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Articles 151 - 180 of 285
Full-Text Articles in Statistics and Probability
Racial Disparities In Mortality Risks In A Sample Of The U.S. Medicare Population, Yijie Zhou, Francesca Dominici, Thomas A. Louis
Racial Disparities In Mortality Risks In A Sample Of The U.S. Medicare Population, Yijie Zhou, Francesca Dominici, Thomas A. Louis
Johns Hopkins University, Dept. of Biostatistics Working Papers
Racial disparities in mortality risks adjusted by socioeconomic status (SES) are not well understood. To add to the understanding of racial disparities, we construct and analyze a data set that links, at individual and zip code levels, three government databases: Medicare, Medicare Current Beneficiary Survey and U.S. Census. Our study population includes more than 4 million Medicare enrollees residing in 2095 zip codes in the Northeast region of U.S. We develop hierarchical models to estimate Black-White disparity in risk of death, adjusted by both individual-level and zip codelevel income. We define population-level attributable risk (AR), relative attributable risk (RAR) and …
Adjusting For Covariates In Studies Of Diagnostic, Screening, Or Prognostic Markers: An Old Concept In A New Setting, Holly Janes, Margaret Pepe
Adjusting For Covariates In Studies Of Diagnostic, Screening, Or Prognostic Markers: An Old Concept In A New Setting, Holly Janes, Margaret Pepe
UW Biostatistics Working Paper Series
The concept of covariate adjustment is well established in therapeutic and etiologic studies. However, it has received little attention in the growing area of medical research devoted to the development of markers for disease diagnosis, screening, or prognosis, where classification accuracy, rather than association, is of primary interest. In this paper, we demonstrate the need for covariate adjustment in studies of classification accuracy, discuss methods for adjusting for covariates, and distinguish covariate adjustment from several other related but fundamentally different uses for covariates. We draw analogies and contrasts throughout with studies of association.
Epidemic Of Lung Cancer Or Artifact Of Classification In The State Of Kentucky?, Beatrice Simo
Epidemic Of Lung Cancer Or Artifact Of Classification In The State Of Kentucky?, Beatrice Simo
Electronic Theses and Dissertations
Lung cancer remains the leading cause of cancer deaths in the United States despite public health campaigns aimed at reducing its rate of mortality. Kentucky is the state with the highest lung cancer incidence and mortality. This study aims to assess the impact of misclassification of cause of death from Lung Cancer in Kentucky for the period 1979 to 2002. We will examine the potential competing classification of death for two other smoking-related diseases, Chronic Obstructive Pulmonary Disease (COPD) and Emphysema. Age-adjusted mortality rates for these diseases for white males were obtained from the National Center for Health Statistics. There …
A Case Study In Pharmacologic Imaging Using Principal Curves In Single Photon Emission Computed Tomography, Brian S. Caffo, Ciprian M. Crainiceanu, Lijuan Deng, Craig W. Hendrix
A Case Study In Pharmacologic Imaging Using Principal Curves In Single Photon Emission Computed Tomography, Brian S. Caffo, Ciprian M. Crainiceanu, Lijuan Deng, Craig W. Hendrix
Johns Hopkins University, Dept. of Biostatistics Working Papers
In this manuscript we are concerned with functional imaging of the colon to assess the kinetics of a microbicide lubricant. The overarching goal is to understand the distribution of the lubricant in the colon. Such information is crucial for understanding the potential impact of the microbicide on HIV viral transmission. The experiment was conducted by imaging a radiolabeled lubricant distributed in the subject’s colon. The tracer imaging was conducted via single photon emission computed tomography (SPECT), a non-invasive, in-vivo functional imaging technique. We develop a novel principal curve algorithm to construct a three dimensional curve through the colon images. The …
Review Of The Maximum Likelihood Functions For Right Censored Data. A New Elementary Derivation., Stefano Patti, Elia Biganzoli, Patrizia Boracchi
Review Of The Maximum Likelihood Functions For Right Censored Data. A New Elementary Derivation., Stefano Patti, Elia Biganzoli, Patrizia Boracchi
