Statistics and Probability Commons^™

A Linear B-Spline Threshold Dose-Response Model With Dose-Specific Response Variation Applied To Developmental Toxicity Studies, Chin-Shang Li, Daniel L. Hunt

Journal of Modern Applied Statistical Methods

A linear B-spline function was modified to model dose-specific response variation in developmental toxicity studies. In this new model, response variation is assumed to differ across dose groups. The model was applied to a developmental toxicity study and proved to be significant over the previous model of singular response variation.

Jmasm28: Gibbs Sampling For 2pno Multi-Unidimensional Item Response Theory Models (Fortran), Yanyan Sheng, Todd C. Headrick

Journal of Modern Applied Statistical Methods

A Fortran 77 subroutine is provided for implementing the Gibbs sampling procedure to a multiunidimensional IRT model for binary item response data with the choice of uniform and normal prior distributions for item parameters. In addition to posterior estimates of the model parameters and their Monte Carlo standard errors, the algorithm also estimates the correlations between distinct latent traits. The subroutine requires the user to have access to the IMSL library. The source code is available at http://www.siuc.edu/~epse1/sheng/Fortran/MUIRT/GSMU2.FOR. An executable file is also provided for download at http://www.siuc.edu/~epse1/sheng/Fortran/MUIRT/EXAMPLE.zip to demonstrate the implementation of the algorithm on simulated data.

Markov Modeling Of Breast Cancer, Chunling Cong, Chris P. Tsokos

Journal of Modern Applied Statistical Methods

Previous work with respect to the treatments and relapse time for breast cancer patients is extended by applying a Markov chain to model three different types of breast cancer patients: alive without ever having relapse, alive with relapse, and deceased. It is shown that combined treatment of tamoxifen and radiation is more effective than single treatment of tamoxifen in preventing the recurrence of breast cancer. However, if the patient has already relapsed from breast cancer, single treatment of tamoxifen would be more appropriate with respect to survival time after relapse. Transition probabilities between three stages during different time periods, 2-year, …

Impact Of Rank-Based Normalizing Transformations On The Accuracy Of Test Scores, Shira R. Soloman, Shlomo S. Sawilowsky

Journal of Modern Applied Statistical Methods

The purpose of this article is to provide an empirical comparison of rank-based normalization methods for standardized test scores. A series of Monte Carlo simulations were performed to compare the Blom, Tukey, Van der Waerden and Rankit approximations in terms of achieving the T score’s specified mean and standard deviation and unit normal skewness and kurtosis. All four normalization methods were accurate on the mean but were variably inaccurate on the standard deviation. Overall, deviation from the target moments was pronounced for the even moments but slight for the odd moments. Rankit emerged as the most accurate method among all …

Bayesian Analysis Of Evidence From Studies Of Warfarin V Aspirin For Symptomatic Intracranial Stenosis, Vicki Hertzberg, Barney Stern, Karen Johnston

Journal of Modern Applied Statistical Methods

Bayesian analyses of symptomatic intracranial stenosis studies were conducted to compare the benefits of long-term therapy with warfarin to aspirin. The synthesis of evidence of effect from previous nonrandomized studies in monitoring a randomized clinical trial was of particular interest. Sequential Bayesian learning analysis was conducted and Bayesian hierarchical random effects models were used to incorporate variability between studies. The posterior point estimates for the risk rate ratio (RRR) were similar between analyses, although the interval estimates resulting from the hierarchical analyses are larger than the corresponding Bayesian learning analyses. This demonstrated the difference between these methods in accounting for …

A Maximum Test For The Analysis Of Ordered Categorical Data, Markus Neuhäeuser

Journal of Modern Applied Statistical Methods

Different scoring schemes are possible when performing exact tests using scores on ordered categorical data. The standard scheme is based on integer scores, but non-integer scores were proposed to increase power (Ivanova & Berger, 2001). However, different non-integer scores exist and the question arises as to which of the non-integer schemes should be chosen. To solve this problem, a maximum test is proposed. To be precise, the maximum of the competing statistics is used as the new test statistic, rather than arbitrarily choosing one single test statistic.

Intermediate R Values For Use In The Fleishman Power Method, Julie M. Smith

Journal of Modern Applied Statistical Methods

Several intermediate r values are calculated at three different correlations for use in the Fleishman Power Method for generating correlated data from normal and non-normal populations.

The Regular Excluded Minors For Signed-Graphic Matroids, Hongxun Qin, Dan Slilaty, Xiangqian Zhou

Mathematics and Statistics Faculty Publications

We show that the complete list of regular excluded minors for the class of signed-graphic matroids is M*(G₁),...,M*(G₂₉),R₁₅,R₁₆. Here G₁,...,G₂₉ are the vertically 2-connected excluded minors for the class of projective-planar graphs and R₁₅ and R₁₆ are two regular matroids that we will define in the article.

