Japan - the influence of gender and obesity: a population-based cross-sectional study

PubMed Central

2010-01-01

Background Although the correlation coefficient between body mass index (BMI) and percent body fat (%BF) or waist circumference (WC) has been reported, studies conducted among population-based schoolchildren to date have been limited in Japan, where %BF and WC are not usually measured in annual health examinations at elementary schools or junior high schools. The aim of the present study was to investigate the relationship of BMI to %BF and WC and to examine the influence of gender and obesity on these relationships among Japanese schoolchildren. Methods Subjects included 3,750 schoolchildren from the fourth and seventh grade in Ina-town, Saitama Prefecture, Japan between 2004 and 2008. Information about subject's age, sex, height, weight, %BF, and WC was collected from annual physical examinations. %BF was measured with a bipedal biometrical impedance analysis device. Obesity was defined by the following two criteria: the obese definition of the Centers for Disease Control and Prevention, and the definition of obesity for Japanese children. Pearson's correlation coefficients between BMI and %BF or WC were calculated separately for sex. Results Among fourth graders, the correlation coefficients between BMI and %BF were 0.74 for boys and 0.97 for girls, whereas those between BMI and WC were 0.94 for boys and 0.90 for girls. Similar results were observed in the analysis of seventh graders. The correlation coefficient between BMI and %BF varied by physique (obese or non-obese), with weaker correlations among the obese regardless of the definition of obesity; most correlation coefficients among obese boys were less than 0.5, whereas most correlations among obese girls were more than 0.7. On the other hand, the correlation coefficients between BMI and WC were more than 0.8 among boys and almost all coefficients were more than 0.7 among girls, regardless of physique. Conclusions BMI was positively correlated with %BF and WC among Japanese schoolchildren. The correlations could be influenced by obesity as well as by gender. Accordingly, it is essential to consider gender and obesity when using BMI as a surrogate for %BF and WC for epidemiological use. PMID:20716379

Zero Pearson coefficient for strongly correlated growing trees

NASA Astrophysics Data System (ADS)

Dorogovtsev, S. N.; Ferreira, A. L.; Goltsev, A. V.; Mendes, J. F. F.

2010-03-01

We obtained Pearson’s coefficient of strongly correlated recursive networks growing by preferential attachment of every new vertex by m edges. We found that the Pearson coefficient is exactly zero in the infinite network limit for the recursive trees (m=1) . If the number of connections of new vertices exceeds one (m>1) , then the Pearson coefficient in the infinite networks equals zero only when the degree distribution exponent γ does not exceed 4. We calculated the Pearson coefficient for finite networks and observed a slow power-law-like approach to an infinite network limit. Our findings indicate that Pearson’s coefficient strongly depends on size and details of networks, which makes this characteristic virtually useless for quantitative comparison of different networks.

Zero Pearson coefficient for strongly correlated growing trees.

PubMed

Dorogovtsev, S N; Ferreira, A L; Goltsev, A V; Mendes, J F F

2010-03-01

We obtained Pearson's coefficient of strongly correlated recursive networks growing by preferential attachment of every new vertex by m edges. We found that the Pearson coefficient is exactly zero in the infinite network limit for the recursive trees (m=1). If the number of connections of new vertices exceeds one (m>1), then the Pearson coefficient in the infinite networks equals zero only when the degree distribution exponent gamma does not exceed 4. We calculated the Pearson coefficient for finite networks and observed a slow power-law-like approach to an infinite network limit. Our findings indicate that Pearson's coefficient strongly depends on size and details of networks, which makes this characteristic virtually useless for quantitative comparison of different networks.

Determining Sample Size for Accurate Estimation of the Squared Multiple Correlation Coefficient.

ERIC Educational Resources Information Center

Algina, James; Olejnik, Stephen

2000-01-01

Discusses determining sample size for estimation of the squared multiple correlation coefficient and presents regression equations that permit determination of the sample size for estimating this parameter for up to 20 predictor variables. (SLD)

Effect of degree correlations above the first shell on the percolation transition

NASA Astrophysics Data System (ADS)

Valdez, L. D.; Buono, C.; Braunstein, L. A.; Macri, P. A.

2011-11-01

The use of degree-degree correlations to model realistic networks which are characterized by their Pearson's coefficient, has become widespread. However the effect on how different correlation algorithms produce different results on processes on top of them, has not yet been discussed. In this letter, using different correlation algorithms to generate assortative networks, we show that for very assortative networks the behavior of the main observables in percolation processes depends on the algorithm used to build the network. The different alghoritms used here introduce different inner structures that are missed in Pearson's coefficient. We explain the different behaviors through a generalization of Pearson's coefficient that allows to study the correlations at chemical distances l from a root node. We apply our findings to real networks.

Evaluation of generalized heat-transfer coefficients in pilot AFBC units

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

Grewal, N.S.

Experimental data for heat transfer rates as obtained in a 0.209m/sup 2/ AFBC unit at the GFETC is examined in the light of the existing four correlations for heat transfer coefficient between an immersed staggered array of horizontal tubes and a gas-solid fluidized bed. The predicted values of heat transfer coefficient from the correlations proposed by Grewal and Bansal are found to be in good agreement with the experimental values of heat transfer coefficient when the contribution due to radiation is also included.

Evaluation of generalized heat transfer coefficients in pilot AFBC units

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

Grewal, N.S.

Experimental data for heat transfer rates as obtained in a 0.209m/sup 2/ AFBC unit at the GFETC is examined in the light of the existing four correlations for heat transfer coefficient between an immersed staggered array of horizontal tubes and a gas-solid fluidized bed. The predicted values of heat transfer coefficient from the correlations proposed by Grewal and Bansal are found to be in good agreement with the experimental values of heat transfer coefficient when the contribution due to radiation is also included.

Variability in the Correlation between Asian Dust Storms and Chlorophyll a Concentration from the North to Equatorial Pacific

PubMed Central

Tan, Sai-Chun; Yao, Xiaohong; Gao, Hui-Wang; Shi, Guang-Yu; Yue, Xu

2013-01-01

A long-term record of Asian dust storms showed seven high-occurrence-frequency centers in China. The intrusion of Asian dust into the downwind seas, including the China seas, the Sea of Japan, the subarctic North Pacific, the North Pacific subtropical gyre, and the western and eastern Equatorial Pacific, has been shown to add nutrients to ocean ecosystems and enhance their biological activities. To explore the relationship between the transported dust from various sources to the six seas and oceanic biological activities with different nutrient conditions, the correlation between monthly chlorophyll a concentration in each sea and monthly dust storm occurrence frequencies reaching the sea during 1997–2007 was examined in this study. No correlations were observed between dust and chlorophyll a concentration in the <50 m China seas because atmospheric deposition is commonly believed to exert less impact on coastal seas. Significant correlations existed between dust sources and many sea areas, suggesting a link between dust and chlorophyll a concentration in those seas. However, the correlation coefficients were highly variable. In general, the correlation coefficients (0.54–0.63) for the Sea of Japan were highest, except for that between the subarctic Pacific and the Taklimakan Desert, where it was as high as 0.7. For the >50 m China seas and the North Pacific subtropical gyre, the correlation coefficients were in the range 0.32–0.57. The correlation coefficients for the western and eastern Equatorial Pacific were relatively low (<0.36). These correlation coefficients were further interpreted in terms of the geographical distributions of dust sources, the transport pathways, the dust deposition, the nutrient conditions of oceans, and the probability of dust storms reaching the seas. PMID:23460892

Variability in the correlation between Asian dust storms and chlorophyll a concentration from the North to Equatorial Pacific.

PubMed

Tan, Sai-Chun; Yao, Xiaohong; Gao, Hui-Wang; Shi, Guang-Yu; Yue, Xu

2013-01-01

A long-term record of Asian dust storms showed seven high-occurrence-frequency centers in China. The intrusion of Asian dust into the downwind seas, including the China seas, the Sea of Japan, the subarctic North Pacific, the North Pacific subtropical gyre, and the western and eastern Equatorial Pacific, has been shown to add nutrients to ocean ecosystems and enhance their biological activities. To explore the relationship between the transported dust from various sources to the six seas and oceanic biological activities with different nutrient conditions, the correlation between monthly chlorophyll a concentration in each sea and monthly dust storm occurrence frequencies reaching the sea during 1997-2007 was examined in this study. No correlations were observed between dust and chlorophyll a concentration in the <50 m China seas because atmospheric deposition is commonly believed to exert less impact on coastal seas. Significant correlations existed between dust sources and many sea areas, suggesting a link between dust and chlorophyll a concentration in those seas. However, the correlation coefficients were highly variable. In general, the correlation coefficients (0.54-0.63) for the Sea of Japan were highest, except for that between the subarctic Pacific and the Taklimakan Desert, where it was as high as 0.7. For the >50 m China seas and the North Pacific subtropical gyre, the correlation coefficients were in the range 0.32-0.57. The correlation coefficients for the western and eastern Equatorial Pacific were relatively low (<0.36). These correlation coefficients were further interpreted in terms of the geographical distributions of dust sources, the transport pathways, the dust deposition, the nutrient conditions of oceans, and the probability of dust storms reaching the seas.

Correlations between symptoms, nasal endoscopy, and in-office computed tomography in post-surgical chronic rhinosinusitis patients.

PubMed

Ryan, William R; Ramachandra, Tara; Hwang, Peter H

2011-03-01

To determine correlations between symptoms, nasal endoscopy findings, and computed tomography (CT) scan findings in post-surgical chronic rhinosinusitis (CRS) patients. Cross-sectional. A total of 51 CRS patients who had undergone endoscopic sinus surgery (ESS) completed symptom questionnaires, underwent endoscopy, and received an in-office sinus CT scan during one clinic visit. For metrics, we used the Sinonasal Outcomes Test-20 (SNOT-20) questionnaire, visual analog symptom scale (VAS), Lund-Kennedy endoscopy scoring scale, and Lund-MacKay (LM) CT scoring scale. We determined Pearson correlation coefficients, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) between scores for symptoms, endoscopy, and CT. The SNOT-20 score and most VAS symptoms had poor correlation coefficients with both endoscopy and CT scores (0.03-0.24). Nasal drainage of pus, nasal congestion, and impaired sense of smell had moderate correlation coefficients with endoscopy and CT (0.24-0.42). Endoscopy had a strong correlation coefficient with CT (0.76). Drainage, edema, and polyps had strong correlation coefficients with CT (0.80, 0.69, and 0.49, respectively). Endoscopy had a PPV of 92.5% and NPV of 45.5% for detecting an abnormal sinus CT (LM score ≥1). In post-ESS CRS patients, most symptoms do not correlate well with either endoscopy or CT findings. Endoscopy and CT scores correlate well. Abnormal endoscopy findings have the ability to confidently rule in the presence of CT opacification, thus validating the importance of endoscopy in clinical decision making. However, a normal endoscopy cannot assure a normal CT. Thus, symptoms, endoscopy, and CT are complementary in the evaluation of the post-ESS CRS patient. Copyright © 2011 The American Laryngological, Rhinological, and Otological Society, Inc., Rhinological, and Otological Society, Inc.

An experimental study on the noise correlation properties of CBCT projection data

NASA Astrophysics Data System (ADS)

Zhang, Hua; Ouyang, Luo; Ma, Jianhua; Huang, Jing; Chen, Wufan; Wang, Jing

2014-03-01

In this study, we systematically investigated the noise correlation properties among detector bins of CBCT projection data by analyzing repeated projection measurements. The measurements were performed on a TrueBeam on-board CBCT imaging system with a 4030CB flat panel detector. An anthropomorphic male pelvis phantom was used to acquire 500 repeated projection data at six different dose levels from 0.1 mAs to 1.6 mAs per projection at three fixed angles. To minimize the influence of the lag effect, lag correction was performed on the consecutively acquired projection data. The noise correlation coefficient between detector bin pairs was calculated from the corrected projection data. The noise correlation among CBCT projection data was then incorporated into the covariance matrix of the penalized weighted least-squares (PWLS) criterion for noise reduction of low-dose CBCT. The analyses of the repeated measurements show that noise correlation coefficients are non-zero between the nearest neighboring bins of CBCT projection data. The average noise correlation coefficients for the first- and second- order neighbors are 0.20 and 0.06, respectively. The noise correlation coefficients are independent of the dose level. Reconstruction of the pelvis phantom shows that the PWLS criterion with consideration of noise correlation results in a lower noise level as compared to the PWLS criterion without considering the noise correlation at the matched resolution.

