Statistics and Probability Commons^™

Diagnostics For Choosing Between Stratified Logrank And Stratified Wilcoxon, Jhoanne Marsh C. Gatpatan

Dissertations

Martinez and Naranjo (2010) proposed a pretest for choosing between Logrank or Wilcoxon test in a two - sample case. However, in the presence of covariates, comparing two populations without adjusting for covariates would yield misleading results. In this study, we propose several pretests that will help the analyst decide to use stratified Logrank or stratified Wilcoxon tests in comparing two survival curves after covariates have been taken into account. Power performance of each adaptive test was done through simulations under PH and non-PH cases.

Spatial Analysis Of Time Between Two Consecutive Dental And Two Consecutive Well-Child Visits For Foster Care Youth, Chenyang Shi

Dissertations

Foster care youth is a medically vulnerable population. Poor dental health and irregular well-child visits may cause serious health-related issues, such as mental disorder, nutrition imbalance, tooth damage, etc. Michigan requires all youth in foster care to receive annual dental and well-child visits. Usually, the study of foster care well-child and dental visits include two parts: time between two consecutive visits (gap time) and number of visits. For this study, a longitudinal-spatial model that has the flexibility to analyze the well-child/dental gap times and number of visits was developed. The longitudinal data (2009-2012) on Michigan foster care youth from 10 …

Development Of Traditional And Rank-Based Algorithms For Linear Models With Autoregressive Errors And Multivariate Logistic Regression With Spatial Random Effects, Shaofeng Zhang

Dissertations

Linear models are the most commonly used statistical methods in many disciplines. One of the model assumptions is that the error terms (residuals) are independent and identically distributed. This assumption is often violated and autoregressive error terms are often encountered by researchers. The most popular technique to deal with linear models with autoregressive errors is perhaps the autoregressive integrated moving average (ARIMA). Another common approach is generalized least squares, such as Cochrane-Orcutt estimation and Prais-Winsten estimation. However, these usually have poor behaviors when fitting small samples. To address this problem, a double bootstrap method was proposed by McKnight et al. …

The Technological Revolution And Data Science, Leslie Walcott

Honors Theses

What was once only depicted in science fiction is now a reality: computers are taking jobs from humans. As technology improves, automation is transforming the workplace. They say a “fourth industrial revolution” is inevitable within the next ten years. In the industrial revolution, the jobs lost were unskilled laborers, such as coal miners, textiles manufacturers, or cotton workers. There was no argument for whether or not a machine could do the jobs more efficiently--it was fact. The term technological unemployment means the loss of jobs caused by technological change. The headline, “Factory workers replaced by automation,” is not particularly startling …

Subgroup Analysis And Growth Curve Models For Longitudinal Data, Nichole Andrews

Dissertations

In clinical trials and biomedical studies, treatments are compared to determine which one is effective against illness. Growth curve analysis can be beneficial in longitudinal biomedical studies, as we can evaluate the treatment effect on the response over time. The generalized growth curve model using polynomial regression is proposed for longitudinal data. An optimal degree for the polynomial is obtained using the BIQIF, an adaptation of the Bayesian information criterion. Quadratic inference functions are used to estimate the parameters of the model, which takes into account the fact that repeated measurements from the same subject are more likely to be …

Benefit Of Ultrasound Curriculum Development For Family Medicine Residents, Nithin Natwa, Uzair Munshey, Duncan Vos, Robert Baker

Research Day

Introduction/Purpose: Musculoskeletal problems comprise some of the most common reasons for ambulatory care encounters in the United States, accounting for 8.3% of the 1.2 billion visits per year according to the CDC. Musculoskeletal Ultrasound use has become more common in primary care for diagnosis and therapeutics. In Family Medicine Residency (FMR) Programs there is a deficiency of a structured, competency-based musculoskeletal ultrasound (MSK US) training despite its growing popularity. Currently, there is no formalized requirement for Ultrasound education as in other residency programs in spite of its benefit. Methods: We received a positive response on our needs analysis survey for …