COBRA Preprint Series
Censoring is a well known feature recurrent in the analysis of lifetime data, occurring in the model when exact lifetimes can be collected for only a representative portion of the surveyed individuals. If lifetimes are known only to exceed some given values, it is referred to as right censoring. In this paper we propose a systematization and a new derivation of the likelihood function for right censored sampling schemes; calculations are reported and assumptions are carefully stated. The sampling schemes considered (Type I, II and Random Censoring) give rise to the same ML function. Only the knowledge of elementary probability …
Ecologic Studies Revisited, Jon Wakefield
Ecologic Studies Revisited, Jon Wakefield
UW Biostatistics Working Paper Series
Ecologic studies use data aggregated over groups, rather than data on individuals. Such studies are popular since they may make use of existing data bases, and can offer large exposure variation if based on broad geographical areas. Unfortunately the aggregation of data that defines ecologic studies results in a loss of information that can lead to ecologic bias. Specifically, ecologic bias arises from the inability of ecologic data to characterize within-area variability in exposures and confounders. We describe in detail particular forms of ecologic bias so that their potential impact on any particular study may be assessed. The only way …
Gamma Generalized Linear Models For Pharmacokinetic Data, Ruth Salway, Jon Wakefield
Gamma Generalized Linear Models For Pharmacokinetic Data, Ruth Salway, Jon Wakefield
UW Biostatistics Working Paper Series
This paper considers the modeling of single dose pharmacoki- netic data. Traditionally, so-called compartmental models have been used to analyze such data. Unfortunately the mean function of such models are sums of exponentials for which inference and computation may not be straightfor- ward. We present an alternative to these models based on generalized linear models, for which desirable statistical properties exist, with a logarithmic link and gamma distribution. The latter has a constant coefficient of variation which is often appropriate for pharmacokinetic data. Inference is convenient from either a likelihood or a Bayesian perspective. We consider models for both single …
Evaluating A Group Sequential Design In The Setting Of Nonproportional Hazards, Daniel L. Gillen, Scott S. Emerson
Evaluating A Group Sequential Design In The Setting Of Nonproportional Hazards, Daniel L. Gillen, Scott S. Emerson
UW Biostatistics Working Paper Series
Group sequential methods have been widely described and implemented in a clinical trial setting where parametric and semiparametric models are deemed suitable. In these situations, the evaluation of the operating characteristics of a group sequential stopping rule remains relatively straightforward. However, in the presence of nonproportional hazards survival data nonparametric methods are often used, and the evaluation of stopping rules is no longer a trivial task. Specifically, nonparametric test statistics do not necessarily correspond to a parameter of clinical interest, thus making it difficult to characterize alternatives at which operating characteristics are to be computed. We describe an approach for …
Ordinal Versions Of Coefficients Alpha And Theta For Likert Rating Scales, Bruno D. Zumbo, Anne M. Gadermann, Cornelia Zeisser
Ordinal Versions Of Coefficients Alpha And Theta For Likert Rating Scales, Bruno D. Zumbo, Anne M. Gadermann, Cornelia Zeisser
Journal of Modern Applied Statistical Methods
Two new reliability indices, ordinal coefficient alpha and ordinal coefficient theta, are introduced. A simulation study was conducted in order to compare the new ordinal reliability estimates to each other and to coefficient alpha with Likert data. Results indicate that ordinal coefficients alpha and theta are consistently suitable estimates of the theoretical reliability, regardless of the magnitude of the theoretical reliability, the number of scale points, and the skewness of the scale point distributions. In contrast, coefficient alpha is in general a negatively biased estimate of reliability. The use of ordinal coefficients alpha and theta as alternatives to coefficient alpha …
