Digital Commons Network^™

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.

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. …

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 …

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.

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 …

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 …

Profiles Of Drug Endangered Children: Investigation In A Clinical Sample, Imanie Samanmali Wijayaratne

Loma Linda University Electronic Theses, Dissertations & Projects

Despite the increase in children born prenatally exposed to methamphetamine, little is known about the cognitive and neuropsychological outcomes of these children. Research specific to prenatal-methamphetamine exposure is extremely limited and has been primarily restricted to rat studies. This research combined with the few studies examining children prenatally exposed to methamphetamine suggests that methamphetamine-exposure is associated with various cognitive and neuropsychological delays and is impacted by both biological and environmental factors. Given the scarcity of research in this area, the current study used archival data from a psychological assessment clinic to (1) describe the frequency of prenatal methamphetamine-exposure cases, (2) …

Observer Reliability Of Cephalometric Landmark Identification On 3-D Mr Images, Michael S. Pollack

Loma Linda University Electronic Theses, Dissertations & Projects

Introduction: Cephalometric analysis is a cornerstone of orthodontic diagnosis, yet much information is lost when 3-dimensional structures are assessed with 2-dimensional methods. CBCT offers 3-dimensional imaging but at the cost of higher levels of ionizing radiation. Magnetic resonance imaging provides 3-dimensional imaging without ionizing radiation and additionally imparts visualization of soft tissue structures. Prior to employing MR images for cephalometric analysis, reliability of landmark identification must be assessed. The purpose of this study was to evaluate intra- and interobserver reliability in 3-dimensional landmark identification using MR images.

Materials and Methods: Fifteen cranial MR images (3.0 T, MP-RAGE) from subjects between …

Using Cone Beam Computed Tomography To Identify A Prediction Model For Obstructive Sleep Apnea, Jodi Parker

Loma Linda University Electronic Theses, Dissertations & Projects

Introduction: Obstructive Sleep Apnea (OSA) patients have increased risk of morbidity and mortality. Early diagnosis may reduce morbidity and mortality. Prediction of OSA from imaging may help to identify OSA patients earlier in life. CBCT can be used for OSA diagnostic imaging due to its three-dimensional (3D) visualization of the upper airway and craniofacial complex. Magnification associated with conventional 2D radiography is eliminated with CBCT, and radiation to the patient is significantly less than previous modalities used to measure craniofacial & airway measurements associated with OSA. During a CBCT scan, the patient's image is taken supine, rather than the upright …

Study Of The Four Factor Theory Of Women’S Sexual Function, Julie M. Merrell

Loma Linda University Electronic Theses, Dissertations & Projects

Tiefer, Hall, and Tavris (2002) described factors comprising four categories of female sexual function. They suggested that unique factors need to be examined to understand sexual function in women. Socio-cultural, political, or economic factors, partner and relationship factors, psychological factors, and medical factors were described as aspects of women’s lives that can be the source of sexual dysfunction. In a previous study, Merrell (2007) utilized Tiefer et al’s (2002) four factor model of sexual functioning to examine female sexual functioning looking specifically at body shame, relationship satisfaction, positive and negative affect, sexual self-schema, and overall health. Based on the results …

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, …

Comparison Of Rationally-Derived And Empirically-Derived Methods For Predicting Failure In Residential Treatment, Jennifer Pester Grattan

Loma Linda University Electronic Theses, Dissertations & Projects

Patient-focused research methods have been used in adult mental health treatment to improve outcomes by tracking individual treatment response and comparing it with expected recovery patterns. One such approach has used rationally- and empirically-derived methods to analyze data from the OQ-45 and identify patients who are not responding as expected to treatment. Treatment is then adjusted, improving outcomes and lowering overall costs.