Analysis Of Subgroup Data In Clinical Trials, Kao-Tai Tsai, Karl E. Peace

Biostatistics: Faculty Presentations (2003-2018)

This conference abstract was published in the Proceedings of the Sixteenth Annual Biopharmaceutical Applied Statistics Symposium.

Sequence Comparison And Stochastic Model Based On Multi-Order Markov Models, Xiang Fang

Department of Statistics: Dissertations, Theses, and Student Research

This dissertation presents two statistical methodologies developed on multi-order Markov models. First, we introduce an alignment-free sequence comparison method, which represents a sequence using a multi-order transition matrix (MTM). The MTM contains information of multi-order dependencies and provides a comprehensive representation of the heterogeneous composition within a sequence. Based on the MTM, a distance measure is developed for pair-wise comparison of sequences. The new method is compared with the traditional maximum likelihood (ML) method, the complete composition vector (CCV) method and the improved version of the complete composition vector (ICCV) method using simulated sequences. We further illustrate the application of …

Bayesian Analysis Of Structural Credit Risk Models With Microstructure Noises, Shirley J. Huang, Jun Yu

Research Collection School Of Economics

In this paper a Markov chain Monte Carlo (MCMC) technique is developed for the Bayesian analysis of structural credit risk models with microstructure noises. The technique is based on the general Bayesian approach with posterior computations performed by Gibbs sampling. Simulations from the Markov chain, whose stationary distribution converges to the posterior distribution, enable exact ¯nite sample inferences of model parameters. The exact inferences can easily be extended to latent state variables and any nonlinear transformation of state variables and parameters, facilitating practical credit risk applications. In addition, the comparison of alternative models can be based on deviance information criterion …

Analisis Data Riskesdas 2007/2008: Kontribusi Karakteristik Ibu Terhadap Status Imunisasi Anak Di Indonesia, Sutanto Priyo Hastono

Kesmas

Cakupan imunisasi terbukti dapat menurunkan secara signifikan kejadian kesakitan dan kematian yang diakibatkan penyakit tersebut, tetapi di Indonesia cakupan tersebut tergolong rendah. Tujuan penelitian adalah mengetahui hubungan karakteristik ibu dengan status imunisasi anak di Indonesia. Disain yang digunakan dalam penelitian adalah potong lintang dengan sampel anak yang berumur antara 1-2 tahun yang tinggal di wilayah Indonesia. Sumber data sekunder yang digunakan adalah Riskesdas Depkes tahun 2007/2008. Proporsi anak usia 12-24 bulan yang mendapat imunisasi lengkap adalah 56,2 % (95% CI :55,1-57,3). Pendidikan ibu dan pendidikan suami ditemukan berhubungan secara bermakna dengan status imunisasi dasar pada anak. Hasil analisis multilevel menemukan …

Causal Inference In Epidemiological Studies With Strong Confounding, Kelly L. Moore, Romain S. Neugebauer, Mark J. Van Der Laan, Ira B. Tager

U.C. Berkeley Division of Biostatistics Working Paper Series

One of the identifiabilty assumptions of causal effects defined by marginal structural model (MSM) parameters is the experimental treatment assignment (ETA) assumption. Practical violations of this assumption frequently occur in data analysis, when certain exposures are rarely observed within some strata of the population. The inverse probability of treatment weighted (IPTW) estimator is particularly sensitive to violations of this assumption, however, we demonstrate that this is a problem for all estimators of causal effects. This is due to the fact that the ETA assumption is about information (or lack thereof) in the data. A new class of causal models, causal …

Lasagna Plots: A Saucy Alternative To Spaghetti Plots, Bruce Swihart, Brian Caffo, Bryan D. James, Matthew Strand, Brian S. Schwartz, Naresh M. Punjabi

Johns Hopkins University, Dept. of Biostatistics Working Papers

Longitudinal repeated measures data has often been visualized with spaghetti plots for continuous out- comes. For large datasets, this often leads to over-plotting and consequential obscuring of trends in the data. This is primarily due to overlapping of trajectories. Here, we suggest a framework called lasagna plot ting that constrains the subject-specific trajectories to prevent overlapping and utilizes gradients of color to depict the outcome. Dynamic sorting and visualization is demonstrated as an exploratory data analysis tool. Supplemental material in the form of sample R code additional illustrated examples are available online.