["Who profits?" - patient characteristics as outcome predictors in psychosomatic rehabilitation].

PubMed

Oster, J; Müller, G; Wietersheim, J von

2009-04-01

The study was to examine how far treatment success in psychosomatic rehabilitation can be predicted from patients' characteristics. The aim of this study included the development of outcome criteria, the analysis of bivariate correlations, as well as development and examination of multivariate models. The motivation for dealing with job-related problems was evaluated separately. Data were available from admission, discharge and three-months follow-up. The data of 463 patients were included. Generated were success criteria concerning sociomedical development, health as well as the ability to work. All success criteria were dichotomized. In the criteria defined, successful outcomes were found in 40 to 60% of the patients. In the bivariate analyses, it was shown that many sick days before rehabilitation, applications for pension, severe disability, high impairment, and suggestion for rehabilitation by the insurance agency, have basically negative effects on success. Correlations with the variables concerning motivation for dealing with job-related problems were rather weak. In multivariate model development, models of different quality were found. For prediction of working ability at discharge, there was an explained variance of nearly 60%. In the other success criteria as well, explained variance amounted to over 20%. The models consist of different constellations of variables, the number of sick days before rehabilitation, variables of application for pension and severity of the impairment frequently included. In case of a current sick leave, rehabilitation should be started early, sociomedical problems have to be dealt with explicitly, and rehabilitation should be accompanied by preparatory and aftercare measures.

Associations Between United States Medical Licensing Examination (USMLE) and Internal Medicine In-Training Examination (IM-ITE) Scores

PubMed Central

Zeger, Scott L.; Kolars, Joseph C.

2008-01-01

Background Little is known about the associations of previous standardized examination scores with scores on subsequent standardized examinations used to assess medical knowledge in internal medicine residencies. Objective To examine associations of previous standardized test scores on subsequent standardized test scores. Design Retrospective cohort study. Participants One hundred ninety-five internal medicine residents. Methods Bivariate associations of United States Medical Licensing Examination (USMLE) Steps and Internal Medicine In-Training Examination (IM-ITE) scores were determined. Random effects analysis adjusting for repeated administrations of the IM-ITE and other variables known or hypothesized to affect IM-ITE score allowed for discrimination of associations of individual USMLE Step scores on IM-ITE scores. Results In bivariate associations, USMLE scores explained 17% to 27% of the variance in IME-ITE scores, and previous IM-ITE scores explained 66% of the variance in subsequent IM-ITE scores. Regression coefficients (95% CI) for adjusted associations of each USMLE Step with IM-ITE scores were USMLE-1 0.19 (0.12, 0.27), USMLE-2 0.23 (0.17, 0.30), and USMLE-3 0.19 (0.09, 0.29). Conclusions No single USMLE Step is more strongly associated with IM-ITE scores than the others. Because previous IM-ITE scores are strongly associated with subsequent IM-ITE scores, appropriate modeling, such as random effects methods, should be used to account for previous IM-ITE administrations in studies for which IM-ITE score is an outcome. PMID:18612735

Associations between United States Medical Licensing Examination (USMLE) and Internal Medicine In-Training Examination (IM-ITE) scores.

PubMed

McDonald, Furman S; Zeger, Scott L; Kolars, Joseph C

2008-07-01

Little is known about the associations of previous standardized examination scores with scores on subsequent standardized examinations used to assess medical knowledge in internal medicine residencies. To examine associations of previous standardized test scores on subsequent standardized test scores. Retrospective cohort study. One hundred ninety-five internal medicine residents. Bivariate associations of United States Medical Licensing Examination (USMLE) Steps and Internal Medicine In-Training Examination (IM-ITE) scores were determined. Random effects analysis adjusting for repeated administrations of the IM-ITE and other variables known or hypothesized to affect IM-ITE score allowed for discrimination of associations of individual USMLE Step scores on IM-ITE scores. In bivariate associations, USMLE scores explained 17% to 27% of the variance in IME-ITE scores, and previous IM-ITE scores explained 66% of the variance in subsequent IM-ITE scores. Regression coefficients (95% CI) for adjusted associations of each USMLE Step with IM-ITE scores were USMLE-1 0.19 (0.12, 0.27), USMLE-2 0.23 (0.17, 0.30), and USMLE-3 0.19 (0.09, 0.29). No single USMLE Step is more strongly associated with IM-ITE scores than the others. Because previous IM-ITE scores are strongly associated with subsequent IM-ITE scores, appropriate modeling, such as random effects methods, should be used to account for previous IM-ITE administrations in studies for which IM-ITE score is an outcome.

Causal networks clarify productivity-richness interrelations, bivariate plots do not

USGS Publications Warehouse

Grace, James B.; Adler, Peter B.; Harpole, W. Stanley; Borer, Elizabeth T.; Seabloom, Eric W.

2014-01-01

We urge ecologists to consider productivity–richness relationships through the lens of causal networks to advance our understanding beyond bivariate analysis. Further, we emphasize that models based on a causal network conceptualization can also provide more meaningful guidance for conservation management than can a bivariate perspective. Measuring only two variables does not permit the evaluation of complex ideas nor resolve debates about underlying mechanisms.

Fisher information for two gamma frailty bivariate Weibull models.

PubMed

Bjarnason, H; Hougaard, P

2000-03-01

The asymptotic properties of frailty models for multivariate survival data are not well understood. To study this aspect, the Fisher information is derived in the standard bivariate gamma frailty model, where the survival distribution is of Weibull form conditional on the frailty. For comparison, the Fisher information is also derived in the bivariate gamma frailty model, where the marginal distribution is of Weibull form.

Closure and ratio correlation analysis of lunar chemical and grain size data

NASA Technical Reports Server (NTRS)

Butler, J. C.

1976-01-01

Major element and major element plus trace element analyses were selected from the lunar data base for Apollo 11, 12 and 15 basalt and regolith samples. Summary statistics for each of the six data sets were compiled, and the effects of closure on the Pearson product moment correlation coefficient were investigated using the Chayes and Kruskal approximation procedure. In general, there are two types of closure effects evident in these data sets: negative correlations of intermediate size which are solely the result of closure, and correlations of small absolute value which depart significantly from their expected closure correlations which are of intermediate size. It is shown that a positive closure correlation will arise only when the product of the coefficients of variation is very small (less than 0.01 for most data sets) and, in general, trace elements in the lunar data sets exhibit relatively large coefficients of variation.

Correlation Between Posttraumatic Growth and Posttraumatic Stress Disorder Symptoms Based on Pearson Correlation Coefficient: A Meta-Analysis.

PubMed

Liu, An-Nuo; Wang, Lu-Lu; Li, Hui-Ping; Gong, Juan; Liu, Xiao-Hong

2017-05-01

The literature on posttraumatic growth (PTG) is burgeoning, with the inconsistencies in the literature of the relationship between PTG and posttraumatic stress disorder (PTSD) symptoms becoming a focal point of attention. Thus, this meta-analysis aims to explore the relationship between PTG and PTSD symptoms through the Pearson correlation coefficient. A systematic search of the literature from January 1996 to November 2015 was completed. We retrieved reports on 63 studies that involved 26,951 patients. The weighted correlation coefficient revealed an effect size of 0.22 with a 95% confidence interval of 0.18 to 0.25. Meta-analysis provides evidence that PTG may be positively correlated with PTSD symptoms and that this correlation may be modified by age, trauma type, and time since trauma. Accordingly, people with high levels of PTG should not be ignored, but rather, they should continue to receive help to alleviate their PTSD symptoms.

[Examination of diagnosis procedure combination survey data that influence function evaluation coefficient II].

PubMed

Nakajima, Hisato; Yano, Kouya; Nagasawa, Kaoko; Kobayashi, Eiji; Yokota, Kuninobu

2015-01-01

On the basis of Diagnosis Procedure Combination (DPC) survey data, the factors that increase the value of function evaluation coefficient II were considered. A total of 1,505 hospitals were divided into groups I, II, and III, and the following items were considered. 1. Significant differences in function evaluation coefficient II and DPC survey data. 2. Examination of using the Mahalanobis-Taguchi (MT) method. 3. Correlation between function evaluation coefficient II and each DPC survey data item. 1. Function evaluation coefficient II was highest in group II. Group I hospitals showed the highest bed capacity, and numbers of hospitalization days, operations, chemotherapies, radiotherapies and general anesthesia procedures. 2. Using the MT method, we found that the number of ambulance conveyances was effective factor in group I hospitals, the number of general anesthesia procedures was effective factor in group II hospitals, and the bed capacity was effective factor in group III hospitals. 3. In group I hospitals, function evaluation coefficient II significantly correlated to the numbers of ambulance conveyances and chemotherapies. In group II hospitals, function evaluation coefficient II significantly correlated to bed capacity, the numbers of ambulance conveyances, hospitalization days, operations, general anesthesia procedures, and mean hospitalization days. In group III hospitals, function evaluation coefficient II significantly correlated to all items. The factors that improve the value of function evaluation coefficient II were the increases in the numbers of ambulance conveyances, chemotherapies and radiotherapies in group I hospitals, increases in the numbers of hospitalization days, operations, ambulance conveyances and general anesthesia procedures in group II hospitals, and increases in the numbers of hospitalization days, operations and ambulance conveyances. These results indicate that the profit of a hospital will increase, which will lead to medical services of good quality.

Estimating a graphical intra-class correlation coefficient (GICC) using multivariate probit-linear mixed models.

PubMed

Yue, Chen; Chen, Shaojie; Sair, Haris I; Airan, Raag; Caffo, Brian S

2015-09-01

Data reproducibility is a critical issue in all scientific experiments. In this manuscript, the problem of quantifying the reproducibility of graphical measurements is considered. The image intra-class correlation coefficient (I2C2) is generalized and the graphical intra-class correlation coefficient (GICC) is proposed for such purpose. The concept for GICC is based on multivariate probit-linear mixed effect models. A Markov Chain Monte Carlo EM (mcm-cEM) algorithm is used for estimating the GICC. Simulation results with varied settings are demonstrated and our method is applied to the KIRBY21 test-retest dataset.

QSAR modeling of flotation collectors using principal components extracted from topological indices.

PubMed

Natarajan, R; Nirdosh, Inderjit; Basak, Subhash C; Mills, Denise R

2002-01-01

Several topological indices were calculated for substituted-cupferrons that were tested as collectors for the froth flotation of uranium. The principal component analysis (PCA) was used for data reduction. Seven principal components (PC) were found to account for 98.6% of the variance among the computed indices. The principal components thus extracted were used in stepwise regression analyses to construct regression models for the prediction of separation efficiencies (Es) of the collectors. A two-parameter model with a correlation coefficient of 0.889 and a three-parameter model with a correlation coefficient of 0.913 were formed. PCs were found to be better than partition coefficient to form regression equations, and inclusion of an electronic parameter such as Hammett sigma or quantum mechanically derived electronic charges on the chelating atoms did not improve the correlation coefficient significantly. The method was extended to model the separation efficiencies of mercaptobenzothiazoles (MBT) and aminothiophenols (ATP) used in the flotation of lead and zinc ores, respectively. Five principal components were found to explain 99% of the data variability in each series. A three-parameter equation with correlation coefficient of 0.985 and a two-parameter equation with correlation coefficient of 0.926 were obtained for MBT and ATP, respectively. The amenability of separation efficiencies of chelating collectors to QSAR modeling using PCs based on topological indices might lead to the selection of collectors for synthesis and testing from a virtual database.

Different hip and knee priority score systems: are they good for the same thing?