Delivery Of Health Education In Adolescents With Behavioral Health Challenges, Ashley Akkal, Ransome Eke Md, Phd, Sulin Wu, Amy Rechenberg, Michael Madrid, Jose Lopez-Vera, Duncan Vos

Research Day

BACKGROUND Adolescents with behavioral health issues tend to have inadequate access to health education, and are thus less aware of the importance of personal and dental hygiene, exercise, and healthy diet and lifestyle habits. Due to this disparity, this population has been known to harbor a higher prevalence of STI’s, drug and alcohol abuse, physical altercations, juvenile detention, and suicide attempts. PURPOSE The overall objective of this study was to examine the effect of integrating a health science curriculum in this population. METHODS Participants aged 5-17 years old were recruited and assigned to either control or science groups by Family …

Determining Best Practices Of Peer Mediation Methods In Kalamazoo Public Schools, Melanie Bourgeau, Dagan Hammar, Neil Hughes, Sarah Kemp, Sydney Spitler, Cathy L. Kothari Phd

Research Day

Determining Best Practices of Peer Mediation methods in Kalamazoo Public Schools Melanie Bourgeau, Dagan Hammar, Neil Hughes, Sarah Kemp, Sydney Spitler, Catherine Kothari BACKGROUND Peer mediation is a method of conflict resolution in which a conflict between two people or groups is guided by a fellow student in order to reach an agreement. Peer mediation has been shown to be an effective tool in helping students resolve conflict and how to respond to future conflicts. This has led to a reduction in school violence and suspensions in schools that have adopted this method. Several methods have been employed in the …

Some Nonparametric Ordered Restricted Inference Problems In The Context Of A Statistical Education Study, Bradford M. Dykes

Dissertations

Over the past 10 years, the Department of Statistics at Western Michigan University has developed a question generating system that can be used for creating multiple forms of exams, quizzes and homework for online and face-to-face use. This system can also be used to provide students with a form of instantaneous feedback. With the goal of analyzing how different levels of feedback in an online learning environment impacts students' performance on assignments, this study presents data collected on two semesters of students enrolled in three different meeting types (strictly online, typical face-to-face, and honors face-to-face) of an introductory Statistics course. …

Statistical Methodology For Data With Multiple Limits Of Detection, Robert M. Flikkema

Dissertations

Limitations of instruments used to collect continuous data sometimes lead to obtaining observations lower than a limit of detection. These observations are known as nondetects. They could be zeroes, or positive numbers, but they are too small to be recorded by a measuring device. Nondetects frequently occur in environmental data. Trace amounts of chemicals can exist in soil or groundwater and are undetectable by a machine reading. These observations pose a problem to researchers since the true values are unknown.

Simulations in the literature have led to inconsistent conclusions regarding what estimation technique to use with nondetect data when estimating …

Does Research On Evaluation Matter? Findings From A Survey Of American Evaluation Association Members And Prominent Evaluation Theorists And Scholars, Satoshi Ozeki

Research and Creative Activities Poster Day

• Evaluation is a relatively new, practice-based field
• Evaluation scholars lead the field by presenting their theories
• Evaluation theories are not based on empirical evidence
• Empirical investigation is required to establish the field of evaluation
• There were calls for more research on evaluation (RoE)
• The number of studies on RoE has increased in the past decade
• It is unknown whether RoE is important in the evaluation community

Empirical Evaluation Of Different Features Of Design In Confirmatory Factor Analysis, Deyab Almaleki

Dissertations

Factor analysis (FA) is the study of variance within a group. Within-subject variance (WSV) is affected by multiple features in a study context, such as: the study experimental design (ED) and sampling design (SD), thus anything that influences or changes variance may affect the conclusions related to FA.