Similar but less extensive research has shown analogous methods can be used with children and adolescents. This would be particularly useful in residential treatment, which is an expensive and inadequately researched approach. This study used archival data gathered …

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 …

Targeted Maximum Likelihood Estimation: A Gentle Introduction, Susan Gruber, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

This paper provides a concise introduction to targeted maximum likelihood estimation (TMLE) of causal effect parameters. The interested analyst should gain sufficient understanding of TMLE from this introductory tutorial to be able to apply the method in practice. A program written in R is provided. This program implements a basic version of TMLE that can be used to estimate the effect of a binary point treatment on a continuous or binary outcome.

Comparing Risk Scoring Systems Beyond The Roc Paradigm In Survival Analysis, Hajime Uno, Lu Tian, Tianxi Cai, Isaac S. Kohane, L. J. Wei

Harvard University Biostatistics Working Paper Series

No abstract provided.

Combinational Mixtures Of Multiparameter Distributions, Valeria Edefonti, Giovanni Parmigiani

Johns Hopkins University, Dept. of Biostatistics Working Papers

We introduce combinatorial mixtures - a flexible class of models for inference on mixture distributions whose component have multidimensional parameters. The key idea is to allow each element of the component-specific parameter vectors to be shared by a subset of other components. This approach allows for mixtures that range from very flexible to very parsimonious, and unifies inference on component-specific parameters with inference on the number of components. We develop Bayesian inference and computation approaches for this class of distributions, and illustrate them in an application. This work was originally motivated by the analysis of cancer subtypes: in terms of …

Shrinkage Estimation Of Expression Fold Change As An Alternative To Testing Hypotheses Of Equivalent Expression, Zahra Montazeri, Corey M. Yanofsky, David R. Bickel

COBRA Preprint Series

Research on analyzing microarray data has focused on the problem of identifying differentially expressed genes to the neglect of the problem of how to integrate evidence that a gene is differentially expressed with information on the extent of its differential expression. Consequently, researchers currently prioritize genes for further study either on the basis of volcano plots or, more commonly, according to simple estimates of the fold change after filtering the genes with an arbitrary statistical significance threshold. While the subjective and informal nature of the former practice precludes quantification of its reliability, the latter practice is equivalent to using a …

The Effects Of Physical Activity And Nutrient Intake On The Risk Of Hip Fracture : Results From The Adventist Health Study-2, Wen-Ling Liao

Loma Linda University Electronic Theses, Dissertations & Projects

This is a two year of follow up study of Adventist Health Study-2 (AHS-2). We assessed the association between physical activity, nutrient intake and risk of hip fracture among peri- and post menopausal Caucasian women using unconditional logistic regression models. All subjects completed a lifestyle questionnaire which including information of physical activity and frequency and portion size of food intake at enrollment into the study (2002-2007). The “Bi-Annual Hospitalization History” questionnaire which included a question about hip fractures due to minor trauma/falls was sent to subjects approximately two years after enrollment, with a response rat of 82.84%. In this cohort, …

Integer-Valued Time Series And Renewal Processes, Yunwei Cui

All Dissertations

This research proposes a new but simple model for stationary time series of integer counts. Previous work in the area has focused on mixture and thinning methods and links to classical time series autoregressive moving-average difference equations; in contrast, our methods use a renewal process to generate a correlated sequence of Bernoulli trials. By superpositioning independent copies of such processes, stationary series with binomial, Poisson, geometric, or any other discrete marginal distribution can be readily constructed. The model class proposed is parsimonious, non-Markov, and readily generates series with either short or long memory autocovariances. The model can be fitted with …

Pattern Recognition For Command And Control Data Systems, Jason Schwier

All Dissertations

To analyze real-world events, researchers collect observation data from an underlying process and construct models to represent the observed situation. In this work, we consider issues that affect the construction and usage of a specific type of model. Markov models are commonly used because their combination of discrete states and stochastic transitions is suited to applications with both deterministic and stochastic components. Hidden Markov Models (HMMs) are a class of Markov model commonly used in pattern recognition. We first demonstrate how to construct HMMs using only the observation data, and no a priori information, by extending a previously developed approach …