PubMed

Escobar, Antonio; Quintana, Jose Maria; Espallargues, Mireia; Allepuz, Alejandro; Ibañez, Berta

2010-10-01

The aim of the present study was to compare two priority tools used for joint replacement for patients on waiting lists, which use two different methods. Two prioritization tools developed and validated by different methodologies were used on the same cohort of patients. The first, an IRYSS hip and knee priority score (IHKPS) developed by RAND method, was applied while patients were on the waiting list. The other, a Catalonia hip-knee priority score (CHKPS) developed by conjoint analysis, was adapted and applied retrospectively. In addition, all patients fulfilled pre-intervention the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Correlation between them was studied by Pearson correlation coefficient (r). Agreement was analysed by means of intra-class correlation coefficient (ICC), Kendall coefficient and Cohern kappa. The relationship between IHKPS, CHKPS and baseline WOMAC scores by r coefficient was studied. The sample consisted of 774 consecutive patients. Pearson correlation coefficient between IHKPS and CHKPS was 0.79. The agreement study showed that ICC was 0.74, Kendall coefficient 0.86 and kappa 0.66. Finally, correlation between CHKPS and baseline WOMAC ranged from 0.43 to 0.64. The results according to the relationship between IHKPS and WOMAC ranged from 0.50 to 0.74. Results support the hypothesis that if the final objective of the prioritization tools is to organize and sort patients on the waiting list, although they use different methodologies, the results are similar. © 2010 Blackwell Publishing Ltd.

High-resolution correlation

NASA Astrophysics Data System (ADS)

Nelson, D. J.

2007-09-01

In the basic correlation process a sequence of time-lag-indexed correlation coefficients are computed as the inner or dot product of segments of two signals. The time-lag(s) for which the magnitude of the correlation coefficient sequence is maximized is the estimated relative time delay of the two signals. For discrete sampled signals, the delay estimated in this manner is quantized with the same relative accuracy as the clock used in sampling the signals. In addition, the correlation coefficients are real if the input signals are real. There have been many methods proposed to estimate signal delay to more accuracy than the sample interval of the digitizer clock, with some success. These methods include interpolation of the correlation coefficients, estimation of the signal delay from the group delay function, and beam forming techniques, such as the MUSIC algorithm. For spectral estimation, techniques based on phase differentiation have been popular, but these techniques have apparently not been applied to the correlation problem . We propose a phase based delay estimation method (PBDEM) based on the phase of the correlation function that provides a significant improvement of the accuracy of time delay estimation. In the process, the standard correlation function is first calculated. A time lag error function is then calculated from the correlation phase and is used to interpolate the correlation function. The signal delay is shown to be accurately estimated as the zero crossing of the correlation phase near the index of the peak correlation magnitude. This process is nearly as fast as the conventional correlation function on which it is based. For real valued signals, a simple modification is provided, which results in the same correlation accuracy as is obtained for complex valued signals.

Development of stock correlation networks using mutual information and financial big data.

PubMed

Guo, Xue; Zhang, Hu; Tian, Tianhai

2018-01-01

Stock correlation networks use stock price data to explore the relationship between different stocks listed in the stock market. Currently this relationship is dominantly measured by the Pearson correlation coefficient. However, financial data suggest that nonlinear relationships may exist in the stock prices of different shares. To address this issue, this work uses mutual information to characterize the nonlinear relationship between stocks. Using 280 stocks traded at the Shanghai Stocks Exchange in China during the period of 2014-2016, we first compare the effectiveness of the correlation coefficient and mutual information for measuring stock relationships. Based on these two measures, we then develop two stock networks using the Minimum Spanning Tree method and study the topological properties of these networks, including degree, path length and the power-law distribution. The relationship network based on mutual information has a better distribution of the degree and larger value of the power-law distribution than those using the correlation coefficient. Numerical results show that mutual information is a more effective approach than the correlation coefficient to measure the stock relationship in a stock market that may undergo large fluctuations of stock prices.

Development of stock correlation networks using mutual information and financial big data

PubMed Central

Guo, Xue; Zhang, Hu

2018-01-01

Stock correlation networks use stock price data to explore the relationship between different stocks listed in the stock market. Currently this relationship is dominantly measured by the Pearson correlation coefficient. However, financial data suggest that nonlinear relationships may exist in the stock prices of different shares. To address this issue, this work uses mutual information to characterize the nonlinear relationship between stocks. Using 280 stocks traded at the Shanghai Stocks Exchange in China during the period of 2014-2016, we first compare the effectiveness of the correlation coefficient and mutual information for measuring stock relationships. Based on these two measures, we then develop two stock networks using the Minimum Spanning Tree method and study the topological properties of these networks, including degree, path length and the power-law distribution. The relationship network based on mutual information has a better distribution of the degree and larger value of the power-law distribution than those using the correlation coefficient. Numerical results show that mutual information is a more effective approach than the correlation coefficient to measure the stock relationship in a stock market that may undergo large fluctuations of stock prices. PMID:29668715

Exact tests using two correlated binomial variables in contemporary cancer clinical trials.

PubMed

Yu, Jihnhee; Kepner, James L; Iyer, Renuka

2009-12-01

New therapy strategies for the treatment of cancer are rapidly emerging because of recent technology advances in genetics and molecular biology. Although newer targeted therapies can improve survival without measurable changes in tumor size, clinical trial conduct has remained nearly unchanged. When potentially efficacious therapies are tested, current clinical trial design and analysis methods may not be suitable for detecting therapeutic effects. We propose an exact method with respect to testing cytostatic cancer treatment using correlated bivariate binomial random variables to simultaneously assess two primary outcomes. The method is easy to implement. It does not increase the sample size over that of the univariate exact test and in most cases reduces the sample size required. Sample size calculations are provided for selected designs.

Why are hyperactivity and academic achievement related?

PubMed

Saudino, Kimberly J; Plomin, Robert

2007-01-01

Although a negative association between hyperactivity and academic achievement is well documented, little is known about the genetic and/or environmental mechanisms responsible for the association. The present study explored links between parent and teacher ratings of hyperactive behavior problems and teacher-assessed achievement in a sample of 1,876 twin pairs (mean age 7.04 years). The results did not differ across rater, nor were there significant differences between males or females or for twins in the same or different classrooms. Hyperactivity was significantly correlated with achievement. Multivariate model-fitting analyses revealed significant genetic and nonshared environmental covariance between the two phenotypes. In addition, bivariate heritabilities were substantial, indicating that the phenotypic correlations between hyperactivity and achievement were largely mediated by genetic influences.

Spaced antenna diversity in temperate latitude meteor burst systems operating near 40 MHz - Variation of signal cross-correlation coefficients with antenna separation

NASA Astrophysics Data System (ADS)

Cannon, Paul S.; Shukla, Anil K.; Lester, Mark

1993-04-01

We have studied 37-MHz signals received over an 800-km temperate latitude path using 400-W continuous wave transmissions. Signals collected during a 9-day period in February 1990 on two antennas at separations of 5, 10, and 20 lambda were analyzed. Three signal categories were identified (overdense, underdense, and not known (NK)) and cross-correlation coefficients between the signals received by the two antennas were calculated for each signal category. No spatial variation, and in particular no decrease, in average cross-correlation coefficient was observed for underdense or NK signals as the antenna spacing was increased from 5 to 20 lambda. At each antenna separation the cross-correlation coefficients of these two categories were strongly dependent on time. Overdense signals, however, showed no cross-correlation time dependency at 5 and 10 lambda, but there was a strong time dependency at 20 lambda. Recommendations are made in regard to the optimum antenna spacing for a meteor burst communication system using spaced antenna diversity.

Transcultural adaptation and psychometric properties of Spanish version of Pregnancy Physical Activity Questionnaire: the PregnActive project.

PubMed

Oviedo-Caro, Miguel Ángel; Bueno-Antequera, Javier; Munguía-Izquierdo, Diego

2018-03-19

To transculturally adapt the Spanish version of Pregnancy Physical Activity Questionnaire (PPAQ) analyzing its psychometric properties. The PPAQ was transculturally adapted into Spanish. Test-retest reliability was evaluated in a subsample of 109 pregnant women. The validity was evaluated in a sample of 208 pregnant women who answered the questionnaire and wore the multi-sensor monitor for 7 valid days. The reliability (intraclass correlation coefficient), concordance (concordance correlation coefficient), correlation (Pearson correlation coefficient), agreement (Bland-Altman plots) and relative activity levels (Jonckheere-Terpstra test) between both administrations and methods were examined. Intraclass correlation coefficients between both administrations were good for all categories except transportation. A low but significant correlation was found for total activity (light and above) whereas no correlation was found for other intensities between both methods. Relative activity levels analysis showed a significant linear trend for increased total activity between both methods. Spanish version of PPAQ is a brief and easily interpretable questionnaire with good reliability and ability to rank individuals, and poor validity compared with multi-sensor monitor. The use of PPAQ provides information of pregnancy-specific activities in order to establish physical activity levels of pregnant women and adapt health promotion interventions. Copyright © 2018 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

Cross-Correlations and Structures of Aero-Engine Gas Path System Based on DCCA Coefficient and Rooted Tree

NASA Astrophysics Data System (ADS)

Dong, Keqiang; Fan, Jie; Gao, You

2015-12-01

Identifying the mutual interaction is a crucial problem that facilitates the understanding of emerging structures in complex system. We here focus on aero-engine dynamic as an example of complex system. By applying the detrended cross-correlation analysis (DCCA) coefficient method to aero-engine gas path system, we find that the low-spool rotor speed (N1) and high-spool rotor speed (N2) fluctuation series exhibit cross-correlation characteristic. Further, we employ detrended cross-correlation coefficient matrix and rooted tree to investigate the mutual interactions of other gas path variables. The results can infer that the exhaust gas temperature (EGT), N1, N2, fuel flow (WF) and engine pressure ratio (EPR) are main gas path parameters.

Colocalization analysis in fluorescence micrographs: verification of a more accurate calculation of pearson's correlation coefficient.

PubMed

Barlow, Andrew L; Macleod, Alasdair; Noppen, Samuel; Sanderson, Jeremy; Guérin, Christopher J

2010-12-01

One of the most routine uses of fluorescence microscopy is colocalization, i.e., the demonstration of a relationship between pairs of biological molecules. Frequently this is presented simplistically by the use of overlays of red and green images, with areas of yellow indicating colocalization of the molecules. Colocalization data are rarely quantified and can be misleading. Our results from both synthetic and biological datasets demonstrate that the generation of Pearson's correlation coefficient between pairs of images can overestimate positive correlation and fail to demonstrate negative correlation. We have demonstrated that the calculation of a thresholded Pearson's correlation coefficient using only intensity values over a determined threshold in both channels produces numerical values that more accurately describe both synthetic datasets and biological examples. Its use will bring clarity and accuracy to colocalization studies using fluorescent microscopy.

Estimation of soil-soil solution distribution coefficient of radiostrontium using soil properties.

PubMed

Ishikawa, Nao K; Uchida, Shigeo; Tagami, Keiko

2009-02-01

We propose a new approach for estimation of soil-soil solution distribution coefficient (K(d)) of radiostrontium using some selected soil properties. We used 142 Japanese agricultural soil samples (35 Andosol, 25 Cambisol, 77 Fluvisol, and 5 others) for which Sr-K(d) values had been determined by a batch sorption test and listed in our database. Spearman's rank correlation test was carried out to investigate correlations between Sr-K(d) values and soil properties. Electrical conductivity and water soluble Ca had good correlations with Sr-K(d) values for all soil groups. Then, we found a high correlation between the ratio of exchangeable Ca to Ca concentration in water soluble fraction and Sr-K(d) values with correlation coefficient R=0.72. This pointed us toward a relatively easy way to estimate Sr-K(d) values.

Reducing Bias and Error in the Correlation Coefficient Due to Nonnormality.

PubMed

Bishara, Anthony J; Hittner, James B

2015-10-01

It is more common for educational and psychological data to be nonnormal than to be approximately normal. This tendency may lead to bias and error in point estimates of the Pearson correlation coefficient. In a series of Monte Carlo simulations, the Pearson correlation was examined under conditions of normal and nonnormal data, and it was compared with its major alternatives, including the Spearman rank-order correlation, the bootstrap estimate, the Box-Cox transformation family, and a general normalizing transformation (i.e., rankit), as well as to various bias adjustments. Nonnormality caused the correlation coefficient to be inflated by up to +.14, particularly when the nonnormality involved heavy-tailed distributions. Traditional bias adjustments worsened this problem, further inflating the estimate. The Spearman and rankit correlations eliminated this inflation and provided conservative estimates. Rankit also minimized random error for most sample sizes, except for the smallest samples ( n = 10), where bootstrapping was more effective. Overall, results justify the use of carefully chosen alternatives to the Pearson correlation when normality is violated.