The aim of this study was to provide empirical evaluation of the influence of different aspects of ED and SD on WSV in the context of FA in terms of model precision and model estimate stability. Four Monte Carlo population correlation matrices were hypothesized based on different communality magnitudes (high, moderate, low, …

Bivariate Negative Binomial Hurdle With Random Spatial Effects, Robert Mcnutt

Dissertations

Count data with excess zeros widely occur in ecology, epidemiology, marketing, and many other disciplines. Mixture distributions consisting of a point mass at zero and a separate discrete distribution are often employed in regression models to account for excessive zero observations in the data. While Poisson models are very popular for count data, Negative Binomial models provide greater flexibility due to their ability to account for overdispersion.

This research focuses on developing a method for analyzing bivariate count data with excess zeros collected over a lattice. A bivariate Zero-Inflated Negative Binomial Hurdle (ZINBH) regression model with spatial random effects is …

Bayesian Rank Based Methods For Linear And Generalized Linear Models, James Kodzo Dzikunu

Dissertations

A Bayesian Rank Based Method for linear models is developed in this research. The estimation of the regression coefficients is based on the full conditional distributions utilizing a rank based initial fit. The data likelihood is based on the asymptotic distribution of the gradient function and the asymptotic linearity of this rank-based procedure. Prior distributions are put on regression coefficient(s) and scale parameter(s). The effects of different priors on this scale parameter(s) are studied. Using these full conditional distributions, the estimates are obtained by a Markov Chain Monte-Carlo (MCMC) procedure. The results of our simulation studies show that these Bayesian …

Poisson Versus Negative Binomial Regression In The Analysis Of Count Data, Barbie Ann L. Bugna

Dissertations

Commonly used tests for treatment effect in kx2 frequency data are Poisson regression, negative binomial regression, and Cochran-Mantel-Haentzel. In practice, Poisson regression or CMH is used as default, and NB regression is used only when there is reason to believe the data has overdispersion beyond what is expected of Poisson counts.

We show that the Poisson regression is sensitive to the Poisson assumption, and does not maintain its size in the presence of overdispersion. In particular, it tends to interpret overdispersion as significant treatment effect. Thus there is a need for a reliable pretest for the Poisson assumption. A commonly …

Rank Based Procedures For Ordered Alternative Models, Yuanyuan Shao

Dissertations

The ordered alternatives in a one-way layout with k ordered treatment levels are appropriate for many applications, especially in psychology and medicine. There is extensive literature in this area, and many parametric and nonparametric approaches have been introduced. Abelson-Tukey (AT) test is a frequently used parametric method. Its coefficients provide an ideal way of combining means for the purpose of detecting a monotonic relationship between the independent and dependent variables. The AT method, though, is not robust. Furthermore, our initial empirical studies show that it is not more powerful than the Jonckheere-Terpstra (JT) and the Hettmansperger- Norton (HN) nonparametric tests …

Failing To Replicate: Hypothesis Testing As A Crucial Key To Make Direct Replications More Credible And Predictable, Pedro Fernando Mateu Bullón

Dissertations

Theory cannot be fully validated unless the original results have been replicated, resulting in conclusion consistency. Replications are the strongest source to verify research findings and knowledge claims. Sciences such as medicine, chemistry, physics, genetics, and biology, are considered successful because their knowledge claims are buttressed by a large set of replications of original studies. Unfortunately in the social sciences many attempts to replicate fail and thus there is a continuing need for replication studies to confirm facts, expand knowledge to gain new understanding, and verify hypotheses. Two plausible explanations for the failure to replicate in the social sciences could …

Three Essays On Panel Data Estimation, Alexander Houser

Dissertations

This work discusses various aspects of panel data estimation. In chapter one, an algorithm for semiparametric random effects estimation is proposed. The performance of bootstrap-based confidence intervals for the proposed estimators are examined and found reasonable. The algorithm is also applied to a set of U.S. state level medical expenditure data to estimate the medical Engel curve. In the second chapter, the predictive performance of various parametric and semiparametric panel data estimators is compared on the same dataset of U.S. state level medical expenditures as well as out of sample forecast performance and bootstrap bias-corrected mean square errors of the …

