Biostatistics Commons^™

Robust Alternatives To Ancova For Estimating The Treatment Effect Via A Randomized Comparative Study, Fei Jiang, Lu Tian, Haoda Fu, Takahiro Hasegawa, Marc Alan Pfeffer, L. J. Wei

Harvard University Biostatistics Working Paper Series

In comparing two treatments via a randomized clinical trial, the analysis of covari- ance technique is often utilized to estimate an overall treatment effect. The ANCOVA is generally perceived as a more efficient procedure than its simple two sample estima- tion counterpart. Unfortunately when the ANCOVA model is not correctly specified, the resulting estimator is generally not consistent especially when the model is nonlin- ear. Recently various nonparametric alternatives, such as the augmentation methods, to ANCOVA have been proposed to estimate the treatment effect by adjusting the covariates. However, the properties of these alternatives have not been studied in the …

Evaluating The Efficiency Of Treatment Comparison In Crossover Design By Allocating Subjects Based On Ranked Auxiliary Variable, Yisong Huang, Hani Samawi, Robert Vogel, Jingjing Yin, Worlanyo E. Gato, Daniel Linder

Biostatistics: Faculty Publications

The validity of statistical inference depends on proper randomization methods. However, even with proper randomization, we can have imbalanced with respect to important characteristics. In this paper, we introduce a method based on ranked auxiliary variables for treatment allocation in crossover designs using Latin squares models. We evaluate the improvement of the efficiency in treatment comparisons using the proposed method. Our simulation study reveals that our proposed method provides a more powerful test compared to simple randomization with the same sample size. The proposed method is illustrated by conducting an experiment to compare two different concentrations of titanium dioxide nanofiber …

Hidden Markov Chain Analysis: Impact Of Misclassification On Effect Of Covariates In Disease Progression And Regression, Haritha Polisetti

USF Tampa Graduate Theses and Dissertations

Most of the chronic diseases have a well-known natural staging system through which the disease progression is interpreted. It is well established that the transition rates from one stage of disease to other stage can be modeled by multi state Markov models. But, it is also well known that the screening systems used to diagnose disease states may subject to error some times. In this study, a simulation study is conducted to illustrate the importance of addressing for misclassification in multi-state Markov models by evaluating and comparing the estimates for the disease progression Markov model with misclassification opposed to disease …

Censoring Unbiased Regression Trees And Ensembles, Jon Arni Steingrimsson, Liqun Diao, Robert L. Strawderman

Johns Hopkins University, Dept. of Biostatistics Working Papers

This paper proposes a novel approach to building regression trees and ensemble learning in survival analysis. By first extending the theory of censoring unbiased transformations, we construct observed data estimators of full data loss functions in cases where responses can be right censored. This theory is used to construct two specific classes of methods for building regression trees and regression ensembles that respectively make use of Buckley-James and doubly robust estimating equations for a given full data risk function. For the particular case of squared error loss, we further show how to implement these algorithms using existing software (e.g., CART, …

Prevalence Of And Risk Factors For Adolescent Obesity In Tennessee Using The 2010 Youth Risk Behavior Survey (Yrbs) Data: An Analysis Using Weighted Hierarchical Logistic Regression, Shimin Zheng, Nicole Holt, Jodi L. Southerland, Yan Cao, Trevor Taylor, Deborah L. Slawson, Mark Bloodworth

ETSU Faculty Works

Background: The rate of adolescent overweight and obesity has more than quadrupled over the past few decades, and has become a major public health problem [1]. In 2011, 55% of 12-19 year olds in the United States (U.S.) were overweight or obese [2]. Adolescence is a pivotal time in which many health risk behaviors such as tobacco, alcohol, and drug use are initiated. Such health risk behaviors have been significantly associated with overweight and obesity among adolescents.

