BIOS 8130 – Advanced Topics in Biostatistics

This course provides an overview of advanced biostatistical descriptive and inferential methods including multiple regression, logistic regression, longitudinal data, survival analysis, and repeated measures with applications to public health and biomedical studies. Emphasis will be placed on developing statistical reasoning and critical thinking skills in addition to programming skills using statistical software (SAS) to analyze public health and biomedical data

PUBH 9130 – Professional Seminar in Biostatistics

This course focuses on study design and sampling methods as well as data analysis of small and large, national and local health surveys and vital statistics in order to gain experience describing data using effective graphical and numerical methods. Students will use statistical software (SAS) to analyze data originating from various survey designs, including data from experimental designs such as parallel, longitudinal studies that involve several treatment or intervention groups. Students will work in groups on data analysis projects and case studies in order to be exposed to others\u27 expertise in different areas of public health and to learn effective collaboration. Readings from the literature in public health and biomedical studies will be analyzed and critiqued so that students will gain experience in distinguishing effective data analysis techniques. Emphasis will be placed on the development of critical thinking skills, statistical reasoning, and collaboration. Prerequisite: A minimum grade of C in PUBH 654

Using the ROC Curve to Measure Association and Evaluate Prediction Accuracy for a Binary Outcome

This review article addresses the ROC curve and its advantage over the odds ratio to measure the association between a continuous variable and a binary outcome. A simple parametric model under the normality assumption and the method of Box-Cox transformation for non-normal data are discussed. Applications of the binormal model and the Box-Cox transformation under both univariate and multivariate inference are illustrated by a comprehensive data analysis tutorial. Finally, a summary and recommendations are given as to the usage of the binormal ROC curve

A More Efficient Nonparametric Test of Symmetry Based on Overlapping Coefficient

In this paper we provide a more efficient nonparametric test of symmetry based on the empirical overlap coefficient using kernel density estimation applied to an extreme order statistics, namely extreme ranked set sampling. Our simulation investigation reveals that our proposed test of symmetry is at least as powerful as currently available tests of symmetry. Intensive simulation is conducted to examine the power of the proposed test. An illustration is provided using cardiac output and body weight of neonates in a neonatal intensive care unit

A Test of Symmetry Based on the Kernel Kullback-Leibler Information with Application to Base Deficit Data

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

Observations of Chemically Enriched QSO Absorbers near z ~ 2.3 Galaxies: Galaxy-Formation Feedback Signatures in the IGM

We present a study of galaxies and intergalactic gas toward the z=2.73 quasar HS1700+6416, to explore the effects of galaxy formation feedback on the IGM. Our observations and ionization simulations indicate that the volume within 100-200 h_71^{-1} physical kpc of high-redshift galaxies contains very small, dense, and metal-rich absorption-line regions. These systems often contain shock-heated gas seen in OVI, and may exhibit [Si/C] abundance enhancements suggestive of Type II supernova enrichment. We argue that the absorbers resemble thin sheets or bubbles, whose physical properties can be explained with a simple model of radiatively efficient shocks propegating through the IGM. Their high metallicities suggest that these shocks are being expelled from--rather than falling into--star forming galaxies. There is a dropoff in the IGM gas density at galaxy impact parameters beyond ~300 physical kpc that may trace boundaries of gas structures where the galaxies reside. The local heavy-element enhancement covers 100-200 kpc; beyond this the observed abundances blend into the general IGM. Supernova-driven winds or dynamical stripping of interstellar gas appears to affect the IGM near massive galaxies, even at R>~100 kpc. However, these feedback systems represent only a few percent of the Lya forest mass at z~2.5. Their mass could be larger if the more numerous metal-poor CIV systems at >~200 kpc are tepid remnants of very powerful winds. Based on present observations it is not clear that this scenario is to be favored over one involving pre-enrichment by smaller galaxies at z>~6.Comment: Accepted for publication in the Astrophysical Journal. 26 pages emulateapj, incl. 5 pages tables, 15 figure

Ventilation Transport Trade Study for Future Space Suit Life Support Systems

A new and advanced portable life support system (PLSS) for space suit surface exploration will require a durable, compact, and energy efficient system to transport the ventilation stream through the space suit. Current space suits used by NASA circulate the ventilation stream via a ball-bearing supported centrifugal fan. As NASA enters the design phase for the next generation PLSS, it is necessary to evaluate available technologies to determine what improvements can be made in mass, volume, power, and reliability for a ventilation transport system. Several air movement devices already designed for commercial, military, and space applications are optimized in these areas and could be adapted for EVA use. This paper summarizes the efforts to identify and compare the latest fan and bearing technologies to determine candidates for the next generation PLSS

Understanding Forced Sex During Adolescence: An Exploratory Study of Risk and Protective Factors

The overall purpose of this study was to explore predictors of forced sex among a sample of middle school students. Youth Risk Behavior Surveys were distributed to middle school youth in southeast Florida. Data were analyzed using descriptive statistics, Chi-Square Automatic Interaction Detector (CHAID), and logistic regression. In the final CHAID model, the segment most at risk was comprised of youth who had been harassed for being gay, lesbian, or bisexual and youth who had experienced dating violence. Past exposure with violence yielded the highest association with forced sex. Moreover, having multiple sexual partners, use of prescription drugs, and experiencing harassment for being gay, lesbian, or bisexual are predictors of forced sex. This study has implications for school-based prevention of forced sex through the identification of risk and protective factors that can be targeted with evidence-based interventions

Correction of Verication Bias using Log-Linear Models for a Single Binaryscale Diagnostic Tests

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 due to the issues of costeffectiveness and invasive nature of the procedures. In practice some of the patients with test results are not selected for verification of the disease status which results in verification bias for diagnostic tests. The ability of the diagnostic test to correctly identify the patients with and without the disease can be evaluated by measures such as sensitivity, specificity and predictive values. However, these measures can give biased estimates if we only consider the patients with test results who also underwent the gold standard procedure. The emphasis of this paper is to apply the log-linear model approach to compute the maximum likelihood estimates for sensitivity, specificity and predictive values. We also compare the estimates with Zhou’s results and apply this approach to analyze Hepatic Scintigraph data under the assumption of ignorable as well as non-ignorable missing data mechanisms. We demonstrated the efficiency of the estimators by using simulation studies