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Georgia Southern Investigates Kernel Density Based Mode Estimation

The mode is a measure of the central tendency as well as the most probable value. Additionally, the mode is not influenced by the tail of the distribution. In the literature the properties and the application of mode estimation is only considered under simple random sampling (SRS). However, ranked set sampling (RSS) is a structural sampling method which improves the efficiency of parameter estimation in many circumstances and typically leads to a reduction in sample size. In this paper we investigate some of the asymptotic properties of kernel density based mode estimation using RSS. We demonstrate that kernel density based mode estimation using RSS is consistent and asymptotically normal with smaller variance than that under SRS. Improved performance of the mode estimation using RSS compared to SRS is supported through a simulation study. An illustration of the computational aspect using a Duchenne muscular dystrophy data set is provided.

Notes on kernel density based mode estimation using more efficient sampling designs,” was recently published in Computational Statistics.

Drs. Hani Samawi was the lead author and Haresh Rochani, JingJing Yin, and Robert Vogel, Department of Biostatistics Jiann-Ping Hsu College of Public Health Georgia Southern University were co-authors.


Georgia Southern Examines Operational and Financial Performance of Georgia’s Critical Access Hospitals

Georgia’s Critical Access Hospitals (CAHs) face increasingly complex threats to financial sustainability, as demonstrated by the disproportionally high number of closures in comparison to other states in the nation.

Financial performance measures (including profitability, revenue, liquidity, debt, utilization, and productivity), site visits, key personnel interviews, and a revenue cycle management assessment were used to assess the strategic landscape of CAHs in Georgia, analyze financial and operational performance, and provide recommendations.

For CAHs in Georgia, financial and operating performance indicators, interviews, and assessments depict a challenging operating environment, but opportunities for improvement exist through implementation of a Lean Six Sigma program and improved benchmarking processes.

Georgia’s CAHs operate in a challenging environment, but operational improvement strategies (such as a Lean Six Sigma program) and benchmarking directed towards business processes, including revenue cycle management, provide opportunities for sustainability in the future.

Operational and financial performance of Georgia’s Critical Access Hospitals,” was recently published in the Journal of the Georgia Public Health Association with Dr. Linda Kimsey, assistant professor of Health Policy and Management at the Jiann-Ping Hsu College of Public Health Georgia Southern University as the lead author. Drs. Bettye Apenteng, William A. Mase, Samuel Opoku, Charles Owens, and Stuart Tedders, and Ms. Angela Peden from the Jiann-Ping Hsu College of Public Health were co-authors.


Georgia Southern Examines Regression Estimators for Different Stratified Sampling Schemes

Two types of stratified regression estimators for the population mean, the separate and the combined estimators, are investigated using stratified random sampling scheme (SSRS) and stratified ranked set sampling (SRSS). We derived mean and variance of the proposed estimators. In addition, we compared the performance of the regression estimators using SRSS with respect to SSRS by simulation. Our derivations and simulations revealed that our proposed estimators are unbiased and using SRSS is more efficient than using SSRS. The procedure are illustrated by using the bilirubin levels in babies in a neonatal intensive care unit data.

On Regression Estimators for Different Stratified Sampling Schemes,” was recently published in the Journal of Statistics and Management Systems.

Dr. Arpita Chatterjee, Department of Mathematics at Georgia Southern University was the lead author and biostatistics faculty from the Jiann-Ping Hsu College of Public Health Georgia Southern University Drs. Hani Samawi, Lili Yu, Daniel Linder (former), Jingxian Cai, and Robert Vogel were co-authors.


JPHCOPH Examines Test Strategies of Treatment Efficacy in Noninferiority Clinical Trials

Dr. Mohammad Huque, Adjunct Professor of Biostatistics in the Jiann-Ping Hsu College of Public Health Georgia Southern University is the lead author of “Consistency Ensured Test Strategies for Supportive Evidence of Treatment Efficacy in Noninferiority Clinical Trials,” recently published in The Journal of Biopharmaceutical Statistics. Noninferiority (NI) clinical trials are designed to demonstrate that a new treatment is not unacceptably worse than an active control on a clinically meaningful endpoint. While such an endpoint can be of any type, the focus of this manuscript is on the binary-type endpoint. Examples of this endpoint can be clinical cure endpoint for patients with bacterial diseases or based on a pre-specified virological threshold for viral diseases. However, in addition to assessing such a binary endpoint for the NI comparison, the trial may also evaluate a second clinically relevant endpoint for providing additional support to the evidence of the designated primary endpoint. Specifically, if the trial is successful in demonstrating statistical significance on the first endpoint, then observing at least a positive trend in efficacy on the second endpoint may provide additional supportive evidence of efficacy. The second endpoint can be a time-to-event type endpoint, such as time-to-symptom resolution (TSR) or time to all-cause mortality for infectious disease trials, time-to-wound closure for wound healing trials, or other endpoints. We propose two consistency ensured test strategies for the two hypotheses of a trial, one associated with the binary endpoint and the other with the second endpoint, both with the objective of drawing inference regarding the efficacy of the new treatment based on findings from testing the two hypotheses. A key feature of these test strategies is that basically it does not require multiplicity adjustment of the significance levels. We conclude with general discussion of the testing methods and possible applications to unmet medical need trials.

Dr. Huque is a Fellow of the American Statistical Association and recently retired after a long career as an applied statistician in the Center for Drug Evaluation and Research at the Food and Drug Association. The Journal of Biopharmaceutical Statistics was founded in 1991 by Dr. Karl E. Peace, who was its Editor-in-Chief for the first 10 years of its existence.


JPHCOPH Examines Consistency-ensured Parametric Tests for Critical Events of Composite Endpoints

Dr. Mohammad Huque, Adjunct Professor of Biostatistics in the Jiann-Ping Hsu College of Public Health at Georgia Southern University is the lead author of “Consistency-ensured Parametric Tests for Critical Events of Composite Endpoints,” recently published in The Journal of Biopharmaceutical Statistics. Composite endpoints (CEs) are commonly used in clinical trials when clinically important events are rare or when the disease is multifaceted. However, components of a CE often differ markedly in their clinical importance. The overall treatment effect on the composite can be driven by less-important, yet more frequently occurring, components, with no effects on some clinically important components. These situations create difficulties in interpreting the results of the CE. The literature has proposed several approaches for handling these conditions, for example, by setting requirements on the results of the clinically important components. However, for a rare event, it can be difficult to draw an appropriate conclusion about its contribution to the overall result of the composite. Here, we propose combining clinically important components to jointly increase their power and to require that their findings meet a prespecified level of evidence, called the consistency criterion. With the increase in power, the study can then be designed with the objectives of establishing efficacy for the composite and/or for the subset of clinically critical components. In this regard, we introduce multiple testing strategies, which account for the consistency requirement and for the correlation between these two endpoints. We illustrate the methodology using the PROactive trial.

Dr. Huque is a Fellow of the American Statistical Association and recently retired after a long career as an applied statistician in the Center for Drug Evaluation and Research at the Food and Drug Association. The Journal of Biopharmaceutical Statistics was founded in 1991 by Dr. Karl E. Peace, who was its Editor-in-Chief for the first 10 years of its existence.