Objective: The purpose of this study is to evaluate the relationship between obesity and the health risk behaviors most commonly associated with premature …

High-Throughput Allele-Specific Expression Across 250 Environmental Conditions, Gregory A. Moyerbrailean, Allison L. Richards, Daniel Kurtz, Cynthia A. Kalita, Gordon O. Davis, Chris T. Harvey, Adnan Alazizi, Donovan Watza, Yoram Sorokin, Nancy J. Hauff, Xiang Zhou, Xiaoquan Wen, Roger Pique-Regi, Francesca Luca

Center for Molecular Medicine and Genetics

Gene-by-environment (GxE) interactions determine common disease risk factors and biomedically relevant complex traits. However, quantifying how the environment modulates genetic effects on human quantitative phenotypes presents unique challenges. Environmental covariates are complex and difficult to measure and control at the organismal level, as found in GWAS and epidemiological studies. An alternative approach focuses on the cellular environment using in vitro treatments as a proxy for the organismal environment. These cellular environments simplify the organism-level environmental exposures to provide a tractable influence on subcellular phenotypes, such as gene expression. Expression quantitative trait loci (eQTL) mapping studies identified GxE interactions in response …

Online Cross-Validation-Based Ensemble Learning, David Benkeser, Samuel D. Lendle, Cheng Ju, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Online estimators update a current estimate with a new incoming batch of data without having to revisit past data thereby providing streaming estimates that are scalable to big data. We develop flexible, ensemble-based online estimators of an infinite-dimensional target parameter, such as a regression function, in the setting where data are generated sequentially by a common conditional data distribution given summary measures of the past. This setting encompasses a wide range of time-series models and as special case, models for independent and identically distributed data. Our estimator considers a large library of candidate online estimators and uses online cross-validation to …

Doubly-Robust Nonparametric Inference On The Average Treatment Effect, David Benkeser, Marco Carone, Mark J. Van Der Laan, Peter Gilbert

U.C. Berkeley Division of Biostatistics Working Paper Series

Doubly-robust estimators are widely used to draw inference about the average effect of a treatment. Such estimators are consistent for the effect of interest if either one of two nuisance parameters is consistently estimated. However, if flexible, data-adaptive estimators of these nuisance parameters are used, double-robustness does not readily extend to inference. We present a general theoretical study of the behavior of doubly-robust estimators of an average treatment effect when one of the nuisance parameters is inconsistently estimated. We contrast different approaches for constructing such estimators and investigate the extent to which they may be modified to also allow doubly-robust …

On Combining Family- And Population- Based Sequencing Data, Yuriko Katsumata, David W. Fardo

Biostatistics Faculty Publications

Several statistical group-based approaches have been proposed to detect effects of variation within a gene for each of the population- and family-based designs. However, unified tests to combine gene-phenotype associations obtained from these 2 study designs are not yet well established. In this study, we investigated the efficient combination of population-based and family-based sequencing data to evaluate best practices using the Genetic Analysis Workshop 19 (GAW19) data set. Because one design employed whole genome sequencing and the other whole exome sequencing, we examined variants overlapping both data sets. We used the family-based sequence kernel association test (famSKAT) to analyze the …

Causal Effect Estimation In Sequencing Studies: A Bayesian Method To Account For Confounder Adjustment Uncertainty, Chi Wang, Jinpeng Liu, David W. Fardo

Biostatistics Faculty Publications

Estimating the causal effect of a single nucleotide variant (SNV) on clinical phenotypes is of interest in many genetic studies. The effect estimation may be confounded by other SNVs as a result of linkage disequilibrium as well as demographic and clinical characteristics. Because a large number of these other variables, which we call potential confounders, are collected, it is challenging to select and adjust for the variables that truly confound the causal effect. The Bayesian adjustment for confounding (BAC) method has been proposed as a general method to estimate the average causal effect in the presence of a large number …

Comparing Performance Of Non-Tree-Based And Tree-Based Association Mapping Methods, Katherine L. Thompson, David W. Fardo

