Statistics and Probability Commons^™

Jmasm45: A Computer Program For Bayesian D-Optimal Binary Repeated Measurements Designs (Matlab), Haftom Temesgen Abebe, Frans E. S. Tan, Gerard J. P. Van Breukelen, Martijn P. F. Berger

Journal of Modern Applied Statistical Methods

Planners of longitudinal studies of binary responses in applied sciences have not yet benefitted from optimal designs, which have been shown to improve precision of model parameter estimates, due to absence of a computer program. An interactive computer program for Bayesian optimal binary repeated measurements designs is presented for this purpose.

Weighted Distributions: A Brief Review, Perspective And Characterizations, Aamir Saghir, Gholamhossein G. Hamedani, Sadaf Tazeem, Aneeqa Khadim

Mathematics, Statistics and Computer Science Faculty Research and Publications

The weighted distributions are widely used in many fields such as medicine, ecology and reliability, to name a few, for the development of proper statistical models. Weighted distributions are milestone for efficient modeling of statistical data and prediction when the standard distributions are not appropriate. A good deal of studies related to the weight distributions have been published in the literature. In this article, a brief review of these distributions is carried out. Implications of the differing weight models for future research as well as some possible strategies are discussed. Finally, characterizations of these distributions based on a simple relationship …

Joint Modelling Of Longitudinal Measurements And Time-To-Event Data : Application To Hiv Study, Mirna Walid Halawani

Theses, Dissertations and Culminating Projects

Longitudinal and survival data are frequently collected in biomedical studies. The research questions of interest in these studies often require separate analysis of the outcomes. But in many occasions interest also lies in studying their association structures, such as in biomarker research, where the clinical studies are designed to identify biomarkers with strong prognostic capabilities for event time outcomes. In the separate analyses, a linear mixed-effects model is used for modeling the longitudinal data to study the changing trend of the response overtime when controlling some covariates and a survival model is used to model the time-to-event data. A common …

Topics In Group Testing With Multiple Infections, Peijie Hou

Theses and Dissertations

Group testing, dating back to the early 1940s, was first proposed to screen for syphilis among US inductees during World War II (Dorfman, 1943). Since then, the benefits of reducing testing costs by employing group testing have been demonstrated in many areas, such as drug discovery, genetics, and infectious disease testing. Traditionally, statistical research in group testing has largely been motivated by applications involving a single infection. With the recent development of multiplex assays that can diagnose multiple infections simultaneously, generalizing the existing group testing literature to incorporate multiple infections is a natural and necessary next step. This dissertation consists …

Bayesian Flexible Modeling Of Interval-Censored Failure Time Data, Sheng-Yang Wang

Theses and Dissertations

Interval-censored data are a special type of survival data, in which the survival time is not accurately observed but known to fall within a specific time interval. Interval censored data commonly arise in real-life epidemiological and medical studies that involve periodic examinations. In this dissertation, several semi-parametric regression models are investigated to provide flexible modeling and robust inference for interval censored data from Bayesian perspectives.

Chapter 1 provides a detailed description about interval-censored data and gives several examples. Existing models and methods for analyzing such interval-censored data are reviewed as well. Chapter 2 develops a unified Bayesian estimation approach under …

Statistical Learning Methods For Facial Recognition, Mengyi Jia

Arts & Sciences Graduate Student Theses and Dissertations

Facial recognition techniques have become increasingly popular in recent decades. This thesis investigates the performance of several methods applied to two different face databases, under a variety of poses and illumination settings. PCA, LDA and KNN are compared and contrasted in terms of their accuracy and processing time.

An Extended Weighted Exponential Distribution, Abbas Mahdavi, Leila Jabari

Journal of Modern Applied Statistical Methods

A new class of weighted distributions is proposed by incorporating an extended exponential distribution in Azzalini’s (1985) method. Several statistics and reliability properties of this new class of distribution are obtained. Maximum likelihood estimators of the unknown parameters cannot be obtained in explicit forms; they have to be obtained by solving some numerical methods. Two data sets are analyzed for illustrative purposes, and show that the proposed model can be used effectively in analyzing real data.

