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Articles 1 - 6 of 6
Full-Text Articles in Public Health
Evaluating The Efficiency Of Treatment Comparison In Crossover Design By Allocating Subjects Based On Ranked Auxiliary Variable, Yisong Huang, Hani Samawi, Robert Vogel, Jingjing Yin, Worlanyo E. Gato, Daniel Linder
Evaluating The Efficiency Of Treatment Comparison In Crossover Design By Allocating Subjects Based On Ranked Auxiliary Variable, Yisong Huang, Hani Samawi, Robert Vogel, Jingjing Yin, Worlanyo E. Gato, Daniel Linder
Biostatistics Faculty Publications
The validity of statistical inference depends on proper randomization methods. However, even with proper randomization, we can have imbalanced with respect to important characteristics. In this paper, we introduce a method based on ranked auxiliary variables for treatment allocation in crossover designs using Latin squares models. We evaluate the improvement of the efficiency in treatment comparisons using the proposed method. Our simulation study reveals that our proposed method provides a more powerful test compared to simple randomization with the same sample size. The proposed method is illustrated by conducting an experiment to compare two different concentrations of titanium dioxide nanofiber …
Estimation Of P(X > Y) When X And Y Are Dependent Random Variables Using Different Bivariate Sampling Schemes, Hani M. Samawi, Amal Helu, Haresh Rochani, Jingjing Yin, Daniel Linder
Estimation Of P(X > Y) When X And Y Are Dependent Random Variables Using Different Bivariate Sampling Schemes, Hani M. Samawi, Amal Helu, Haresh Rochani, Jingjing Yin, Daniel Linder
Biostatistics Faculty Publications
The stress-strength models have been intensively investigated in the literature in regards of estimating the reliability θ = P (X > Y) using parametric and nonparametric approaches under different sampling schemes when X and Y are independent random variables. In this paper, we consider the problem of estimating θ when (X, Y) are dependent random variables with a bivariate underlying distribution. The empirical and kernel estimates of θ = P (X > Y), based on bivariate ranked set sampling (BVRSS) are considered, when (X, Y) are paired dependent continuous random variables. The estimators obtained are compared to their counterpart, bivariate simple random …
Improved Estimation Of Optimal Cut-Off Point Associated With Youden Index Using Ranked Set Sampling, Jingjing Yin, Hani M. Samawi, Daniel Linder
Improved Estimation Of Optimal Cut-Off Point Associated With Youden Index Using Ranked Set Sampling, Jingjing Yin, Hani M. Samawi, Daniel Linder
Biostatistics Faculty Publications
A diagnostic cut-off point of a biomarker measurement is needed for classifying a random subject to be either diseased or healthy. However, the cut-off point is usually unknown and needs to be estimated by some optimization criteria. One important criterion is the Youden index, which has been widely adopted in practice. The Youden index, which is defined as the maximum of (sensitivity + specificity −1), directly measures the largest total diagnostic accuracy a biomarker can achieve. Therefore, it is desirable to estimate the optimal cut-off point associated with the Youden index. Sometimes, taking the actual measurements of a biomarker is …
Uncovering Local Trends In Genetic Effects Of Multiple Phenotypes Via Functional Linear Models, Olga A. Vsevolozhskaya, Dmitri V. Zaykin, David A. Barondess, Xiaoren Tong, Sneha Jadhav, Qing Lu
Uncovering Local Trends In Genetic Effects Of Multiple Phenotypes Via Functional Linear Models, Olga A. Vsevolozhskaya, Dmitri V. Zaykin, David A. Barondess, Xiaoren Tong, Sneha Jadhav, Qing Lu
Biostatistics Faculty Publications
Recent technological advances equipped researchers with capabilities that go beyond traditional genotyping of loci known to be polymorphic in a general population. Genetic sequences of study participants can now be assessed directly. This capability removed technology-driven bias toward scoring predominantly common polymorphisms and let researchers reveal a wealth of rare and sample-specific variants. Although the relative contributions of rare and common polymorphisms to trait variation are being debated, researchers are faced with the need for new statistical tools for simultaneous evaluation of all variants within a region. Several research groups demonstrated flexibility and good statistical power of the functional linear …
Motorcycle Helmet Effectiveness In Reducing Head, Face And Brain Injuries By State And Helmet Law, Cody S. Olsen, Andrea M. Thomas, Michael Singleton, Anna M. Gaichas, Tracy J. Smith, Gary A. Smith, Justin Peng, Michael J. Bauer, Ming Qu, Denise Yeager, Timothy Kerns, Cynthia Burch, Lawrence J. Cook
Motorcycle Helmet Effectiveness In Reducing Head, Face And Brain Injuries By State And Helmet Law, Cody S. Olsen, Andrea M. Thomas, Michael Singleton, Anna M. Gaichas, Tracy J. Smith, Gary A. Smith, Justin Peng, Michael J. Bauer, Ming Qu, Denise Yeager, Timothy Kerns, Cynthia Burch, Lawrence J. Cook
Biostatistics Faculty Publications
Background: Despite evidence that motorcycle helmets reduce morbidity and mortality, helmet laws and rates of helmet use vary by state in the U.S.
Methods: We pooled data from eleven states: five with universal laws requiring all motorcyclists to wear a helmet, and six with partial laws requiring only a subset of motorcyclists to wear a helmet. Data were combined in the Crash Outcome Data Evaluation System's General Use Model and included motorcycle crash records probabilistically linked to emergency department and inpatient discharges for years 2005-2008. Medical outcomes were compared between partial and universal helmet law settings. We estimated adjusted relative …
A Test Of Symmetry Based On The Kernel Kullback-Leibler Information With Application To Base Deficit Data, Hani M. Samawi, Robert L. Vogel
A Test Of Symmetry Based On The Kernel Kullback-Leibler Information With Application To Base Deficit Data, Hani M. Samawi, Robert L. Vogel
Biostatistics Faculty Publications
The assumption of the symmetry of the underlying distribution is important to many statistical inference and modeling procedures. This paper provides a test of symmetry using kernel density estimation and the Kullback-Leibler information. Based on simulation studies, the new test procedure outperforms other tests of symmetry found in the literature, including the Runs Test of Symmetry. We illustrate our new procedure using real data.