Statistics Faculty Publications

A central goal in the biomedical and biological sciences is to link variation in quantitative traits to locations along the genome (single nucleotide polymorphisms). Sequencing technology has rapidly advanced in recent decades, along with the statistical methodology to analyze genetic data. Two classes of association mapping methods exist: those that account for the evolutionary relatedness among individuals, and those that ignore the evolutionary relationships among individuals. While the former methods more fully use implicit information in the data, the latter methods are more flexible in the types of data they can handle. This study presents a comparison of the 2 …

Performance-Constrained Binary Classification Using Ensemble Learning: An Application To Cost-Efficient Targeted Prep Strategies, Wenjing Zheng, Laura Balzer, Maya L. Petersen, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Binary classifications problems are ubiquitous in health and social science applications. In many cases, one wishes to balance two conflicting criteria for an optimal binary classifier. For instance, in resource-limited settings, an HIV prevention program based on offering Pre-Exposure Prophylaxis (PrEP) to select high-risk individuals must balance the sensitivity of the binary classifier in detecting future seroconverters (and hence offering them PrEP regimens) with the total number of PrEP regimens that is financially and logistically feasible for the program to deliver. In this article, we consider a general class of performance-constrained binary classification problems wherein the objective function and the …

Matching The Efficiency Gains Of The Logistic Regression Estimator While Avoiding Its Interpretability Problems, In Randomized Trials, Michael Rosenblum, Jon Arni Steingrimsson

Johns Hopkins University, Dept. of Biostatistics Working Papers

Adjusting for prognostic baseline variables can lead to improved power in randomized trials. For binary outcomes, a logistic regression estimator is commonly used for such adjustment. This has resulted in substantial efficiency gains in practice, e.g., gains equivalent to reducing the required sample size by 20-28% were observed in a recent survey of traumatic brain injury trials. Robinson and Jewell (1991) proved that the logistic regression estimator is guaranteed to have equal or better asymptotic efficiency compared to the unadjusted estimator (which ignores baseline variables). Unfortunately, the logistic regression estimator has the following dangerous vulnerabilities: it is only interpretable when …

Pleiotropic Effects Of Csf Levels Of Alzheimer’S Disease Proteins, Olga A. Vsevolozhskaya, Ilai Keren, David W. Fardo, Dmitri V. Zaykin

Biostatistics Presentations

Cerebrospinal fluid (CSF) analytes harbor potential as diagnostic biomarkers for Alzheimer’s Disease (AD). Quantitative measures of CSF proteins comprise a set of often highly correlated endophenotypes that have previously shown promise in genetic analyses (Cruchaga et al., 2013; Kauwe et al., 2014). Pleiotropic impact of genetic variations on this set may provide additional insights into AD pathology at its earliest stages. To determine which specific endophenotypes are pleiotropic, one can employ methods based on the reverse regression of genotype on phenotypes. Recently, we proposed a method based functional linear models (Vsevolozhskaya et al, 2016) that utilizes reverse regression and simultaneously …

Using Low-Dose Radiation To Potentiate The Effect Of Induction Chemotherapy In Head And Neck Cancer: Results Of A Prospective Phase 2 Trial, Susanne M. Arnold, Mahesh Kudrimoti, Emily V. Dressler, John F. Gleason, Natalie L. Silver, William F. Regine, Joseph Valentino

Internal Medicine Faculty Publications

Purpose: Low-dose fractionated radiation therapy (LDFRT) induces effective cell killing through hyperradiation sensitivity and potentiates effects of chemotherapy. We report our second investigation of LDFRT as a potentiator of the chemotherapeutic effect of induction carboplatin and paclitaxel in locally advanced squamous cell cancer of the head and neck (SCCHN).