Reducing Bias and Error in the Correlation Coefficient Due to Nonnormality

PubMed Central

Hittner, James B.

2014-01-01

It is more common for educational and psychological data to be nonnormal than to be approximately normal. This tendency may lead to bias and error in point estimates of the Pearson correlation coefficient. In a series of Monte Carlo simulations, the Pearson correlation was examined under conditions of normal and nonnormal data, and it was compared with its major alternatives, including the Spearman rank-order correlation, the bootstrap estimate, the Box–Cox transformation family, and a general normalizing transformation (i.e., rankit), as well as to various bias adjustments. Nonnormality caused the correlation coefficient to be inflated by up to +.14, particularly when the nonnormality involved heavy-tailed distributions. Traditional bias adjustments worsened this problem, further inflating the estimate. The Spearman and rankit correlations eliminated this inflation and provided conservative estimates. Rankit also minimized random error for most sample sizes, except for the smallest samples (n = 10), where bootstrapping was more effective. Overall, results justify the use of carefully chosen alternatives to the Pearson correlation when normality is violated. PMID:29795841

Correlation and prediction of gaseous diffusion coefficients.

NASA Technical Reports Server (NTRS)

Marrero, T. R.; Mason, E. A.

1973-01-01

A new correlation method for binary gaseous diffusion coefficients from very low temperatures to 10,000 K is proposed based on an extended principle of corresponding states, and having greater range and accuracy than previous correlations. There are two correlation parameters that are related to other physical quantities and that are predictable in the absence of diffusion measurements. Quantum effects and composition dependence are included, but high-pressure effects are not. The results are directly applicable to multicomponent mixtures.

Equations of prediction for abdominal fat in brown egg-laying hens fed different diets.

PubMed

Souza, C; Jaimes, J J B; Gewehr, C E

2017-06-01

The objective was to use noninvasive measurements to formulate equations for predicting the abdominal fat weight of laying hens in a noninvasive manner. Hens were fed with different diets; the external body measurements of birds were used as regressors. We used 288 Hy-Line Brown laying hens, distributed in a completely randomized design in a factorial arrangement, submitted for 16 wk to 2 metabolizable energy levels (2,550 and 2,800 kcal/kg) and 3 levels of crude protein in the diet (150, 160, and 170 g/kg), totaling 6 treatments, with 48 hens each. Sixteen hens per treatment of 92 wk age were utilized to evaluate body weight, bird length, tarsus and sternum, greater and lesser diameter of the tarsus, and abdominal fat weight, after slaughter. The equations were obtained by using measures evaluated with regressors through simple and multiple linear regression with the stepwise method of indirect elimination (backward), with P < 0.10 for all variables remaining in the model. The weight of abdominal fat as predicted by the equations and observed values for each bird were subjected to Pearson's correlation analysis. The equations generated by energy levels showed coefficients of determination of 0.50 and 0.74 for 2,800 and 2,550 kcal/kg of metabolizable energy, respectively, with correlation coefficients of 0.71 and 0.84, with a highly significant correlation between the calculated and observed values of abdominal fat. For protein levels of 150, 160, and 170 g/kg in the diet, it was possible to obtain coefficients of determination of 0.75, 0.57, and 0.61, with correlation coefficients of 0.86, 0.75, and 0.78, respectively. Regarding the general equation for predicting abdominal fat weight, the coefficient of determination was 0.62; the correlation coefficient was 0.79. The equations for predicting abdominal fat weight in laying hens, based on external measurements of the birds, showed positive coefficients of determination and correlation coefficients, thus allowing researchers to determine abdominal fat weight in vivo. © 2016 Poultry Science Association Inc.

Virial Coefficients for the Liquid Argon

NASA Astrophysics Data System (ADS)

Korth, Micheal; Kim, Saesun

2014-03-01

We begin with a geometric model of hard colliding spheres and calculate probability densities in an iterative sequence of calculations that lead to the pair correlation function. The model is based on a kinetic theory approach developed by Shinomoto, to which we added an interatomic potential for argon based on the model from Aziz. From values of the pair correlation function at various values of density, we were able to find viral coefficients of liquid argon. The low order coefficients are in good agreement with theoretical hard sphere coefficients, but appropriate data for argon to which these results might be compared is difficult to find.

Reproducibility of food consumption frequencies derived from the Children's Eating Habits Questionnaire used in the IDEFICS study.

PubMed

Lanfer, A; Hebestreit, A; Ahrens, W; Krogh, V; Sieri, S; Lissner, L; Eiben, G; Siani, A; Huybrechts, I; Loit, H-M; Papoutsou, S; Kovács, E; Pala, V

2011-04-01

To investigate the reproducibility of food consumption frequencies derived from the food frequency section of the Children's Eating Habits Questionnaire (CEHQ-FFQ) that was developed and used in the IDEFICS (Identification and prevention of dietary- and lifestyle-induced health effects in children and infants) project to assess food habits in 2- to 9-year-old European children. From a subsample of 258 children who participated in the IDEFICS baseline examination, parental questionnaires of the CEHQ were collected twice to assess reproducibility of questionnaire results from 0 to 354 days after the first examination. Weighted Cohen's kappa coefficients (κ) and Spearman's correlation coefficients (r) were calculated to assess agreement between the first and second questionnaires for each food item of the CEHQ-FFQ. Stratification was performed for sex, age group, geographical region and length of period between the first and second administrations. Fisher's Z transformation was applied to test correlation coefficients for significant differences between strata. For all food items analysed, weighted Cohen's kappa coefficients (κ) and Spearman's correlation coefficients (r) were significant and positive (P<0.001). Reproducibility was lowest for diet soft drinks (κ=0.23, r=0.32) and highest for sweetened milk (κ=0.68, r=0.76). Correlation coefficients were comparable to those of previous studies on FFQ reproducibility in children and adults. Stratification did not reveal systematic differences in reproducibility by sex and age group. Spearman's correlation coefficients differed significantly between northern and southern European countries for 10 food items. In nine of them, the lower respective coefficient was still high enough to conclude acceptable reproducibility. As expected, longer time (>128 days) between the first and second administrations resulted in a generally lower, yet still acceptable, reproducibility. Results indicate that the CEHQ-FFQ gives reproducible estimates of the consumption frequency of 43 food items from 14 food groups in European children.

[Cross-cultural adaptation and validation of the Health and Taste Attitude Scale (HTAS) in Portuguese].

PubMed

Koritar, Priscila; Philippi, Sonia Tucunduva; Alvarenga, Marle dos Santos; Santos, Bernardo dos

2014-08-01

The scope of this study was to show the cross-cultural adaptation and validation of the Health and Taste Attitude Scale in Portuguese. The methodology included translation of the scale; evaluation of conceptual, operational and item-based equivalence by 14 experts and 51 female undergraduates; semantic equivalence and measurement assessment by 12 bilingual women by the paired t-test, the Pearson correlation coefficient and the coefficient intraclass correlation; internal consistency and test-retest reliability by Cronbach's alpha and intraclass correlation coefficient, respectively, after application on 216 female undergraduates; assessment of discriminant and concurrent validity via the t-test and Spearman's correlation coefficient, respectively, in addition to Confirmatory Factor and Exploratory Factor Analysis. The scale was considered adequate and easily understood by the experts and university students and presented good internal consistency and reliability (µ 0.86, ICC 0.84). The results show that the scale is valid and can be used in studies with women to better understand attitudes related to taste.

Negative Correlation between the Diffusion Coefficient and Transcriptional Activity of the Glucocorticoid Receptor.

PubMed

Mikuni, Shintaro; Yamamoto, Johtaro; Horio, Takashi; Kinjo, Masataka

2017-08-25

The glucocorticoid receptor (GR) is a transcription factor, which interacts with DNA and other cofactors to regulate gene transcription. Binding to other partners in the cell nucleus alters the diffusion properties of GR. Raster image correlation spectroscopy (RICS) was applied to quantitatively characterize the diffusion properties of EGFP labeled human GR (EGFP-hGR) and its mutants in the cell nucleus. RICS is an image correlation technique that evaluates the spatial distribution of the diffusion coefficient as a diffusion map. Interestingly, we observed that the averaged diffusion coefficient of EGFP-hGR strongly and negatively correlated with its transcriptional activities in comparison to that of EGFP-hGR wild type and mutants with various transcriptional activities. This result suggests that the decreasing of the diffusion coefficient of hGR was reflected in the high-affinity binding to DNA. Moreover, the hyper-phosphorylation of hGR can enhance the transcriptional activity by reduction of the interaction between the hGR and the nuclear corepressors.

Comprehensive analysis of correlation coefficients estimated from pooling heterogeneous microarray data

PubMed Central

2013-01-01

Background The synthesis of information across microarray studies has been performed by combining statistical results of individual studies (as in a mosaic), or by combining data from multiple studies into a large pool to be analyzed as a single data set (as in a melting pot of data). Specific issues relating to data heterogeneity across microarray studies, such as differences within and between labs or differences among experimental conditions, could lead to equivocal results in a melting pot approach. Results We applied statistical theory to determine the specific effect of different means and heteroskedasticity across 19 groups of microarray data on the sign and magnitude of gene-to-gene Pearson correlation coefficients obtained from the pool of 19 groups. We quantified the biases of the pooled coefficients and compared them to the biases of correlations estimated by an effect-size model. Mean differences across the 19 groups were the main factor determining the magnitude and sign of the pooled coefficients, which showed largest values of bias as they approached ±1. Only heteroskedasticity across the pool of 19 groups resulted in less efficient estimations of correlations than did a classical meta-analysis approach of combining correlation coefficients. These results were corroborated by simulation studies involving either mean differences or heteroskedasticity across a pool of N > 2 groups. Conclusions The combination of statistical results is best suited for synthesizing the correlation between expression profiles of a gene pair across several microarray studies. PMID:23822712

Behavioral and Psychosocial Correlates of HIV Testing Among Male Clients of Female Sex Workers in Tijuana, Mexico.

PubMed

Fleming, Paul J; Patterson, Thomas L; Chavarin, Claudia V; Semple, Shirley J; Magis-Rodriguez, Carlos; Pitpitan, Eileen V

2017-08-01

We use data collected from a sample of 400 male clients of female sex workers (FSW) to examine their HIV testing behavior. We present frequencies of HIV testing and used bivariate and multivariable analyses to assess its socio-demographic, behavioral, and psychosocial correlates. We found that the majority (55 %) of male clients of FSW in Tijuana, Mexico had never had an HIV test and the prevalence of HIV testing within the past year was low (9 %). In multivariable analyses, significant correlates of having ever tested for HIV were higher age, higher HIV knowledge score, lower sexual compulsiveness score, lower misogynistic attitudes score, having a condom break during sex with a FSW, and higher frequency of sex with a FSW while she was high. Our findings represent an important starting point for developing effective interventions to address the need to promote HIV testing among this population.

TETRA-COM: a comprehensive SPSS program for estimating the tetrachoric correlation.

PubMed

Lorenzo-Seva, Urbano; Ferrando, Pere J

2012-12-01

We provide an SPSS program that implements descriptive and inferential procedures for estimating tetrachoric correlations. These procedures have two main purposes: (1) bivariate estimation in contingency tables and (2) constructing a correlation matrix to be used as input for factor analysis (in particular, the SPSS FACTOR procedure). In both cases, the program computes accurate point estimates, as well as standard errors and confidence intervals that are correct for any population value. For purpose (1), the program computes the contingency table together with five other measures of association. For purpose (2), the program checks the positive definiteness of the matrix, and if it is found not to be Gramian, performs a nonlinear smoothing procedure at the user's request. The SPSS syntax, a short manual, and data files related to this article are available as supplemental materials from brm.psychonomic-journals.org/content/supplemental.

Life satisfaction and its correlates in older women with osteoarthritis.

