Physical Sciences and Mathematics Commons^™

Factors Associated With Loss To Follow-Up Among Hiv-Infected Patients At An Urban, Hospital-Based Outpatient Hiv Clinic, Timothy J. Friel Md, Anthony Nerino, Lynn Nagel, J D'Aversa, Anthony Strobel, Dorothy Faulkner Phd

Department of Medicine

No abstract provided.

Rapid Door To Balloon Time In The Treatment Of Acute St- Elevation Myocardial Infarction Meaningfully Reduces Overall Hospital Stay, Amit N. Nanavati Md, Nainesh Patel Md, Bruce Feldman Do, J Patrick Kleaveland Md, Orlando E. Rivera Rn, David A. Cox Md

Department of Medicine

No abstract provided.

Critical Assessment Of Outcomes In Acute Aortic Dissection (Type A) At A Community Hospital: A 10 Year Review, Timothy S. Misselbeck, James K. Wu Md, Stephen Deturk Ba, Michael F. Szwerc Md, Sanjay M. Mehta Md, Theodore G. Phillips Md, Gary W. Szydlowski Md, Raymond L. Singer Md

Department of Surgery

No abstract provided.

A Quality Improvement Initiative Using A Novel Travel Survey To Define High-Risk International Travel And Promote Patient-Centered Counseling, Craig A. Mackaness Do, Mark Knouse Md, Suzanne J. Templer Do, Deepti Verma Md, Allison Osborne Ba, Michael J. Weiss Mph

Department of Medicine

No abstract provided.

An Evaluation Of Warfarin Use And 30-Day Hemorrhage In Bariatric Surgery, Amanda M. Curry, Richard Boorse Md, Peter J. Bechtel Md, Cathy Fuhrman Rn, Msn, Cathleen Webber Rn, Mshs, Suzanne L. Smith Mba, Rrt, Tas

Department of Surgery

No abstract provided.

Analysis Of Discrete Choice Probit Models With Structured Correlation Matrices, Bhaskara Ravi

Mathematics & Statistics Theses & Dissertations

Discrete choice models are very popular in Economics and the conditional logit model is the most widely used model to analyze consumer choice behavior, which was introduced in a seminal paper by McFadden (1974). This model is based on the assumption that the unobserved factors, which determine the consumer choices, are independent and follow a Gumbel distribution, widely known as the Independence of irrelevant Alternatives (IIA) assumption. Alternate models that relax IIA assumption are the Generalized Extreme Value (GEV) models, which allow dependency between unobserved factors. However, GEV models do not incorporate all dependency patterns, other choice behaviors such as …

An Introduction To Item Response Theory For Health Behavior Researchers, Russell Warne

Russell T Warne

OBJECTIVE:

To introduce item response theory (IRT) to health behavior researchers by contrasting it with classical test theory and providing an example of IRT in health behavior.

METHOD:

Demonstrate IRT by fitting the 2PL model to substance-use survey data from the Adolescent Health Risk Behavior questionnaire (n=1343 adolescents).

RESULTS:

An IRT 2PL model can produce viable substance use scores that differentiate different levels of substance use, resulting in improved precision and specificity at the respondent level.

CONCLUSION:

IRT is a viable option for health researchers who want to produce high-quality scores for unidimensional constructs. The results from our example-although not …

Testing For Regime Swtiching: A Comment, Douglas Steigerwald, Andrew Carter

Douglas G. Steigerwald

An autoregressive model with Markov-regime switching is analyzed that reflects on the properties of the quasi-likelihood ratio test developed by Cho and White (2007). For such a model, we show that consistency of the quasi-maximum likelihood estimator for the population parameter values, on which consistency of the test is based, does not hold. We describe a condition that ensures consistency of the estimator and discuss the consistency of the test in the absence of consistency of the estimator.

A Comparative Analysis Of Decision Trees Vis-À-Vis Other Computational Data Mining Techniques In Automotive Insurance Fraud Detection, Adrian Gepp, Kuldeep Kumar, J Holton Wilson, Sukanto Bhattacharya

Adrian Gepp

No abstract provided.

Incorporating Network Structure In Integrative Analysis Of Cancer Prognosis Data, Shuangge Ma

Shuangge Ma

In high-throughput cancer genomic studies, markers identified from the analysis of single datasets may have unsatisfactory properties because of low sample sizes. Integrative analysis pools and analyzes raw data from multiple studies, and can effectively increase sample size and lead to improved marker identification results. In this study, we consider the integrative analysis of multiple high-throughput cancer prognosis studies. In the existing integrative analysis studies, the interplay among genes, which can be described using the network structure, has not been effectively accounted for. In network analysis, tightly-connected nodes (genes) are more likely to have related biological functions and similar regression …

Risk Factors Of Follicular Lymphoma, Shuangge Ma

Shuangge Ma

No abstract provided.

Health Insurance Coverage And Impact: A Survey In Three Cities In China, Shuangge Ma

Shuangge Ma

No abstract provided.

Integrative Analysis Of Multiple Cancer Genomic Datasets Under The Heterogeneity Model, Shuangge Ma

Shuangge Ma

No abstract provided.

Health Insurance Coverage, Medical Expenditure And Coping Strategy: Evidence From Taiwan, Shuangge Ma

Shuangge Ma

No abstract provided.