Lq-Moments For Statistical Analysis Of Extreme Events, Ani Shabri, Abdul Aziz Jemain
Lq-Moments For Statistical Analysis Of Extreme Events, Ani Shabri, Abdul Aziz Jemain
Journal of Modern Applied Statistical Methods
Statistical analysis of extremes is conducted for predicting large return periods events. LQ-moments that are based on linear combinations are reviewed for characterizing the upper quantiles of distributions and larger events in data. The LQ-moments method is presented based on a new quick estimator using five points quantiles and the weighted kernel estimator to estimate the parameters of the generalized extreme value (GEV) distribution. Monte Carlo methods illustrate the performance of LQ-moments in fitting the GEV distribution to both GEV and non-GEV samples. The proposed estimators of the GEV distribution were compared with conventional L-moments and LQ-moments based on linear …
Jmasm 26: Hettmansperger And Mckean Linear Model Aligned Rank Test For The Single Covariate And One-Way Ancova Case (Sas), Paul A. Nakonezny, Robert D. Shull
Jmasm 26: Hettmansperger And Mckean Linear Model Aligned Rank Test For The Single Covariate And One-Way Ancova Case (Sas), Paul A. Nakonezny, Robert D. Shull
Journal of Modern Applied Statistical Methods
A SAS program (SAS 9.1.3 release, SAS Institute, Cary, N.C.) is presented to implement the Hettmansperger and McKean (1983) linear model aligned rank test (nonparametric ANCOVA) for the single covariate and one-way ANCOVA case. As part of this program, SAS code is also provided to derive the residuals from the regression of Y on X (which is step 1 in the Hettmansperger and McKean procedure) using either ordinary least squares regression (proc reg in SAS) or robust regression with MM estimation (proc robustreg in SAS).
Reliability And Statistical Power: How Measurement Fallibility Affects Power And Required Sample Sizes For Several Parametric And Nonparametric Statistics, Gibbs Y. Kanyongo, Gordon P. Brook, Lydia Kyei-Blankson, Gulsah Gocmen
Reliability And Statistical Power: How Measurement Fallibility Affects Power And Required Sample Sizes For Several Parametric And Nonparametric Statistics, Gibbs Y. Kanyongo, Gordon P. Brook, Lydia Kyei-Blankson, Gulsah Gocmen
Journal of Modern Applied Statistical Methods
The relationship between reliability and statistical power is considered, and tables that account for reduced reliability are presented. A series of Monte Carlo experiments were conducted to determine the effect of changes in reliability on parametric and nonparametric statistical methods, including the paired samples dependent t test, pooled-variance independent t test, one-way analysis of variance with three levels, Wilcoxon signed-rank test for paired samples, and Mann-Whitney-Wilcoxon test for independent groups. Power tables were created that illustrate the reduction in statistical power from decreased reliability for given sample sizes. Sample size tables were created to provide the approximate sample sizes required …
On Flexible Tests Of Independence And Homoscedasticity, Rand R. Wilcox
On Flexible Tests Of Independence And Homoscedasticity, Rand R. Wilcox
Journal of Modern Applied Statistical Methods
Consider the nonparametric regression model Y = m(X) + τ(X)ε , where X and ε are independent random variables, ε has a mean of zero and variance σ2, τ is some unknown function used to model heteroscedasticity, and m(X) is an unknown function reflecting some conditional measure of location associated with Y, given X. Detecting dependence, by testing the hypothesis that m(X) does not vary with X, has the potential of being more sensitive to a wider range of associations compared to using Pearson's correlation. This note has two goals. The first is to point …
Using The Fractional Imputation Methodology To Evaluate Variance Due To Hot Deck Imputation In Survey Data, Adriana Pérez
Using The Fractional Imputation Methodology To Evaluate Variance Due To Hot Deck Imputation In Survey Data, Adriana Pérez
Journal of Modern Applied Statistical Methods
This article examines empirically the effect on the variance estimate due to the use of hot deck imputation with a nearest neighbor donor in comparison with the pairwise fractional hot deck imputation methodology in the 1999 Survey of Doctorate Recipients.