PubMed

Tak, Sunghee H; Laffrey, Shirley C

2003-01-01

To identify the relationships among functional disability, chronic daily stress, coping strategies, beliefs about personal control, social support, and life satisfaction in older women with osteoarthritis. A descriptive, correlational design was used. The study participants were 107 women aged 60 years or older. Study participants completed six survey questionnaires and a demographic form. Bivariate correlational analyses showed that older women with poorer functional ability experienced greater chronic daily stress, reported more frequent use of emotion-focused coping strategies, and had a higher chance health locus of control. A hierarchic regression analysis revealed that the perceived social support and internal health locus of control significantly contributed to the prediction of life satisfaction after demographic, illness-related, and stress-related variables were controlled. Stress management strategies matched to the participants' style of coping process can increase their sense of control over their health and enhance their social networks and activities.

Personal growth, symptoms, and uncertainty in community-residing adults with heart failure.

PubMed

Overbaugh, Kristen J; Parshall, Mark B

Personal growth has not been studied extensively in heart failure (HF). To characterize personal growth in HF and its relationships with symptom burden, uncertainty, and demographic and clinical factors. Associations among personal growth, uncertainty, symptom burden, and clinical and demographic variables were examined in adult outpatients with HF using bivariate correlations and multiple regressions. Participants (N = 103; 76% male, mean age = 74 years, 97% New York Heart Association classes II and III) reported moderate levels of personal growth, uncertainty, and symptom burden. Personal growth was weakly correlated with age and symptom burden but not with other study variables. In a regression model, age, sex, ethnicity, disease severity, time since diagnosis, symptom burden, and uncertainty were not significant independent correlates of personal growth. Community-residing patients with HF report moderate personal growth that is not explained by uncertainty, symptom burden, or demographic and clinical variables. Copyright © 2016 Elsevier Inc. All rights reserved.

High-level language ability in healthy individuals and its relationship with verbal working memory.

PubMed

Antonsson, Malin; Longoni, Francesca; Einald, Christina; Hallberg, Lina; Kurt, Gabriella; Larsson, Kajsa; Nilsson, Tina; Hartelius, Lena

2016-01-01

The aims of the study were to investigate healthy subjects' performance on a clinical test of high-level language (HLL) and how it is related to demographic characteristics and verbal working memory (VWM). One hundred healthy subjects (20-79 years old) were assessed with the Swedish BeSS test (Laakso, Brunnegård, Hartelius, & Ahlsén, 2000) and two digit span tasks. Relationships between the demographic variables, VWM and BeSS were investigated both with bivariate correlations and multiple regression analysis. The results present the norms for BeSS. The correlations and multiple regression analysis show that demographic variables had limited influence on test performance. Measures of VWM were moderately related to total BeSS score and weakly to moderately correlated with five of the seven subtests. To conclude, education has an influence on the test as a whole but measures of VWM stood out as the most robust predictor of HLL.

Psychosocial correlates of suicidal ideation in rural South African adolescents.

PubMed

Shilubane, Hilda N; Ruiter, Robert A C; Bos, Arjan E R; van den Borne, Bart; James, Shamagonam; Reddy, Priscilla S

2014-01-01

Suicide is a prevalent problem among young people in Southern Africa, but prevention programs are largely absent. This survey aimed to identify the behavioral and psychosocial correlates of suicidal ideation among adolescents in Limpopo. A two-stage cluster sample design was used to establish a representative sample of 591 adolescents. Bivariate correlations and multiple linear regression analyses were conducted. Findings show that suicidal ideation is prevalent among adolescents. The psychosocial factors perceived social support and negative feelings about the family and the behavioral factors forced sexual intercourse and physical violence by the partner were found to increase the risk of suicidal ideation. Depression mediated the relationship between these psychosocial and behavioral risk factors and suicidal ideation. This study increased our understanding of the psychosocial and behavioral predictors of adolescent suicidal ideation. The findings provide target points for future intervention programs and call for supportive structures to assist adolescents with suicidal ideation.

Factors associated with changes in vaginal length and diameter during pelvic radiotherapy for cervical cancer.

PubMed

Martins, Jumara; Vaz, Ana Francisca; Grion, Regina Celia; Esteves, Sérgio Carlos Barros; Costa-Paiva, Lúcia; Baccaro, Luiz Francisco

2017-12-01

This study reports the incidence and factors associated with vaginal stenosis and changes in vaginal dimensions after pelvic radiotherapy for cervical cancer. A descriptive longitudinal study with 139 women with cervical cancer was conducted from January 2013 to November 2015. The outcome variables were vaginal stenosis assessed using the Common Terminology Criteria for Adverse Events (CTCAE v3.0) and changes in vaginal diameter and length after the end of radiotherapy. Independent variables were the characteristics of the neoplasm, clinical and sociodemographic data. Bivariate analysis was carried out using χ 2 , Kruskal-Wallis and Mann-Whitney's test. Multiple analysis was carried out using Poisson regression and a generalized linear model. Most women (50.4%) had stage IIIB tumors. According to CTCAE v3.0 scale, 30.2% had no stenosis, 69.1% had grade 1 and 0.7% had grade 2 stenosis after radiotherapy. Regarding changes in vaginal measures, the mean variation in diameter was - 0.6 (± 1.7) mm and the mean variation in length was - 0.6 (± 1.3) cm. In the final statistical model, having tumoral invasion of the vaginal walls (coefficient + 0.73, p < 0.01) and diabetes (coefficient + 1.16; p < 0.01) were associated with lower vaginal stenosis and lower reduction of vaginal dimensions. Advanced clinical stage (coefficient + 1.44; p = 0.02) and receiving brachytherapy/teletherapy (coefficient - 1.17, p < 0.01) were associated with higher reduction of vaginal dimensions. Most women had mild vaginal stenosis with slight reductions in both diameter and length of the vaginal canal. Women with tumoral invasion of the vagina have an increase in vaginal length soon after radiotherapy due to a reduction in tumoral volume.

Correlation between National Influenza Surveillance Data and Google Trends in South Korea

PubMed Central

Jo, Min Woo; Shin, Soo-Yong; Lee, Jae Ho; Ryoo, Seoung Mok; Kim, Won Young; Seo, Dong-Woo

2013-01-01

Background In South Korea, there is currently no syndromic surveillance system using internet search data, including Google Flu Trends. The purpose of this study was to investigate the correlation between national influenza surveillance data and Google Trends in South Korea. Methods Our study was based on a publicly available search engine database, Google Trends, using 12 influenza-related queries, from September 9, 2007 to September 8, 2012. National surveillance data were obtained from the Korea Centers for Disease Control and Prevention (KCDC) influenza-like illness (ILI) and virologic surveillance system. Pearson's correlation coefficients were calculated to compare the national surveillance and the Google Trends data for the overall period and for 5 influenza seasons. Results The correlation coefficient between the KCDC ILI and virologic surveillance data was 0.72 (p<0.05). The highest correlation was between the Google Trends query of H1N1 and the ILI data, with a correlation coefficient of 0.53 (p<0.05), for the overall study period. When compared with the KCDC virologic data, the Google Trends query of bird flu had the highest correlation with a correlation coefficient of 0.93 (p<0.05) in the 2010-11 season. The following queries showed a statistically significant correlation coefficient compared with ILI data for three consecutive seasons: Tamiflu (r = 0.59, 0.86, 0.90, p<0.05), new flu (r = 0.64, 0.43, 0.70, p<0.05) and flu (r = 0.68, 0.43, 0.77, p<0.05). Conclusions In our study, we found that the Google Trends for certain queries using the survey on influenza correlated with national surveillance data in South Korea. The results of this study showed that Google Trends in the Korean language can be used as complementary data for influenza surveillance but was insufficient for the use of predictive models, such as Google Flu Trends. PMID:24339927

Correlation between national influenza surveillance data and google trends in South Korea.

PubMed

Cho, Sungjin; Sohn, Chang Hwan; Jo, Min Woo; Shin, Soo-Yong; Lee, Jae Ho; Ryoo, Seoung Mok; Kim, Won Young; Seo, Dong-Woo

2013-01-01

In South Korea, there is currently no syndromic surveillance system using internet search data, including Google Flu Trends. The purpose of this study was to investigate the correlation between national influenza surveillance data and Google Trends in South Korea. Our study was based on a publicly available search engine database, Google Trends, using 12 influenza-related queries, from September 9, 2007 to September 8, 2012. National surveillance data were obtained from the Korea Centers for Disease Control and Prevention (KCDC) influenza-like illness (ILI) and virologic surveillance system. Pearson's correlation coefficients were calculated to compare the national surveillance and the Google Trends data for the overall period and for 5 influenza seasons. The correlation coefficient between the KCDC ILI and virologic surveillance data was 0.72 (p<0.05). The highest correlation was between the Google Trends query of H1N1 and the ILI data, with a correlation coefficient of 0.53 (p<0.05), for the overall study period. When compared with the KCDC virologic data, the Google Trends query of bird flu had the highest correlation with a correlation coefficient of 0.93 (p<0.05) in the 2010-11 season. The following queries showed a statistically significant correlation coefficient compared with ILI data for three consecutive seasons: Tamiflu (r = 0.59, 0.86, 0.90, p<0.05), new flu (r = 0.64, 0.43, 0.70, p<0.05) and flu (r = 0.68, 0.43, 0.77, p<0.05). In our study, we found that the Google Trends for certain queries using the survey on influenza correlated with national surveillance data in South Korea. The results of this study showed that Google Trends in the Korean language can be used as complementary data for influenza surveillance but was insufficient for the use of predictive models, such as Google Flu Trends.

A bivariate gamma probability distribution with application to gust modeling. [for the ascent flight of the space shuttle

NASA Technical Reports Server (NTRS)

Smith, O. E.; Adelfang, S. I.; Tubbs, J. D.

1982-01-01

A five-parameter gamma distribution (BGD) having two shape parameters, two location parameters, and a correlation parameter is investigated. This general BGD is expressed as a double series and as a single series of the modified Bessel function. It reduces to the known special case for equal shape parameters. Practical functions for computer evaluations for the general BGD and for special cases are presented. Applications to wind gust modeling for the ascent flight of the space shuttle are illustrated.

The association between conduct problems and maltreatment: testing genetic and environmental mediation.

PubMed

Schulz-Heik, R Jay; Rhee, Soo Hyun; Silvern, Louise E; Haberstick, Brett C; Hopfer, Christian; Lessem, Jeffrey M; Hewitt, John K

2010-05-01

It is often assumed that childhood maltreatment causes conduct problems via an environmentally mediated process. However, the association may be due alternatively to either a nonpassive gene-environment correlation, in which parents react to children's genetically-influenced conduct problems by maltreating them, or a passive gene-environment correlation, in which parents' tendency to engage in maltreatment and children's conduct problems are both influenced by a hereditary vulnerability to antisocial behavior (i.e. genetic mediation). The present study estimated the contribution of these processes to the association between maltreatment and conduct problems. Bivariate behavior genetic analyses were conducted on approximately 1,650 twin and sibling pairs drawn from a large longitudinal study of adolescent health (Add Health). The correlation between maltreatment and conduct problems was small; much of the association between maltreatment and conduct problems was due to a nonpassive gene-environment correlation. Results were more consistent with the hypothesis that parents respond to children's genetically-influenced conduct problems by maltreating them than the hypothesis that maltreatment causes conduct problems.

Supersymmetric contributions to weak decay correlation coefficients

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

Profumo, S.; Ramsey-Musolf, M. J.; Tulin, S.

2007-04-01

We study supersymmetric contributions to correlation coefficients that characterize the spectral shape and angular distribution for polarized {mu}- and {beta}-decays. In the minimal supersymmetric standard model (MSSM), one-loop box graphs containing superpartners can give rise to non-(V-Ax(V-A) four-fermion operators in the presence of left-right or flavor mixing between sfermions. We analyze the present phenomenological constraints on such mixing and determine the range of allowed contributions to the weak decay correlation coefficients. We discuss the prospective implications for future {mu}- and {beta}-decay experiments, and argue that they may provide unique probes of left-right mixing in the first generation scalar fermion sector.

Ecotoxicology of phenylphosphonothioates.