Ranked Based Procedures For Ordered Alternative Models, Yuanyuan Shao

Research and Creative Activities Poster Day

The ordered alternatives in a one-way layout with k ordered treatment levels are appropriate for many applications, especially in psychology and medicine. There is an extensive literature in this area, and many parametric and nonparametric approaches have been introduced. This study uses rank based estimators to robustify the Abelson-Tukey method. The approach extends to the two-way layout with b blocks and k treatments. One of the two statistics having maximum asymptotic local power and the greatest efficiency when the alternative hypothesis consists of a specific pattern, and extended research has been completed on detecting ordered alternatives with unknown peaks.

Lnference On Differences In K Means For Data With Excess Zeros And Detection Limits, Haolai Jiang

Dissertations

Many data have excess zeros or unobservable values falling below detection limit. For example, data on hospitalization costs incurred by members of a health insurance plan will have zeros for the percentage who did not get sick. Benzene exposure measurements on petroleum re nery workers have some exposures fall below the limit of detection. Traditional methods of inference like one-way ANOVA are not appropriate to analyze such data since the point mass at zero violates typical distribution assumptions.

For testing for equality of means of k distributions, we will propose a likelihood ratio test that accounts for excess zeros or …

Comparison Of Hazard, Odds And Risk Ratio In The Two-Sample Survival Problem, Benedict P. Dormitorio

Dissertations

Cox proportional hazards is the standard method for analyzing treatment efficacy when time-to-event data is available. In the absence of time-to-event, investigators may use logistic regression which only requires relative frequencies of events, or Poisson regression which requires only interval-summarized frequency tables of time-to-event. When event frequencies are used instead of time-to-events, does it always result in a loss in power?

We investigate the relative performance of the three methods. In particular, we compare the power of tests based on the respective effect-size estimates (1)hazard ratio (HR), (2)odds ratio (OR), and (3)risk ratio (RR). We use a variety of survival …

A Comparison Of Students’ Perceptions Of Stress In Parallel Problem-Based And Lecture-Based Curricula, Sonia Wardley, Brooks Applegate, Deyab Almaleki, James Van Rhee

Research and Creative Activities Poster Day

Introduction

What is stress? Research asserts that stress is the mental state that results from an inability to cope (Burton 2004)

Why focus on stress?

• Persistent stress can lead to serious psychological problems such as interpersonal difficulties, depression, anxiety, and even suicide (Shapiro 2000)
• Several studies have found up to a third of medical students experience stress-related problems

The importance of this study comes from: A review of the extent literature suggests there is no systematic inquiry of the effects of stress experienced by students in LBL and PBL curricula in PA education

A Metaevaluation Of Energy Efficiency Evaluations, Brandy Brown

Dissertations

This study systematically reviews the methodological characteristics of energy efficiency evaluations and uses metaevaluation to assess its quality. Metaevaluation is used to systematically assess the quality of evaluation products, confirm that evaluations deliver sound findings and conclusions, are useful to the client, are credible, are ethically conducted, and are done as cost-effective as possible. The results of this study show that the ability to accurately assess evaluation for methodological quality using evaluations reports as a primary data source depends on the presence of detailed descriptions of evaluation methods. Furthermore, the study suggests that methodological variations of energy efficiency evaluations coalesce …

Multivariate Autoregressive Time Series Using Schweppe Weighted Wilcoxon Estimates, Jaime Burgos

Dissertations

The increasing needs of forecasting techniques has led to the popularity of the vector autoregressive model in multivariate time series analysis, which has become of typical use across different fields due to its simplicity in application. The traditional method for estimating the model parameters is the least squares minimization, due to the linear nature of the model and its similarity with multivariate linear regression. However, since least squares estimates are sensitive to outliers, more robust techniques have become of interest. This manuscript investigates a robust alternative by obtaining the estimates using a weighted Wilcoxon dispersion with Schweppe-type weights. The first …

A Metaevaluation Of Evaluations Of Health Care Programs That Employ The Chronic Care Model, Jan Fields