A Comparison Of Eight Shrinkage Formulas Under Extreme Conditions, David A. Walker
A Comparison Of Eight Shrinkage Formulas Under Extreme Conditions, David A. Walker
Journal of Modern Applied Statistical Methods
The performance of various shrinkage formulas for estimating the population squared multiple correlation coefficient (ρ2) were compared under extreme conditions often found in educational research with small sample sizes of 10, 15, 20, 25, 30 and regressor variates ranging from 2 to 4. A new formula for estimating ρ2, Adj R2 DW, was examined in terms of its performance under various conditions of N, p, ρ2, along with its bias properties and standard error estimates. The two shrinkage formulas that performed most consistently were the Claudy (Adj R2 C) and Walker (Adj R2 DW)
Examining Cronbach Alpha, Theta, Omega Reliability Coefficients According To Sample Size, Ilker Ercan, Berna Yazici, Deniz Sigirli, Bulent Ediz, Ismet Kan
Examining Cronbach Alpha, Theta, Omega Reliability Coefficients According To Sample Size, Ilker Ercan, Berna Yazici, Deniz Sigirli, Bulent Ediz, Ismet Kan
Journal of Modern Applied Statistical Methods
Differentiations according to the sample size of different reliability coefficients are examined. It is concluded that the estimates obtained by Cronbach alpha and teta coefficients are not related with the sample size, even the estimates obtained from the small samples can represent the population parameter. However, the Omega coefficient requires large sample sizes.
Analyses Of Unbalanced Groups-Versus-Individual Research Designs Using Three Alternative Approximate Degrees Of Freedom Tests: Test Development And Type I Error Rates, Stephanie Wehry, James Algina
Analyses Of Unbalanced Groups-Versus-Individual Research Designs Using Three Alternative Approximate Degrees Of Freedom Tests: Test Development And Type I Error Rates, Stephanie Wehry, James Algina
Journal of Modern Applied Statistical Methods
Three approximate degrees of freedom quasi-F tests of treatment effectiveness were developed for use in research designs when one treatment is individually delivered and the other is delivered to individuals nested in groups of unequal size. Imbalance in the data was studied from the prospective of subject attrition. The results indicated the test that best controls the Type I error rate depends on the number of groups in the group-administered treatment but does not depend on the subject attrition rates included in the study.
Another Look At The Confidence Intervals For The Noncentral T Distribution, Bruno Lecoutre
Another Look At The Confidence Intervals For The Noncentral T Distribution, Bruno Lecoutre
Journal of Modern Applied Statistical Methods
An alternative approach to the computation of confidence intervals for the noncentrality parameter of the Noncentral t distribution is proposed. It involves the percent points of a statistical distribution. This conceptual improvement renders the technical process for deriving the limits more comprehensible. Accurate approximations can be derived and easily used.
Better Binomial Confidence Intervals, James F. Reed Iii
Better Binomial Confidence Intervals, James F. Reed Iii
Journal of Modern Applied Statistical Methods
The construction of a confidence interval for a binomial parameter is a basic analysis in statistical inference. Most introductory statistics textbook authors present the binomial confidence interval based on the asymptotic normality of the sample proportion and estimating the standard error - the Wald method. For the one sample binomial confidence interval the Clopper-Pearson exact method has been regarded as definitive as it eliminates both overshoot and zero width intervals. The Clopper-Pearson exact method is the most conservative and is unquestionably a better alternative to the Wald method. Other viable alternatives include Wilson's Score, the Agresti-Coull method, and the Borkowf …
A Spline-Based Lack-Of-Fit Test For Independent Variable Effect, Chin-Shang Li, Wanzhu Tu
A Spline-Based Lack-Of-Fit Test For Independent Variable Effect, Chin-Shang Li, Wanzhu Tu
Journal of Modern Applied Statistical Methods
In regression analysis of count data, independent variables are often modeled by their linear effects under the assumption of log-linearity. In reality, the validity of such an assumption is rarely tested, and its use is at times unjustifiable. A lack-of-fit test is proposed for the adequacy of a postulated functional form of an independent variable within the framework of semiparametric Poisson regression models based on penalized splines. It offers added flexibility in accommodating the potentially non-loglinear effect of the independent variable. A likelihood ratio test is constructed for the adequacy of the postulated parametric form, for example log-linearity, of the …
A Comparison Of One-High-Threshold And Two-High-Threshold Multinomial Models Of Source Monitoring, Mahesh Menon, Todd S. Woodward
A Comparison Of One-High-Threshold And Two-High-Threshold Multinomial Models Of Source Monitoring, Mahesh Menon, Todd S. Woodward
Journal of Modern Applied Statistical Methods
A data simulation study comparing the one-high-threshold (1HT) and two-high-threshold (2HT) multinomial models suggested that 2HT models are more likely to misestimate the underlying parameter values, due to inflation of some parameters (b and d), and deflation of others (D).