Impact Of Illness And Medical Expenditure On Household Consumptions: A Survey In Western China, Shuangge Ma

Shuangge Ma

No abstract provided.

Identification Of Gene-Environment Interactions In Cancer Prognosis Studies Using Penalization, Shuangge Ma

Shuangge Ma

High-throughput cancer studies have been extensively conducted, searching for genetic risk factors independently associated with prognosis beyond clinical and environmental risk factors. Many studies have shown that the gene-environment interactions may have important implications. Some of the existing methods, such as the commonly adopted single-marker analysis, may be limited in that they cannot accommodate the joint effects of a large number of genetic markers or use ineffective marker identification techniques. In this study, we analyze cancer prognosis studies, and adopt the AFT (accelerated failure time) model to describe survival. A weighted least squares approach, which has the lowest computational cost, …

Some Non-Asymptotic Properties Of Parametric Bootstrap P-Values, Chris Lloyd

Chris J. Lloyd

The bootstrap P-value is the exact tail probability of a test statistic, cal-culated assuming the nuisance parameter equals the null maximum likelihood (ML) estimate. For discrete data, bootstrap P-values perform amazingly well even for small samples, even as standard first order methods perform surprisingly poorly. Why is this? Detailed numerical calculations in Lloyd (2012a) strongly suggest that the good performance of bootstrap is not explained by asymptotics. In this paper, I establish several desirable non-asymptotic properties of bootstrap P-values. The most important of these is that bootstrap will correct ‘bad’ ordering of the sample space which leads to a more …

Positive Trait Item Response Models, Joseph F. Lucke

Joseph Lucke

A new item response model is proposed for which the trait is positive. Three such models, the loglogistic, the log-normal, and the Weibull, are presented along with their item information curves. The data of seven addiction items from the DSM-IV from a study on alcohol addiction is analyzed by these three models using Bayesian Markov chain Monte Carlo methods. The item characteristic curves and item information curves are presented for all three models. The person scores for four item response patterns are presented for the log-logistic model.

Excel Calculator For Assignment/Article "Compound Interest And The Power Of Saving", Richard H. Serlin

Richard H. Serlin

No abstract provided.

Assessing Content Validity Through Correlation And Relevance Tools A Bayesian Randomized Equivalence Experiment, Byron J. Gajewski, Diane K. Boyle, Marjorie Bott, Larry R. Price, Jamie Leopold, Nancy Dunton

Byron J Gajewski

Content validity elicits expert opinion regarding items of a psychometric instrument. Expert opinion can be elicited in many forms: for example, how essential an item is or its relevancy to a domain. This study developed an alternative tool that elicits expert opinion regarding correlations between each item and its respective domain. With 109 Registered Nurse (RN) site coordinators from National Database of Nursing Quality Indicators, we implemented a randomized Bayesian equivalence trial with coordinators completing ‘‘relevance’’ or ‘‘correlation’’ content tools regarding the RN Job Enjoyment Scale. We confirmed our hypothesis that the two tools would result in equivalent content information. …

Syllabus Of Intermediate Macroeconomics (Master's Course), Reza Moosavi Mohseni Dr.

Reza Moosavi Mohseni

No abstract provided.

Modeling Dependence Using Skew T Copulas: Bayesian Inference And Applications, Michael S. Smith, Quan Gan, Robert Kohn

Michael Stanley Smith

[THIS IS AN AUGUST 2010 REVISION THAT REPLACES ALL PREVIOUS VERSIONS.]

We construct a copula from the skew t distribution of Sahu, Dey & Branco (2003). This copula can capture asymmetric and extreme dependence between variables, and is one of the few copulas that can do so and still be used in high dimensions effectively. However, it is difficult to estimate the copula model by maximum likelihood when the multivariate dimension is high, or when some or all of the marginal distributions are discrete-valued, or when the parameters in the marginal distributions and copula are estimated jointly. We therefore propose …

Adaptive Matching In Randomized Trials And Observational Studies, M. Van Der Laan, Laura Balzer, M. Petersen

Laura B. Balzer

Resampling-Based Information Criteria For Best-Subset Regression, Philip T. Reiss, Lei Huang, Joseph E. Cavanaugh, Amy Krain Roy

Philip T. Reiss

When a linear model is chosen by searching for the best subset among a set of candidate predictors, a fixed penalty such as that imposed by the Akaike information criterion may penalize model complexity inadequately, leading to biased model selection. We study resampling-based information criteria that aim to overcome this problem through improved estimation of the effective model dimension. The first proposed approach builds upon previous work on bootstrap-based model selection. We then propose a more novel approach based on cross-validation. Simulations and analyses of a functional neuroimaging data set illustrate the strong performance of our resampling-based methods, which are …

Estimation Of Copula Models With Discrete Margins Via Bayesian Data Augmentation, Michael S. Smith, Mohamad A. Khaled

Michael Stanley Smith

Estimation of copula models with discrete margins is known to be difficult beyond the bivariate case. We show how this can be achieved by augmenting the likelihood with latent variables, and computing inference using the resulting augmented posterior. To evaluate this we propose two efficient Markov chain Monte Carlo sampling schemes. One generates the latent variables as a block using a Metropolis-Hasting step with a proposal that is close to its target distribution, the other generates them one at a time. Our method applies to all parametric copulas where the conditional copula functions can be evaluated, not just elliptical copulas …