|August 2010 ‐ May 2014||Ph.D. in Public Health, Georgia Southern University|
|January 2008 ‐ May 2010||M.S. in Public Health, Georgia Southern University|
|September 2002 ‐ March 2007||B.S. in Medicine and Surgery, Maharaja Sayajirao University of Baroda|
P.O. Box 8015
Statesboro, GA 30460
Phone: (912) 478-1011
Office: Hendricks Hall
Peer Reviewed Articles (18)
Using Ranked Auxiliary Covariate as a More Efficient Sampling Design for ANCOVA Model: Analysis of a Psychological Intervention to Buttress Resilience Communications for Statistical Applications and Methods (2017)
Drawing a sample can be costly or time consuming in some studies. However, it may be possible to rank the sampling units according to some baseline auxiliary covariates, which are easily obtainable, and/or cost efficient. ...
Estimates for Cell Counts and Common Odds Ratio in Three-way Contingency Tables by Homogeneous Log-linear Models With Missing Data AStA Advances in Statistical Analysis (2017)
Missing observations often occur in cross-classified data collected during observational, clinical, and public health studies. Inappropriate treatment of missing data can reduce statistical power and give biased results. This work extends the Baker, Rosenberger and ...
On Kernel Density Estimation Based on Different Stratified Sampling With Optimal Allocation Communications in Statistics - Theory and Methods (2016)
Kernel density estimation is probably the most widely used non parametric statistical method for estimating probability densities. In this paper, we investigate the performance of kernel density estimator based on stratified simple and ranked set ...
Estimation of P(X > Y) When X and Y Are Dependent Random Variables Using Different Bivariate Sampling Schemes Communications for Statistical Applications and Methods (2016)
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 ...
Rank-Based Kernel Estimation of the Area Under the ROC Curve Statistical Methodology (2016)
In medical diagnostics, the ROC curve is the graph of sensitivity against 1-specificity as the diagnostic threshold runs through all possible values. The ROC curve and its associated summary indices are very useful for the ...
More Efficient Logistic Analysis Using Moving Extreme Ranked Set Sampling Journal of Applied Statistics (2016)
Logistic regression is the most popular technique available for modeling dichotomous-dependent variables. It has intensive application in the field of social, medical, behavioral and public health sciences. In this paper we propose a more efficient ...
Correction of Verication Bias using Log-linear Models for a Single Binaryscale Diagnostic Tests Journal of Biometrics & Biostatistics (2015)
In diagnostic medicine, the test that determines the true disease status without an error is referred to as the gold standard. Even when a gold standard exists, it is extremely difficult to verify each patient ...
How Long does that 10-Year Smoke Alarm Really Last? A Survival Analysis of Smoke Alarms Installed through the SAIFE Program in Rural Georgia Public Health Research (2015)
Background: When functioning properly, a smoke alarm alerts individuals in the residence that smoke is near the alarm. Smoke alarms serve as a primary prevention mechanism to abate morbidity and mortality related to residential fires. ...
Book Chapters (1)
Markov Chain Monte-Carlo Methods for Missing Data Under Ignorability Assumptions Monte-Carlo Simulation-Based Statistical Modeling (2017)
Missing observations are a common occurrence in public health, clinical studies and social science research. Consequences of discarding missing observa-tions, sometimes called complete case analysis, are low statistical power and poten-tially biased estimates. Fully Bayesian ...
Letters to the editor (2)
Proper Awareness, but Wrong Action. What Is Missing? Pediatrics (2016)
The study by Robinson and Sutin suggests that “Contrary to popular belief, parental identification of child overweight is not protective against further weight gain”(1) We were approached by the press to address the potential contradictions ...