PubMed Central

Francis, B M; Hansen, L G; Fukuto, T R; Lu, P Y; Metcalf, R L

1980-01-01

The phenylphosphonothioate insecticides EPN and leptophos, and several analogs, were evaluated with respect to their delayed neurotoxic effects in hens and their environmental behavior in a terrestrial-aquatic model ecosystem. Acute toxicity to insects was highly correlated with sigma sigma of the substituted phenyl group (regression coefficient r = -0.91) while acute toxicity to mammals was slightly less well correlated (regression coefficient r = -0.71), and neurotoxicity was poorly correlated with sigma sigma (regression coefficient r = -0.35). Both EPN and leptophos were markedly more persistent and bioaccumulative in the model ecosystem than parathion. Desbromoleptophos, a contaminant and metabolite of leptophos, was seen to be a highly stable and persistent terminal residue of leptophos. PMID:6159210

Choosing the best index for the average score intraclass correlation coefficient.

PubMed

Shieh, Gwowen

2016-09-01

The intraclass correlation coefficient (ICC)(2) index from a one-way random effects model is widely used to describe the reliability of mean ratings in behavioral, educational, and psychological research. Despite its apparent utility, the essential property of ICC(2) as a point estimator of the average score intraclass correlation coefficient is seldom mentioned. This article considers several potential measures and compares their performance with ICC(2). Analytical derivations and numerical examinations are presented to assess the bias and mean square error of the alternative estimators. The results suggest that more advantageous indices can be recommended over ICC(2) for their theoretical implication and computational ease.

The Evolution of Pearson's Correlation Coefficient

ERIC Educational Resources Information Center

Kader, Gary D.; Franklin, Christine A.

2008-01-01

This article describes an activity for developing the notion of association between two quantitative variables. By exploring a collection of scatter plots, the authors propose a nonstandard "intuitive" measure of association; and by examining properties of this measure, they develop the more standard measure, Pearson's Correlation Coefficient. The…

Modeling Concordance Correlation Coefficient for Longitudinal Study Data

ERIC Educational Resources Information Center

Ma, Yan; Tang, Wan; Yu, Qin; Tu, X. M.

2010-01-01

Measures of agreement are used in a wide range of behavioral, biomedical, psychosocial, and health-care related research to assess reliability of diagnostic test, psychometric properties of instrument, fidelity of psychosocial intervention, and accuracy of proxy outcome. The concordance correlation coefficient (CCC) is a popular measure of…

Neonates with Bartter syndrome have enormous fluid and sodium requirements.

PubMed

Azzi, Antonio; Chehade, Hassib; Deschênes, Georges

2015-07-01

Managing neonatal Bartter syndrome by achieving adequate weight gain is challenging. We assessed the correlation between weight gain in neonatal Bartter syndrome and the introduction of fluid and sodium supplementations and indomethacin during the first 4 weeks of life. Daily fluid and electrolytes requirements were analysed using linear regression and Spearman correlation coefficients. The weight gain coefficient was calculated as daily weight gain after physiological neonatal weight loss. We studied seven infants. The highest weight gain coefficients occurred between weeks two and four in the five neonates who either received prompt amounts of fluid (maximum 810 mL/kg/day) and sodium (maximum 70 mmol/kg/day) or were treated with indomethacin. For the two patients with the highest weight gain coefficient, water and sodium supplementations were decreased in weeks two to four leading to a significant negative Spearman correlation between weight gain and fluid supplements (r = -0.55 and -0.68) and weight gain and sodium supplementations (r = -0.96 and -0.72). The two patients with the lowest weight gain coefficient had positive Spearman correlation coefficients between weight gain and fluid and sodium supplementations. Infants with neonatal Bartter syndrome required rapid and enormous fluid and sodium supplementations or the early introduction of indomethacin treatment to achieve adequate weight gain during the early postnatal period. ©2015 Foundation Acta Paediatrica. Published by John Wiley & Sons Ltd.

Molecular genetic analysis of the F11 gene in 14 Turkish patients with factor XI deficiency: identification of novel and recurrent mutations and their inheritance within families

PubMed Central

Colakoglu, Seyma; Bayhan, Turan; Tavil, Betül; Keskin, Ebru Yılmaz; Cakir, Volkan; Gümrük, Fatma; Çetin, Mualla; Aytaç, Selin; Berber, Ergul

2018-01-01

Background Factor XI (FXI) deficiency is an autosomal bleeding disease associated with genetic defects in the F11 gene which cause decreased FXI levels or impaired FXI function. An increasing number of mutations has been reported in the FXI mutation database, most of which affect the serine protease domain of the protein. FXI is a heterogeneous disorder associated with a variable bleeding tendency and a variety of causative F11 gene mutations. The molecular basis of FXI deficiency in 14 patients from ten unrelated families in Turkey was analysed to establish genotype-phenotype correlations and inheritance of the mutations in the patients’ families. Material and methods Fourteen index cases with a diagnosis of FXI deficiency and family members of these patients were enrolled into the study. The patients’ F11 genes were amplified by polymerase chain reaction and subjected to direct DNA sequencing analysis. The findings were analysed statistically using bivariate correlations, Pearson’s correlation coefficient and the nonparametric Mann-Whitney test. Results Direct DNA sequencing analysis of the F11 genes revealed that all of the 14 patients had a F11 gene mutation. Eight different mutations were identified in the apple 1, apple 2 or serine protease domains, except one which was a splice site mutation. Six of the mutations were recurrent. Two of the mutations were novel missense mutations, p.Val522Gly and p.Cys581Arg, within the catalytic domain. The p.Trp519Stop mutation was observed in two families whereas all the other mutations were specific to a single family. Discussion Identification of mutations confirmed the genetic heterogeneity of FXI deficiency. Most of the patients with mutations did not have any bleeding complications, whereas some had severe bleeding symptoms. Genetic screening for F11 gene mutations is important to decrease the mortality and morbidity rate associated with FXI deficiency, which can be life-threatening if bleeding occurs in tissues with high fibrinolytic activity. PMID:27723456

[The appraisal of reliability and validity of subjective workload assessment technique and NASA-task load index].

PubMed

Xiao, Yuan-mei; Wang, Zhi-ming; Wang, Mian-zhen; Lan, Ya-jia

2005-06-01

To test the reliability and validity of two mental workload assessment scales, i.e. subjective workload assessment technique (SWAT) and NASA task load index (NASA-TLX). One thousand two hundred and sixty-eight mental workers were sampled from various kinds of occupations, such as scientific research, education, administration and medicine, etc, with randomized cluster sampling. The re-test reliability, split-half reliability, Cronbach's alpha coefficient and correlation coefficients between item score and total score were adopted to test the reliability. The test of validity included structure validity. The re-test reliability coefficients of these two scales and their items were ranged from 0.516 to 0.753 (P < 0.01), indicating the two scales had good re-test reliability; the split-half reliability of SWAT was 0.645, and its Cronbach's alpha coefficient was more than 0.80, all the correlation coefficients between its items score and total score were more than 0.70; as for NASA-TLX, both the split-half reliability and Cronbach's alpha coefficient were more than 0.80, the correlation coefficients between its items score and total score were all more than 0.60 (P < 0.01) except the item of performance. Both scales had good inner consistency. The Pearson correlation coefficient between the two scales was 0.492 (P < 0.01), implying the results of the two scales had good consistency. Factor analysis showed that the two scales had good structure validity. Both SWAT and NASA-TLX have good reliability and validity and may be used as a valid tool to assess mental workload in China after being revised properly.

Pharmaceuticals' sorptions relative to properties of thirteen different soils.

PubMed

Kodešová, Radka; Grabic, Roman; Kočárek, Martin; Klement, Aleš; Golovko, Oksana; Fér, Miroslav; Nikodem, Antonín; Jakšík, Ondřej

2015-04-01

Transport of human and veterinary pharmaceuticals in soils and consequent ground-water contamination are influenced by many factors, including compound sorption on soil particles. Here we evaluate the sorption isotherms for 7 pharmaceuticals on 13 soils, described by Freundlich equations, and assess the impact of soil properties on various pharmaceuticals' sorption on soils. Sorption of ionizable pharmaceuticals was, in many cases, highly affected by soil pH. The sorption coefficient of sulfamethoxazole was negatively correlated to soil pH, and thus positively related to hydrolytic acidity and exchangeable acidity. Sorption coefficients for clindamycin and clarithromycin were positively related to soil pH and thus negatively related to hydrolytic acidity and exchangeable acidity, and positively related to base cation saturation. The sorption coefficients for the remaining pharmaceuticals (trimethoprim, metoprolol, atenolol, and carbamazepine) were also positively correlated with the base cation saturation and cation exchange capacity. Positive correlations between sorption coefficients and clay content were found for clindamycin, clarithromycin, atenolol, and metoprolol. Positive correlations between sorption coefficients and organic carbon content were obtained for trimethoprim and carbamazepine. Pedotransfer rules for predicting sorption coefficients of various pharmaceuticals included hydrolytic acidity (sulfamethoxazole), organic carbon content (trimethoprimand carbamazepine), base cation saturation (atenolol and metoprolol), exchangeable acidity and clay content (clindamycin), and soil active pH and clay content (clarithromycin). Pedotransfer rules, predicting the Freundlich sorption coefficients, could be applied for prediction of pharmaceutical mobility in soils with similar soil properties. Predicted sorption coefficients together with pharmaceutical half-lives and other imputes (e.g., soil-hydraulic, geological, hydro-geological, climatic) may be used for assessing potential ground-water contamination. Copyright © 2014 Elsevier B.V. All rights reserved.

Statistical analysis on multifractal detrended cross-correlation coefficient for return interval by oriented percolation

NASA Astrophysics Data System (ADS)

Deng, Wei; Wang, Jun

2015-06-01

We investigate and quantify the multifractal detrended cross-correlation of return interval series for Chinese stock markets and a proposed price model, the price model is established by oriented percolation. The return interval describes the waiting time between two successive price volatilities which are above some threshold, the present work is an attempt to quantify the level of multifractal detrended cross-correlation for the return intervals. Further, the concept of MF-DCCA coefficient of return intervals is introduced, and the corresponding empirical research is performed. The empirical results show that the return intervals of SSE and SZSE are weakly positive multifractal power-law cross-correlated, and exhibit the fluctuation patterns of MF-DCCA coefficients. The similar behaviors of return intervals for the price model is also demonstrated.

Information-theoretic indices usage for the prediction and calculation of octanol-water partition coefficient.

PubMed

Persona, Marek; Kutarov, Vladimir V; Kats, Boris M; Persona, Andrzej; Marczewska, Barbara

2007-01-01

The paper describes the new prediction method of octanol-water partition coefficient, which is based on molecular graph theory. The results obtained using the new method are well correlated with experimental values. These results were compared with the ones obtained by use of ten other structure correlated methods. The comparison shows that graph theory can be very useful in structure correlation research.

Analytic posteriors for Pearson's correlation coefficient.

PubMed

Ly, Alexander; Marsman, Maarten; Wagenmakers, Eric-Jan

2018-02-01

Pearson's correlation is one of the most common measures of linear dependence. Recently, Bernardo (11th International Workshop on Objective Bayes Methodology, 2015) introduced a flexible class of priors to study this measure in a Bayesian setting. For this large class of priors, we show that the (marginal) posterior for Pearson's correlation coefficient and all of the posterior moments are analytic. Our results are available in the open-source software package JASP.

Validity of a self-administered food frequency questionnaire in the 5-year follow-up survey of the JPHC Study Cohort I to assess sodium and potassium intake: comparison with dietary records and 24-hour urinary excretion level.

PubMed

Sasaki, Satoshi; Ishihara, Junko; Tsugane, Shoichiro

2003-01-01

We compared the intake levels of sodium and potassium assessed with a self-administered semi-quantitative food frequency questionnaire (FFQ) used in a 5-year follow-up survey of the JPHC study and 28-day dietary record (DR), and the corresponding two 24-hour urinary excretion levels (32 men and 57 women) in 3-areas, i.e., Ninohe, Yokote, and Saku Public Health Center areas. The Spearman rank correlation coefficients between dietary sodium assessed with FFQ and the urinary excretion for crude values were 0.24 and -0.10 in men and women, respectively. After adjusting for energy and creatinine, the sodium correlation coefficients were 0.35 and 0.25 in men and women, respectively. The correlation coefficients for crude potassium values were 0.18 and -0.13 in men and women, respectively. After adjusting for energy and creatinine, the potassium correlation coefficients were 0.48 and 0.18 in men and women, respectively in conclusion, a weak correlation was observed both for sodium and potassium after energy and creatinine adjustment in men, whereas no meaningful correlation was observed in women.