Multinomial Logistic Regression Model For The Inferential Risk Age Groups For Infection Caused By Vibrio Cholerae In Kolkata, India, Krishnan Rajendran, Thandavarayan Ramamurthy, Dipika Sur
Multinomial Logistic Regression Model For The Inferential Risk Age Groups For Infection Caused By Vibrio Cholerae In Kolkata, India, Krishnan Rajendran, Thandavarayan Ramamurthy, Dipika Sur
Journal of Modern Applied Statistical Methods
Multinomial Logistic Regression (MLR) modeling is an effective approach for categorical outcomes, as compared with discriminant function analysis and log-linear models for profiling individual category of dependent variable. To explore the yearly change of inferential age groups of acute diarrhoeal patients infected with Vibrio cholerae during 1996-2000 by MLR, systematic sampling data were generated from an active surveillance study. Among 1330 V.cholerae infected cases, the predominant age category was up to 5 years accounting for 478 (30.5%) cases. The independent variables V.cholerae O1 (p<0.001) and non-O1 and non-O139 (p < 0.001) were significantly associated with children under 5 years age group. V.cholerae O139 inferential age group was > 40 years. The infection mediated by V.cholerae O1 had significantly decreasing trend Exp(B) year wise from …
Estimation Of Risk For Developing Cardiac Problem In Patients Of Type 2 Diabetes As Obtained By The Technique Of Density Estimation, Ajit Mukherjee, Ajit Mathur, Rakesh Mittal
Estimation Of Risk For Developing Cardiac Problem In Patients Of Type 2 Diabetes As Obtained By The Technique Of Density Estimation, Ajit Mukherjee, Ajit Mathur, Rakesh Mittal
Journal of Modern Applied Statistical Methods
High levels of cholesterol and triglyceride are known to be strongly associated with development of cardiac problem in patients of type 2 diabetes. In a hospital-based study, patients showing ECG positive were compared with those who were not. The observations on cholesterol and triglyceride were considered for estimation of risk for developing the cardiac problem. The technique of density estimation employing Epanechnikov kernel was used for estimating bivariate probability density functions with respect to observations on cholesterol and triglyceride of the two groups. Using the odds form of Bayes’ rule, the estimates of posterior odds were computed.
Effects Of Physical Activity On Psychological Change In Advanced Age: A Multivariate Meta-Analysis, Meng-Jia Wu, Betsy Jane Becker, Yael Netz
Effects Of Physical Activity On Psychological Change In Advanced Age: A Multivariate Meta-Analysis, Meng-Jia Wu, Betsy Jane Becker, Yael Netz
Journal of Modern Applied Statistical Methods
An example of multivariate meta-analysis is demonstrated by synthesizing the treatment effects of exercise of 15 groups on six mood state changes in elders measured by the Profile of Mood States (POMS) scale. Two different methods were used to analyze this multivariate dataset. The SAS codes for two set of the analyses were provided. Results showed that exercise has a modest and positive impact on elders mood change.