Modeling Multilevel Sleep Transitional Data Via Poisson Log-Linear Multilevel Models, Bruce J. Swihart

COBRA Preprint Series

This paper proposes Poisson log-linear multilevel models to investigate population variability in sleep state transition rates. We specifically propose a Bayesian Poisson regression model that is more flexible, scalable to larger studies, and easily fit than other attempts in the literature. We further use hierarchical random effects to account for pairings of individuals and repeated measures within those individuals, as comparing diseased to non-diseased subjects while minimizing bias is of epidemiologic importance. We estimate essentially non-parametric piecewise constant hazards and smooth them, and allow for time varying covariates and segment of the night comparisons. The Bayesian Poisson regression is justified …

Quasi-Least Squares With Mixed Linear Correlation Structures, Jichun Xie, Justine Shults, Jon Peet, Dwight Stambolian, Mary F. Cotch

UPenn Biostatistics Working Papers

Quasi-least squares (QLS) is a two-stage computational approach for estimation of the correlation parameters in the framework of generalized estimating equations (GEE). We prove two general results for the class of mixed linear correlation structures: namely, that the stage one QLS estimate of the correlation parameter always exists and is feasible (yields a positive definite estimated correlation matrix) for any correlation structure, while the stage two estimator exists and is unique (and therefore consistent) with probability one, for the class of mixed linear correlation structures. Our general results justify the implementation of QLS for particular members of the class of …

The Em Algorithm For Group Testing Regression Models Under Matrix Pooling, Christopher R. Bilder, Boan Zhang

Department of Statistics: Faculty Publications

No abstract provided.

Student Fact Book, Fall 2009, Thirty-Third Annual Edition, Wright State University, Office Of Student Information Systems, Wright State University

Wright State University Student Fact Books

The student fact book has general demographic information on all students enrolled at Wright State University for Fall Quarter, 2009.

Design And Implementation Of S-Marks: A Secure Middleware For Pervasive Computing Applications, Sheikh Iqbal Ahamed, Haifeng Li, Nilothpal Talukder, Mehrab Monjur, Chowdhury Sharif Hasan

Mathematics, Statistics and Computer Science Faculty Research and Publications

As portable devices have become a part of our everyday life, more people are unknowingly participating in a pervasive computing environment. People engage with not a single device for a specific purpose but many devices interacting with each other in the course of ordinary activity. With such prevalence of pervasive technology, the interaction between portable devices needs to be continuous and imperceptible to device users. Pervasive computing requires a small, scalable and robust network which relies heavily on the middleware to resolve communication and security issues. In this paper, we present the design and implementation of S-MARKS which incorporates device …

Detectability Of Convex-Shaped Objects In Digital Images, Its Fundamental Limit And Multiscale Analysis, Xiaoming Huo, Xuelei (Sherry) Ni

Faculty Articles

Given a convex-shape inhomogeneous region embedded in a noisy image, we consider the conditions under which such an embedded region is detectable. The existence of low order-of-complexity detection algorithms is also studied. The main results are (1) an analytical threshold (of a statistic) that specifies what is detectable, and (2) the existence of a multiscale detection algorithm whose order of complexity is roughly the optimal O(n(2) log(2) (n)).

Our analysis has two main components. We first show that in a discrete image, the number of convex sets increases faster than any finite degree polynomial of the image size n. Hence …

Investigation Of Mlb Data With Multivariate Statistics, Vincent Milano

Statistics

A statistical study was performed in order to explore the relationships of the offensive player statistics for every player in the 2008 Major League Baseball season. The purpose of the study was to explore various multivariate statistical methods within the data set.

The offensive variables in the study are: games, at-bats, runs, hits, singles, doubles, triples, homeruns, extra base hits, runs batted in, total bases, walks, strikeouts, stolen bases, times caught stealing, on-base percentage, slugging percentage, on-base plus slugging percentage, and batting average. All variables are season totals except for onbase percentage, slugging percentage, on-base plus slugging, and batting average. …

Composite Likelihood Em Algorithm With Applications To Multivariate Hidden Markov Model , Xin Gao, Peter Xuekun Song

COBRA Preprint Series

The method of composite likelihood is useful to deal with estimation and inference in parametric models with high-dimensional data, where the full likelihood approach renders to intractable computational complexity. We develop an extension of the EM algorithm in the framework of composite likelihood estimation in the presence of missing data or latent variables. We establish three key theoretical properties of the composite likelihood EM (CLEM) algorithm, including the ascent property, the algorithmic convergence and the convergence rate. The proposed method is applied to estimate the transition probabilities in multivariate hidden Markov model. Simulation studies are presented to demonstrate the empirical …

Readings In Targeted Maximum Likelihood Estimation, Mark J. Van Der Laan, Sherri Rose, Susan Gruber

U.C. Berkeley Division of Biostatistics Working Paper Series

This is a compilation of current and past work on targeted maximum likelihood estimation. It features the original targeted maximum likelihood learning paper as well as chapters on super (machine) learning using cross validation, randomized controlled trials, realistic individualized treatment rules in observational studies, biomarker discovery, case-control studies, and time-to-event outcomes with censored data, among others. We hope this collection is helpful to the interested reader and stimulates additional research in this important area.