A User’s Guide to BISAM (BIvariate SAMple): The Bivariate Data Modeling Program.

DTIC Science & Technology

1983-08-01

method for the null case specified and is then used to form the bivariate density-quantile function as described in section 4. If D(U) in stage...employed assigns average ranks for tied observations. Other methods for assigning ranks to tied observations are often employed but are not attempted...34 €.. . . . .. . .. . . . ,.. . ,•. . . ... *.., .. , - . . . . - - . . .. - -. .. observations will weaken the results obtained since underlying continuous distributions are assumed. One should avoid such situations if possible. Two methods

28 CFR 50.14 - Guidelines on employee selection procedures.

Code of Federal Regulations, 2011 CFR

2011-07-01

... out are: Assumptions of validity based on a procedure's name or descriptive labels; all forms of... relationship (e.g., correlation coefficient) between performance on a selection procedure and one or more... upon a study involving a large number of subjects and has a low correlation coefficient will be subject...

28 CFR 50.14 - Guidelines on employee selection procedures.

Code of Federal Regulations, 2012 CFR

2012-07-01

... out are: Assumptions of validity based on a procedure's name or descriptive labels; all forms of... relationship (e.g., correlation coefficient) between performance on a selection procedure and one or more... upon a study involving a large number of subjects and has a low correlation coefficient will be subject...

28 CFR 50.14 - Guidelines on employee selection procedures.

Code of Federal Regulations, 2014 CFR

2014-07-01

... out are: Assumptions of validity based on a procedure's name or descriptive labels; all forms of... relationship (e.g., correlation coefficient) between performance on a selection procedure and one or more... upon a study involving a large number of subjects and has a low correlation coefficient will be subject...

28 CFR 50.14 - Guidelines on employee selection procedures.

Code of Federal Regulations, 2010 CFR

2010-07-01

... out are: Assumptions of validity based on a procedure's name or descriptive labels; all forms of... relationship (e.g., correlation coefficient) between performance on a selection procedure and one or more... upon a study involving a large number of subjects and has a low correlation coefficient will be subject...

28 CFR 50.14 - Guidelines on employee selection procedures.

Code of Federal Regulations, 2013 CFR

2013-07-01

... out are: Assumptions of validity based on a procedure's name or descriptive labels; all forms of... relationship (e.g., correlation coefficient) between performance on a selection procedure and one or more... upon a study involving a large number of subjects and has a low correlation coefficient will be subject...

Inferential Procedures for Correlation Coefficients Corrected for Attenuation.

ERIC Educational Resources Information Center

Hakstian, A. Ralph; And Others

1988-01-01

A model and computation procedure based on classical test score theory are presented for determination of a correlation coefficient corrected for attenuation due to unreliability. Delta and Monte Carlo method applications are discussed. A power analysis revealed no serious loss in efficiency resulting from correction for attentuation. (TJH)

Bivariate versus multivariate smart spectrophotometric calibration methods for the simultaneous determination of a quaternary mixture of mosapride, pantoprazole and their degradation products.

PubMed

Hegazy, M A; Yehia, A M; Moustafa, A A

2013-05-01

The ability of bivariate and multivariate spectrophotometric methods was demonstrated in the resolution of a quaternary mixture of mosapride, pantoprazole and their degradation products. The bivariate calibrations include bivariate spectrophotometric method (BSM) and H-point standard addition method (HPSAM), which were able to determine the two drugs, simultaneously, but not in the presence of their degradation products, the results showed that simultaneous determinations could be performed in the concentration ranges of 5.0-50.0 microg/ml for mosapride and 10.0-40.0 microg/ml for pantoprazole by bivariate spectrophotometric method and in the concentration ranges of 5.0-45.0 microg/ml for both drugs by H-point standard addition method. Moreover, the applied multivariate calibration methods were able for the determination of mosapride, pantoprazole and their degradation products using concentration residuals augmented classical least squares (CRACLS) and partial least squares (PLS). The proposed multivariate methods were applied to 17 synthetic samples in the concentration ranges of 3.0-12.0 microg/ml mosapride, 8.0-32.0 microg/ml pantoprazole, 1.5-6.0 microg/ml mosapride degradation products and 2.0-8.0 microg/ml pantoprazole degradation products. The proposed bivariate and multivariate calibration methods were successfully applied to the determination of mosapride and pantoprazole in their pharmaceutical preparations.

Meta-Analysis of the Correlation between Apparent Diffusion Coefficient and Standardized Uptake Value in Malignant Disease

PubMed Central

Deng, Shengming; Wu, Zhifang; Wu, Yiwei; Zhang, Wei; Li, Jihui; Dai, Na

2017-01-01

The objective of this meta-analysis is to explore the correlation between the apparent diffusion coefficient (ADC) on diffusion-weighted MR and the standard uptake value (SUV) of 18F-FDG on PET/CT in patients with cancer. Databases such as PubMed (MEDLINE included), EMBASE, and Cochrane Database of Systematic Review were searched for relevant original articles that explored the correlation between SUV and ADC in English. After applying Fisher's r-to-z transformation, correlation coefficient (r) values were extracted from each study and 95% confidence intervals (CIs) were calculated. Sensitivity and subgroup analyses based on tumor type were performed to investigate the potential heterogeneity. Forty-nine studies were eligible for the meta-analysis, comprising 1927 patients. Pooled r for all studies was −0.35 (95% CI: −0.42–0.28) and exhibited a notable heterogeneity (I2 = 78.4%; P < 0.01). In terms of the cancer type subgroup analysis, combined correlation coefficients of ADC/SUV range from −0.12 (lymphoma, n = 5) to −0.59 (pancreatic cancer, n = 2). We concluded that there is an average negative correlation between ADC and SUV in patients with cancer. Higher correlations were found in the brain tumor, cervix carcinoma, and pancreas cancer. However, a larger, prospective study is warranted to validate these findings in different cancer types. PMID:29097924

Meta-Analysis of the Correlation between Apparent Diffusion Coefficient and Standardized Uptake Value in Malignant Disease.

PubMed

Deng, Shengming; Wu, Zhifang; Wu, Yiwei; Zhang, Wei; Li, Jihui; Dai, Na; Zhang, Bin; Yan, Jianhua

2017-01-01

The objective of this meta-analysis is to explore the correlation between the apparent diffusion coefficient (ADC) on diffusion-weighted MR and the standard uptake value (SUV) of 18 F-FDG on PET/CT in patients with cancer. Databases such as PubMed (MEDLINE included), EMBASE, and Cochrane Database of Systematic Review were searched for relevant original articles that explored the correlation between SUV and ADC in English. After applying Fisher's r -to- z transformation, correlation coefficient ( r ) values were extracted from each study and 95% confidence intervals (CIs) were calculated. Sensitivity and subgroup analyses based on tumor type were performed to investigate the potential heterogeneity. Forty-nine studies were eligible for the meta-analysis, comprising 1927 patients. Pooled r for all studies was -0.35 (95% CI: -0.42-0.28) and exhibited a notable heterogeneity ( I 2 = 78.4%; P < 0.01). In terms of the cancer type subgroup analysis, combined correlation coefficients of ADC/SUV range from -0.12 (lymphoma, n = 5) to -0.59 (pancreatic cancer, n = 2). We concluded that there is an average negative correlation between ADC and SUV in patients with cancer. Higher correlations were found in the brain tumor, cervix carcinoma, and pancreas cancer. However, a larger, prospective study is warranted to validate these findings in different cancer types.

American Orthopaedic Foot and Ankle Society ankle-hindfoot scale: A cross-cultural adaptation and validation study from Iran.

PubMed

Vosoughi, Amir Reza; Roustaei, Narges; Mahdaviazad, Hamideh

2018-06-01

The use of valid and reliable outcome rating scales is essential for evaluating the result of different treatments and interventions. The purposes of this study were to translate and culturally adapt the American Orthopaedic Foot and Ankle Society ankle-hindfoot scale (AOFAS-AHFS) into Persian languages and evaluate its psychometric properties. Forward-backward translation and cultural adaptation method were used to develop Persian version of AOFAS-AHFS. From March to July 2016, one hundred consecutive patients with ankle and hindfoot injuries were included. Internal consistency and reproducibility were evaluated using Cronbach's alpha, Spearman's rank correlation coefficient and Intraclass correlation coefficient (ICC) respectively. Construct validity reported which compare the outcome rating scale measurements with Short Form-36 (SF-36), also convergent and discriminant validity evaluated using Spearman's rank correlation coefficient. Mean age (SD) of the patients was 41.95±13.45years. Cronbach's α coefficient, Spearman's rho and ICC values were 0.71, 0.89 and 0.90 respectively. Total score of AOFAS-AHFS and SF-36 domains has a correlation ranged between 0.17-0.55. Spearman's rank correlation coefficient of 0.4 was exceeded by all items with the exception of stability. The Spearman's rank correlation between each item in functional subscales with its own subscales was higher than the correlation between these items and other subscales. Persian version of AOFAS-AHFS provides additional reliable and valid instrument which can be used to assess broad range of patients with foot and ankle disorders that speaking in Persian. However, it seems that the original version of AOFAS-AHFS needs some revisions. Copyright © 2017 European Foot and Ankle Society. Published by Elsevier Ltd. All rights reserved.

Development of a rapid, simple assay of plasma total carotenoids

PubMed Central

2012-01-01

Background Plasma total carotenoids can be used as an indicator of risk of chronic disease. Laboratory analysis of individual carotenoids by high performance liquid chromatography (HPLC) is time consuming, expensive, and not amenable to use beyond a research laboratory. The aim of this research is to establish a rapid, simple, and inexpensive spectrophotometric assay of plasma total carotenoids that has a very strong correlation with HPLC carotenoid profile analysis. Results Plasma total carotenoids from 29 volunteers ranged in concentration from 1.2 to 7.4 μM, as analyzed by HPLC. A linear correlation was found between the absorbance at 448 nm of an alcohol / heptane extract of the plasma and plasma total carotenoids analyzed by HPLC, with a Pearson correlation coefficient of 0.989. The average coefficient of variation for the spectrophotometric assay was 6.5% for the plasma samples. The limit of detection was about 0.3 μM and was linear up to about 34 μM without dilution. Correlations between the integrals of the absorption spectra in the range of carotenoid absorption and total plasma carotenoid concentration gave similar results to the absorbance correlation. Spectrophotometric assay results also agreed with the calculated expected absorbance based on published extinction coefficients for the individual carotenoids, with a Pearson correlation coefficient of 0.988. Conclusion The spectrophotometric assay of total carotenoids strongly correlated with HPLC analysis of carotenoids of the same plasma samples and expected absorbance values based on extinction coefficients. This rapid, simple, inexpensive assay, when coupled with the carotenoid health index, may be useful for nutrition intervention studies, population cohort studies, and public health interventions. PMID:23006902

Bivariate Left-Censored Bayesian Model for Predicting Exposure: Preliminary Analysis of Worker Exposure during the Deepwater Horizon Oil Spill.

PubMed

Groth, Caroline; Banerjee, Sudipto; Ramachandran, Gurumurthy; Stenzel, Mark R; Sandler, Dale P; Blair, Aaron; Engel, Lawrence S; Kwok, Richard K; Stewart, Patricia A

2017-01-01

In April 2010, the Deepwater Horizon oil rig caught fire and exploded, releasing almost 5 million barrels of oil into the Gulf of Mexico over the ensuing 3 months. Thousands of oil spill workers participated in the spill response and clean-up efforts. The GuLF STUDY being conducted by the National Institute of Environmental Health Sciences is an epidemiological study to investigate potential adverse health effects among these oil spill clean-up workers. Many volatile chemicals were released from the oil into the air, including total hydrocarbons (THC), which is a composite of the volatile components of oil including benzene, toluene, ethylbenzene, xylene, and hexane (BTEXH). Our goal is to estimate exposure levels to these toxic chemicals for groups of oil spill workers in the study (hereafter called exposure groups, EGs) with likely comparable exposure distributions. A large number of air measurements were collected, but many EGs are characterized by datasets with a large percentage of censored measurements (below the analytic methods' limits of detection) and/or a limited number of measurements. We use THC for which there was less censoring to develop predictive linear models for specific BTEXH air exposures with higher degrees of censoring. We present a novel Bayesian hierarchical linear model that allows us to predict, for different EGs simultaneously, exposure levels of a second chemical while accounting for censoring in both THC and the chemical of interest. We illustrate the methodology by estimating exposure levels for several EGs on the Development Driller III, a rig vessel charged with drilling one of the relief wells. The model provided credible estimates in this example for geometric means, arithmetic means, variances, correlations, and regression coefficients for each group. This approach should be considered when estimating exposures in situations when multiple chemicals are correlated and have varying degrees of censoring. © The Author 2017. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

Chinese women's participation in fertility discussions.