Dissertations

Background: The purpose of this dissertation is to explore the use of metaevaluation to evaluate the quality of healthcare studies conducted on programs that employ the Chronic Care Model (CCM) to provide chronic illness care. In this study, healthcare studies of CCM programs are regarded as program evaluations. Method: Using a non-experimental cross-sectional design, 28 healthcare studies of CCM programs were evaluated using the accuracy standards portion of the Program Evaluations Metaevaluation Checklist (Stufflebeam, 2011). The results of the metaevaluations were analyzed and compared to the HEAL grade of the same healthcare studies as determined by the Hierarchy of Evidence …

Using Multi-Objective Value Estimation To Support Predictive Analytics For Human Service Project Management, David D. Wingard

Dissertations

Human service organizations need outcome measurement approaches that support project management for efficiency and effectiveness. While, in recent years, human services have increased their capacity to manage data and measure outcomes empirically, several barriers remain. First, current outcome measurement practices are not designed to effectively support the management of human services programs for maximum efficiency and effectiveness. Second, human services organizations need a methodology to manage programs to identified outcomes. This dissertation explored meaningful solutions to both issues. In Paper 1 (Chapter II), this dissertation assessed strengths and limitations of current outcome evaluation approaches and suggested an innovative application of …

Improving The Design Of Cluster-Randomized Trials In Education: Informing The Selection Of Variance Design Parameter Values For Science Achievement Studies, Carl D. Westine

Dissertations

The purpose of this three-essay dissertation is to provide practical guidance to evaluators planning cluster-randomized trials (CRTs) of science achievement. In an educational setting, interventions are often administered at the cluster level, while outcomes are typically measured at the student level through standardized achievement testing. When evaluating an intervention, a CRT is appropriate because it allows for treatment to be modeled at a different level than the unit of analysis, and properly accounts for the violation of independence that occurs due to nesting. Accurately designing a CRT involves estimating variance parameters (i.e., intraclass correlations [ICCs] and percent of variance explained …

Harnessing Complexity: Analysis Methodology And Ethical Framework To Facilitate Utilization Of Video Data In Evaluations, Kurt A. Wilson

Dissertations

Most evaluations in the nonprofit and international development sectors are conducted in contexts of complexity; the specific intervention being evaluated is but one of many interrelated factors influencing the desired outcome. Video data, especially when directly generated by program participants, can provide both exceptionally rich qualitative data as well as contextually-relevant feedback within complex systems. Despite these unique strengths and opportunities, video data is underutilized in the field of evaluation. This dissertation addresses specific barriers associated with video data through three inter-related papers: Papers one and two (Chapters II and III) present the findings from two interrelated studies of an …

Estimation And Inference For Spatial And Spatio-Temporal Mixed Effects Models, Casey M. Jelsema

Dissertations

One of the most common goals of geostatistical analysis is that of spatial prediction, in other words: filling in the blank areas of the map. There are two popular methods for accomplishing spatial prediction. Either kriging, or Bayesian hierarchical models. Both methods require the inverse of the spatial covariance matrix of the data. As the sample size, n, becomes large, both of these methods become impractical. Reduced rank spatial models (RRSM) allow prediction on massive datasets without compromising the complexity of the spatial process. This dissertation focuses on RRSMs, particularly situations where the data follow non-Gaussian distributions.

The manner in …

A Robust Estimate For The Bifurcating Autoregressive Model With Application To Cell Lineage Data, Tamer M. E. Elbayoumi

Dissertations

The bifurcating autoregressive model (BAR) is commonly used to model binary tree data. One application for this model relates to cell lineage data in biology. The purpose of studying the cell lineage process is to know whether the observed correlations between related cells are due to similarities in the environmental, inherited effects, or a combination of both of them. Because outliers in this kind of data are quite common, the need for a robust estimation procedure is necessary. A weighted L1 (WL1) estimate for estimating the parameters of the BAR model is considered. When the weights are constant, the estimate …