A Comparison Of Depth Functions In Maximal Depth Classification Rules, Olusola Samuel Makinde, Adeyinka Damilare Adewumi

Journal of Modern Applied Statistical Methods

Data depth has been described as alternative to some parametric approaches in analyzing many multivariate data. Many depth functions have emerged over two decades and studied in literature. In this study, a nonparametric approach to classification based on notions of different data depth functions is considered and some properties of these methods are studied. The performance of different depth functions in maximal depth classifiers is investigated using simulation and real data with application to agricultural industry.

The Double Prior Selection For The Parameter Of Exponential Life Time Model Under Type Ii Censoring, Ronak M. Patel, Achyut C. Patel

Journal of Modern Applied Statistical Methods

A comparison of double informative priors assumed for the parameter of exponential life time model is considered. Three different sets of double priors are included, and the results are compared with a forth single prior. The data is Type II censored and Bayes estimators for the parameter and reliability are carried out under a squared error loss function in the cases of the four different sets of prior distributions. The predictive distribution was derived for future failure time and also for the remaining ordered failure times after the first r failure times have been observed. Corresponding Bayes credible equal tail …

Jmasm43: Teereg: Trimmed Elemental Estimation (R), Wei Jiang, Matthew S. Mayo

Journal of Modern Applied Statistical Methods

Trimmed elemental regression is robust to outliers and violations of model assumptions. Its properties and statistical inference were evaluated using bias-corrected and accelerated bootstrap confidence intervals. An R package named TEEReg is developed to compute the trimmed elemental estimates and the corresponding bootstrap confidence intervals. Two examples are provided to demonstrate its usage.

Outlier Impact And Accommodation On Power, Hongjing Liao, Yanju Li, Gordon P. Brooks

Journal of Modern Applied Statistical Methods

The outliers’ influence on power rates in ANOVA and Welch tests at various conditions was examined and compared with the effectiveness of nonparametric methods and Winsorizing in minimizing the impact of outliers. Results showed that, considering both power and Type I error, a nonparametric test is the safest choice to control the inflation of Type I error with a decent sample size and yield relatively high power.

Book Review: Multivariate Statistical Methods, A Primer, C. R. Rao

Journal of Modern Applied Statistical Methods

Multivariate Statistical Methods, A Primer, 4th Ed. Bryan F. J. Manly and Jorge A. Navarro Alberto. NY: Chapman & Hall / CRC Press. 2016. 264 p. ISBN 10: 1498728960 / ISBN 13: 978-1498728966

Jmasm44: Implementing Multiple Ratio Imputation By The Emb Algorithm (R), Masayoshi Takahashi

Journal of Modern Applied Statistical Methods

Although single ratio imputation is often used to deal with missing values in practice, there is a paucity of discussion regarding multiple ratio imputation. Code in the R statistical environment is presented to execute multiple ratio imputation by the Expectation-Maximization with Bootstrapping (EMB) algorithm.

Tuberculosis And Risk Of Acute Myocardial Infarction: A Propensity Score-Matched Analysis, Moises A. Huaman, Richard J. Kryscio, Carl J. Fichtenbaum, David Henson, Elizabeth G. Salt, Timothy R. Sterling, Beth A. Garvy

Biostatistics Faculty Publications

Several pathogens have been associated with increased cardiovascular disease (CVD) risk. Whether this occurs with Mycobacterium tuberculosis infection is unclear. We assessed if tuberculosis disease increased the risk of acute myocardial infarction (AMI). We identified patients with tuberculosis index claims from a large de-identified database of ~15 million adults enrolled in a U.S. commercial insurance policy between 2008 and 2010. Tuberculosis patients were 1:1 matched to patients without tuberculosis claims using propensity scores. We compared the occurrence of index AMI claims between the tuberculosis and non-tuberculosis cohorts using Kaplan–Meier curves and Cox Proportional Hazard models. Data on 2026 patients with …

Novel Statistical Approaches For Missing Values In Truncated High-Dimensional Metabolomics Data With A Detection Threshold., Jasmit Sureshkumar Shah