PubMed

Li, L

1993-01-01

In an attempt to better understand the process through which the family planning (FP) programs and socioeconomic developments in China affect fertility, women's participation in fertility discussions with their husbands are examined as an intermediate factor in a study based on results of a random survey of 6654 ever-married women of reproductive age from 7 cities and 30 counties of Guangdong. First, it must be noted that Chinese couples do have individual choices (albeit quite limited ones) about their fertility; they can choose to follow or ignore government policy or they can choose to remain childless. The present study has 3 major hypotheses: 1) the more a woman is involved in fertility discussions with her husband, the fewer children she will have; 2) urban women with a higher educational status will be more likely to have such discussions; and 3) women who are contacted individually by FP personnel are more likely to be involved in fertility discussions. After a discussion of data collection and variables (number of living children, education of wife and husband, age at marriage, residence, living with parents, contacted by FP personnel, and discussion with husband), the results are presented in terms of zero-order correlation coefficients indicating their relationships. The bivariate analysis supported the hypotheses. Multiple regression analysis showed that age at marriage, education of wives and husbands, FP contacts, and participation in discussions remain significant fertility determinants (but the correlation between fertility and residence becomes trivial). A further regression model indicated that a woman's educational attainment is the most significant positive indication of their participation in fertility discussions. These results imply that as women's status continues to improve in China and the deeply-rooted patriarchal tradition loses hold, increased gender equity and education will influence a fertility decline. FP personnel could also encourage women to actively participate in fertility discussions with their husbands.

Campylobacter spp., Giardia spp., Cryptosporidium spp., Noroviruses, and Indicator Organisms in Surface Water in Southwestern Finland, 2000-2001

PubMed Central

Hörman, Ari; Rimhanen-Finne, Ruska; Maunula, Leena; von Bonsdorff, Carl-Henrik; Torvela, Niina; Heikinheimo, Annamari; Hänninen, Marja-Liisa

2004-01-01

A total of 139 surface water samples from seven lakes and 15 rivers in southwestern Finland were analyzed during five consecutive seasons from autumn 2000 to autumn 2001 for the presence of various enteropathogens (Campylobacter spp., Giardia spp., Cryptosporidium spp., and noroviruses) and fecal indicators (thermotolerant coliforms, Escherichia coli, Clostridium perfringens, and F-RNA bacteriophages) and for physicochemical parameters (turbidity and temperature); this was the first such systematic study. Altogether, 41.0% (57 of 139) of the samples were positive for at least one of the pathogens; 17.3% were positive for Campylobacter spp. (45.8% of the positive samples contained Campylobacter jejuni, 25.0% contained Campylobacter lari, 4.2% contained Campylobacter coli, and 25.0% contained Campylobacter isolates that were not identified), 13.7% were positive for Giardia spp., 10.1% were positive for Cryptosporidium spp., and 9.4% were positive for noroviruses (23.0% of the positive samples contained genogroup I and 77.0% contained genogroup II). The samples were positive for enteropathogens significantly (P < 0.05) less frequently during the winter season than during the other sampling seasons. No significant differences in the prevalence of enteropathogens were found when rivers and lakes were compared. The presence of thermotolerant coliforms, E. coli, and C. perfringens had significant bivariate nonparametric Spearman's rank order correlation coefficients (P < 0.001) with samples that were positive for one or more of the pathogens analyzed. The absence of these indicators in a logistic regression model was found to have significant predictive value (odds ratios, 1.15 × 108, 7.57, and 2.74, respectively; P < 0.05) for a sample that was negative for the pathogens analyzed. There were no significant correlations between counts or count levels for thermotolerant coliforms or E. coli or the presence of F-RNA phages and pathogens in the samples analyzed. PMID:14711629

[Tobacco quality analysis of industrial classification of different years using near-infrared (NIR) spectrum].

PubMed

Wang, Yi; Xiang, Ma; Wen, Ya-Dong; Yu, Chun-Xia; Wang, Luo-Ping; Zhao, Long-Lian; Li, Jun-Hui

2012-11-01

In this study, tobacco quality analysis of main Industrial classification of different years was carried out applying spectrum projection and correlation methods. The group of data was near-infrared (NIR) spectrum from Hongta Tobacco (Group) Co., Ltd. 5730 tobacco leaf Industrial classification samples from Yuxi in Yunnan province from 2007 to 2010 year were collected using near infrared spectroscopy, which from different parts and colors and all belong to tobacco varieties of HONGDA. The conclusion showed that, when the samples were divided to two part by the ratio of 2:1 randomly as analysis and verification sets in the same year, the verification set corresponded with the analysis set applying spectrum projection because their correlation coefficients were above 0.98. The correlation coefficients between two different years applying spectrum projection were above 0.97. The highest correlation coefficient was the one between 2008 and 2009 year and the lowest correlation coefficient was the one between 2007 and 2010 year. At the same time, The study discussed a method to get the quantitative similarity values of different industrial classification samples. The similarity and consistency values were instructive in combination and replacement of tobacco leaf blending.

Increased correlation coefficient between the written test score and tutors' performance test scores after training of tutors for assessment of medical students during problem-based learning course in Malaysia.

PubMed

Jaiprakash, Heethal; Min, Aung Ko Ko; Ghosh, Sarmishtha

2016-03-01

This paper is aimed at finding if there was a change of correlation between the written test score and tutors' performance test scores in the assessment of medical students during a problem-based learning (PBL) course in Malaysia. This is a cross-sectional observational study, conducted among 264 medical students in two groups from November 2010 to November 2012. The first group's tutors did not receive tutor training; while the second group's tutors were trained in the PBL process. Each group was divided into high, middle and low achievers based on their end-of-semester exam scores. PBL scores were taken which included written test scores and tutors' performance test scores. Pearson correlation coefficient was calculated between the two kinds of scores in each group. The correlation coefficient between the written scores and tutors' scores in group 1 was 0.099 (p<0.001) and for group 2 was 0.305 (p<0.001). The higher correlation coefficient in the group where tutors received the PBL training reinforces the importance of tutor training before their participation in the PBL course.

p-capture reaction cycles in rotating massive stars and their impact on elemental abundances in globular cluster stars: A case study of O, Na and Al

NASA Astrophysics Data System (ADS)

Mahanta, Upakul; Goswami, Aruna; Duorah, Hiralal; Duorah, Kalpana

2017-08-01

Elemental abundance patterns of globular cluster stars can provide important clues for understanding cluster formation and early chemical evolution. The origin of the abundance patterns, however, still remains poorly understood. We have studied the impact of p-capture reaction cycles on the abundances of oxygen, sodium and aluminium considering nuclear reaction cycles of carbon-nitrogen-oxygen-fluorine, neon-sodium and magnesium-aluminium in massive stars in stellar conditions of temperature range 2×107 to 10×107 K and typical density of 102 gm cc-1. We have estimated abundances of oxygen, sodium and aluminium with respect to Fe, which are then assumed to be ejected from those stars because of rotation reaching a critical limit. These ejected abundances of elements are then compared with their counterparts that have been observed in some metal-poor evolved stars, mainly giants and red giants, of globular clusters M3, M4, M13 and NGC 6752. We observe an excellent agreement with [O/Fe] between the estimated and observed abundance values for globular clusters M3 and M4 with a correlation coefficient above 0.9 and a strong linear correlation for the remaining two clusters with a correlation coefficient above 0.7. The estimated [Na/Fe] is found to have a correlation coefficient above 0.7, thus implying a strong correlation for all four globular clusters. As far as [Al/Fe] is concerned, it also shows a strong correlation between the estimated abundance and the observed abundance for globular clusters M13 and NGC 6752, since here also the correlation coefficient is above 0.7 whereas for globular cluster M4 there is a moderate correlation found with a correlation coefficient above 0.6. Possible sources of these discrepancies are discussed.

Robust Correlation Analyses: False Positive and Power Validation Using a New Open Source Matlab Toolbox

PubMed Central

Pernet, Cyril R.; Wilcox, Rand; Rousselet, Guillaume A.

2012-01-01

Pearson’s correlation measures the strength of the association between two variables. The technique is, however, restricted to linear associations and is overly sensitive to outliers. Indeed, a single outlier can result in a highly inaccurate summary of the data. Yet, it remains the most commonly used measure of association in psychology research. Here we describe a free Matlab(R) based toolbox (http://sourceforge.net/projects/robustcorrtool/) that computes robust measures of association between two or more random variables: the percentage-bend correlation and skipped-correlations. After illustrating how to use the toolbox, we show that robust methods, where outliers are down weighted or removed and accounted for in significance testing, provide better estimates of the true association with accurate false positive control and without loss of power. The different correlation methods were tested with normal data and normal data contaminated with marginal or bivariate outliers. We report estimates of effect size, false positive rate and power, and advise on which technique to use depending on the data at hand. PMID:23335907

Robust correlation analyses: false positive and power validation using a new open source matlab toolbox.

PubMed

Pernet, Cyril R; Wilcox, Rand; Rousselet, Guillaume A

2012-01-01

Pearson's correlation measures the strength of the association between two variables. The technique is, however, restricted to linear associations and is overly sensitive to outliers. Indeed, a single outlier can result in a highly inaccurate summary of the data. Yet, it remains the most commonly used measure of association in psychology research. Here we describe a free Matlab((R)) based toolbox (http://sourceforge.net/projects/robustcorrtool/) that computes robust measures of association between two or more random variables: the percentage-bend correlation and skipped-correlations. After illustrating how to use the toolbox, we show that robust methods, where outliers are down weighted or removed and accounted for in significance testing, provide better estimates of the true association with accurate false positive control and without loss of power. The different correlation methods were tested with normal data and normal data contaminated with marginal or bivariate outliers. We report estimates of effect size, false positive rate and power, and advise on which technique to use depending on the data at hand.

An Exploratory Analysis of Factors Affecting Participation in Air Force Knowledge Now Communities of Practice

DTIC Science & Technology

2004-03-01

reliability coefficients are presented in chapter four in the factor analysis section. Along with Crobach’s Alpha coefficients, the Kaiser - Meyer - Olkin ...the pattern of correlation coefficients > 0.300 in the correlation matrix • Kaiser - Meyer - Olkin Measure of Sampling Adequacy (MSA) > 0.700 • Bartlett’s...exploratory factor analysis. The Kaiser - Meyer - Olkin measure of sampling adequacy yielded a value of .790, and Bartlett’s test of sphericity yielded a

Using the Bivariate Dale Model to jointly estimate predictors of frequency and quantity of alcohol use.

PubMed

McMillan, Garnett P; Hanson, Tim; Bedrick, Edward J; Lapham, Sandra C

2005-09-01

This study demonstrates the usefulness of the Bivariate Dale Model (BDM) as a method for estimating the relationship between risk factors and the quantity and frequency of alcohol use, as well as the degree of association between these highly correlated drinking measures. The BDM is used to evaluate childhood sexual abuse, along with age and gender, as risk factors for the quantity and frequency of beer consumption in a sample of driving-while-intoxicated (DWI) offenders (N = 1,964; 1,612 men). The BDM allows one to estimate the relative odds of drinking up to each level of ordinal-scaled quantity and frequency of alcohol use, as well as model the degree of association between quantity and frequency of alcohol consumption as a function of covariates. Individuals who experienced childhood sexual abuse have increased risks of higher quantity and frequency of beer consumption. History of childhood sexual abuse has a greater effect on women, causing them to drink higher quantities of beer per drinking occasion. The BDM is a useful method for evaluating predictors of the quantity-frequency of alcohol consumption. SAS macrocode for fitting the BDM model is provided.