Application Of A New Procedure For Power Analysis And Comparison Of The Adjusted Univariate And Multivariate Tests In Repeated Measures Designs, Sean W. Mulvenon, M. Austin Betz, Kening Wang, Bruno D. Zumbo
Application Of A New Procedure For Power Analysis And Comparison Of The Adjusted Univariate And Multivariate Tests In Repeated Measures Designs, Sean W. Mulvenon, M. Austin Betz, Kening Wang, Bruno D. Zumbo
Journal of Modern Applied Statistical Methods
A relationship between the multivariate and univariate noncentrality parameters in repeated measures designs was developed for the purpose of assessing the relative power of the univariate and multivariate approaches. An application is provided examining the use of repeated measures designs to evaluate student achievement in a K-12 school system
The Effects Of Heteroscedasticity On Tests Of Equivalence, Jamie A. Gruman, Robert A. Cribbie, Chantal A. Arpin-Cribbie
The Effects Of Heteroscedasticity On Tests Of Equivalence, Jamie A. Gruman, Robert A. Cribbie, Chantal A. Arpin-Cribbie
Journal of Modern Applied Statistical Methods
Tests of equivalence, which are designed to assess the similarity of group means, are becoming more popular, yet very little is known about the statistical properties of these tests. Monte Carlo methods are used to compare the test of equivalence proposed by Schuirmann with modified tests of equivalence that incorporate a heteroscedastic error term. It was found that the latter were more accurate than the Schuirmann test in detecting equivalence when sample sizes and variances were unequal.
On The Properties Of Beta-Gamma Distribution, Lingji Kong, Carl Lee, J.H. Sepanski
On The Properties Of Beta-Gamma Distribution, Lingji Kong, Carl Lee, J.H. Sepanski
Journal of Modern Applied Statistical Methods
A class of generalized gamma distribution called the beta-gamma distribution is proposed. Some of its properties are examined. Its shape can be reversed J-shaped, unimodal, or bimodal. Reliability and hazard functions are also derived, and applications are discussed.
On The Product Of Maxwell And Rice Random Variables, M. Shakil, B. M. Golam Kibria
On The Product Of Maxwell And Rice Random Variables, M. Shakil, B. M. Golam Kibria
Journal of Modern Applied Statistical Methods
The distributions of the product of independent random variables arise in many applied problems. These have been extensively studied by many researchers. In this paper, the exact distributions of the product |XY| have been derived when X and Y are Maxwell and Rice random variables respectively, and are distributed independently of each other. The associated cdfs, pdfs, and kth moments have been given.
Optimal Lp-Metric For Minimizing Powered Deviations In Regression, Stan Lipovetsky
Optimal Lp-Metric For Minimizing Powered Deviations In Regression, Stan Lipovetsky
Journal of Modern Applied Statistical Methods
Minimizations by least squares or by least absolute deviations are well known criteria in regression modeling. In this work the criterion of generalized mean by powered deviations is suggested. If the parameter of the generalized mean equals one or two, the fitting corresponds to the least absolute or the least squared deviations, respectively. Varying the power parameter yields an optimum value for the objective with a minimum possible residual error. Estimation of a most favorable value of the generalized mean parameter shows that it almost does not depend on data. The optimal power always occurs to be close to 1.7, …
A Comparison Of Two Rank Tests For Repeated Measure Designs, Tian Tian, Rand R. Wilcox
A Comparison Of Two Rank Tests For Repeated Measure Designs, Tian Tian, Rand R. Wilcox
Journal of Modern Applied Statistical Methods
This article compares the small-sample properties of the Agresti-Pendergast and the ATS rank-based method, as described in Brunner, Domh, and Langer (2002), for comparing J dependent groups. The results indicate that the Type I error of the Agresti-Pendergast method is more conservative when J = 2 , but under most conditions, the ATS method performs best in terms of both Type I errors and power.