Electronic Theses and Dissertations

Despite considerable advances in high throughput technology over the last decade, new challenges have emerged related to the analysis, interpretation, and integration of high-dimensional data. The arrival of omics datasets has contributed to the rapid improvement of systems biology, which seeks the understanding of complex biological systems. Metabolomics is an emerging omics field, where mass spectrometry technologies generate high dimensional datasets. As advances in this area are progressing, the need for better analysis methods to provide correct and adequate results are required. While in other omics sectors such as genomics or proteomics there has and continues to be critical understanding …

Trend And Return Level Of Extreme Snow Events In New York City, Mintaek Lee

Boise State University Theses and Dissertations

A major winter storm brought up to 42 inches of snow in parts of the Mid-Atlantic and Northeast United States for January 22-24, 2016. The blizzard of January 2016 impacted about 102.8 million people, where at least 55 people died due to the snowstorm and it caused economic losses in a range of $500 million to $3 billion. This thesis studies two important aspects of extreme snow events: maximum snowfall and maximum snow depth. We apply extreme value methods to extreme snowfall and snow depth data from the New York City area to examine if there are any significant linear …

Price Prediction: Determining Changes In Stock Pricing Through Sentiment Analysis Of Online Consumer Reviews, Daryl F. Boykin

UNLV Theses, Dissertations, Professional Papers, and Capstones

The rapid growth of technology has changed the dynamics in which consumers socialize and make their purchasing decisions. The volume of online reviews has grown rapidly over the past decade, leading the peer groups of consumer to carry a disproportionate weight in the purchasing decision process. The sheer volume of reviews can be a daunting task for an operator to attempt to incorporate the reviews in their analysis. Sentiment analysis allows for large volumes of consumer reviews to be processed in a relatively easy, and time sensitive manner. The information contained in these reviews, the sentiment score, is the same …

Generalized Clusterwise Regression For Simultaneous Estimation Of Optimal Pavement Clusters And Performance Models, Mukesh Khadka

UNLV Theses, Dissertations, Professional Papers, and Capstones

The existing state-of-the-art approach of Clusterwise Regression (CR) to estimate pavement performance models (PPMs) pre-specifies explanatory variables without testing their significance; as an input, this approach requires the number of clusters for a given data set. Time-consuming ‘trial and error’ methods are required to determine the optimal number of clusters. A common objective function is the minimization of the total sum of squared errors (SSE). Given that SSE decreases monotonically as a function of the number of clusters, the optimal number of clusters with minimum SSE always is the total number of data points. Hence, the minimization of SSE is …

Demographics, Patterns Of Care, And Survival In Pediatric Medulloblastoma, Emily V. Dressler, Therese A. Dolecek, Meng Liu, John L. Villano

Internal Medicine Faculty Publications

We evaluated the American College of Surgeon’s National Cancer Data Base (NCDB) to describe current hospital-based epidemiologic frequency, survival, and patterns of care of pediatric medulloblastoma. We analyzed NCDB 1998–2011 data on medulloblastoma for children ages 0–19 years using logistic and poisson regression, Kaplan–Meier survival estimates, and Cox proportional hazards models. 3647 cases of medulloblastoma in those aged 0–19 years were identified. Chemotherapy was received by 79 and 74% received radiation, with 65% receiving both therapies. Those who received radiation were more likely to be older than four, while those who received chemotherapy were more likely to be age four …

A Bayesian Variable Selection Method With Applications To Spatial Data, Xiahan Tang

Graduate Theses and Dissertations

This thesis first describes the general idea behind Bayes Inference, various sampling methods based on Bayes theorem and many examples. Then a Bayes approach to model selection, called Stochastic Search Variable Selection (SSVS) is discussed. It was originally proposed by George and McCulloch (1993). In a normal regression model where the number of covariates is large, only a small subset tend to be significant most of the times. This Bayes procedure specifies a mixture prior for each of the unknown regression coefficient, the mixture prior was originally proposed by Geweke (1996). This mixture prior will be updated as data becomes …