Robustness Of Semiparametric Efficiency In Nearly-Correct Models For Two-Phase Samples, Thomas Lumley

UW Biostatistics Working Paper Series

Augmented inverse-probability weighted (AIPW) estimators for incomplete-data models typically do not have full semiparametric efficiency, but do have model-robustness properties not shared by the efficient estimator. We examine the performance of efficient and AIPW estimators when the complete-data model is nearly correctly specified, in the sense that the misspecification is not reliably detectable from the data by any possible diagnostic or test. Asymptotic results for these nearly true models are obtained by representing them as sequences of misspecified models that are mutually contiguous with a correctly specified model. For some least favorable direction of model misspecification the bias in the …

Causal Inference For Nested Case-Control Studies Using Targeted Maximum Likelihood Estimation, Sherri Rose, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

A nested case-control study is conducted within a well-defined cohort arising out of a population of interest. This design is often used in epidemiology to reduce the costs associated with collecting data on the full cohort; however, the case control sample within the cohort is a biased sample. Methods for analyzing case-control studies have largely focused on logistic regression models that provide conditional and not marginal causal estimates of the odds ratio. We previously developed a Case-Control Weighted Targeted Maximum Likelihood Estimation (TMLE) procedure for case-control study designs, which relies on the prevalence probability q0. We propose the use of …

Redefining Cpg Islands Using A Hideen Markov Model, Hao Wu, Brain Caffo, Harris A. Jaffee, Andrew P. Feinberg, Rafael A. Irizarry

Johns Hopkins University, Dept. of Biostatistics Working Papers

The DNA of most vertebrates is depleted in CpG dinucleotides; C followed by a G in the 5’ to 3’ direction. CpGs are the target for DNA methylation, a chemical modification of cytosine (C) heritable during cell division and the most well characterized epigenetic mechanism. The remaining CpGs tend to cluster in regions referred to as CpG islands (CGI). Knowing CGI locations is important because they mark functionally relevant epigenetic loci in development and disease. For various mammals, including human, a readily available and widely used list of CGI is available from the UCSC Genome Browser. This list was derived …

Deriving Optimal Composite Scores: Relating Observational/Longitudinal Data With A Primary Endpoint, Rhonda Ellis

Theses and Dissertations

In numerous clinical/experimental studies, multiple endpoints are measured on each subject. It is often not clear which of these endpoints should be designated as of primary importance. The desirability function approach is a way of combining multiple responses into a single unitless composite score. The response variables may include multiple types of data: binary, ordinal, count, interval data. Each response variable is transformed to a 0 to1 unitless scale with zero representing a completely undesirable response and one representing the ideal value. In desirability function methodology, weights on individual components can be incorporated to allow different levels of importance to …

The Scher Report On Non-Human Primate Research — Biased And Deeply Flawed, Jarrod Bailey, Katy Taylor

Experimentation Collection

The European Commission’s Scientific Committee on Health and Environmental Risks (SCHER) recently issued an Opinion on the need for non-human primate (NHP) use in biomedical research, and the possibilities of replacing NHP use with alternatives, as part of the Directive 86/609/EEC revision process. Here, we summarise our recent complaint to the European Ombudsman about SCHER’s Opinion and the entire consultation process. It is our opinion that the Working Group almost entirely failed to address its remit, and that the Group was unbalanced and contained insufficient expertise. The Opinion presumed the validity of NHP research with inadequate supporting evidence, and ignored …

Impact Of Ambient Air Pollution On Survival Of Renal Transplant Recipients, Rhonda Kristine Hwang

Loma Linda University Electronic Theses, Dissertations & Projects

There is increasing evidence that ambient air pollution is associated with coronary heart disease morbidity and mortality. This research has focused on the general public and less so on possible sensitive subgroups even though these may have even greater susceptibility to adverse effects of ambient air pollution. With highly prevalent traditional as well as nontraditional risk factors, renal transplant recipients may potentially be a sensitive subgroup. The purpose of this study was to evaluate the possible effect of between long-term exposure to air pollution on the risk of CHD mortality among renal transplant recipients. This cohort study includes 32,239 adult, …

Neurodevelopmental Outcome & Mr Spectroscopy Of Therapeutic Hypothermia After Pediatric Drowning, Sharon Mieras Perugini

Loma Linda University Electronic Theses, Dissertations & Projects

Despite advances in medical treatment and technology, outcome following pediatric drowning can vary widely from mild to severe impairments and death. Prognosis is often difficult to predict given a number of contributing factors. As such, this study examined the relationship between clinical indicators including submersion duration, initial GCS and PRISM scores, and waking time with outcome as well as metabolite ratios based on magnetic resonance spectroscopy. Research stemming from the area of cardiac arrest as well as anecdotal case study reports of cold water drownings suggests that lowering the body temperature may be helpful and protective. As such, the use …