Experimental Design: Two cycles of induction therapy were given every 21 days: paclitaxel (75 mg/m²) on days 1, 8, and 15; carboplatin (area under the curve 6) day 1; and LDFRT 50 cGy fractions (2 each on days 1, 2, 8, and 15). Objectives included primary site complete response …

Estimation Of P(X > Y) When X And Y Are Dependent Random Variables Using Different Bivariate Sampling Schemes, Hani M. Samawi, Amal Helu, Haresh Rochani, Jingjing Yin, Daniel Linder

Biostatistics: Faculty Publications

The stress-strength models have been intensively investigated in the literature in regards of estimating the reliability θ = P (X > Y) using parametric and nonparametric approaches under different sampling schemes when X and Y are independent random variables. In this paper, we consider the problem of estimating θ when (X, Y) are dependent random variables with a bivariate underlying distribution. The empirical and kernel estimates of θ = P (X > Y), based on bivariate ranked set sampling (BVRSS) are considered, when (X, Y) are paired dependent continuous random variables. The estimators obtained are compared to their counterpart, bivariate simple random …

Weighted-Samgsr: Combining Significance Analysis Of Microarray-Gene Set Reduction Algorithm With Pathway Topology-Based Weights To Select Relevant Genes, Suyan Tian, Howard H. Chang, Chi Wang

Biostatistics Faculty Publications

Background: It has been demonstrated that a pathway-based feature selection method that incorporates biological information within pathways during the process of feature selection usually outperforms a gene-based feature selection algorithm in terms of predictive accuracy and stability. Significance analysis of microarray-gene set reduction algorithm (SAMGSR), an extension to a gene set analysis method with further reduction of the selected pathways to their respective core subsets, can be regarded as a pathway-based feature selection method.

Methods: In SAMGSR, whether a gene is selected is mainly determined by its expression difference between the phenotypes, and partially by the number of pathways to …

Fto Genotype And Weight Loss: Systematic Review And Meta-Analysis Of 9563 Individual Participant Data From Eight Randomised Controlled Trials., Katherine M Livingstone, Carlos Celis-Morales, George D Papandonatos, Bahar Erar, Jose C Florez, Kathleen A Jablonski, Cristina Razquin, Amelia Marti, Yoriko Heianza, Tao Huang, Frank M Sacks, Mathilde Svendstrup, Xuemei Sui, Timothy S Church, Tiina Jääskeläinen, Jaana Lindström, Jaakko Tuomilehto, Matti Uusitupa, Tuomo Rankinen, Wim H M Saris, Torben Hansen, Oluf Pedersen, Arne Astrup, Thorkild I A Sørensen, Lu Qi, George A Bray, Miguel A Martinez-Gonzalez, J Alfredo Martinez, Paul W Franks, Jeanne M Mccaffery, Jose Lara, John C Mathers

Epidemiology Faculty Publications

OBJECTIVE: To assess the effect of the FTO genotype on weight loss after dietary, physical activity, or drug based interventions in randomised controlled trials.

DESIGN: Systematic review and random effects meta-analysis of individual participant data from randomised controlled trials.

DATA SOURCES: Ovid Medline, Scopus, Embase, and Cochrane from inception to November 2015.

ELIGIBILITY CRITERIA FOR STUDY SELECTION: Randomised controlled trials in overweight or obese adults reporting reduction in body mass index, body weight, or waist circumference by FTO genotype (rs9939609 or a proxy) after dietary, physical activity, or drug based interventions. Gene by treatment interaction models were fitted to individual …

Model Averaged Double Robust Estimation, Matthew Cefalu, Francesca Dominici, Nils D. Arvold Md, Giovanni Parmigiani

Harvard University Biostatistics Working Paper Series

Existing methods in causal inference do not account for the uncertainty in the selection of confounders. We propose a new class of estimators for the average causal effect, the model averaged double robust estimators, that formally account for model uncertainty in both the propensity score and outcome model through the use of Bayesian model averaging. These estimators build on the desirable double robustness property by only requiring the true propensity score model or the true outcome model be within a specified class of models to maintain consistency. We provide asymptotic results and conduct a large scale simulation study that indicates …

Variation Of Driving Skill Among Elderly Drivers Compared To Young Drivers In Japan, Indri Hapsari Susilowati, Akira Yasukouchi

Kesmas

Penelitian ini menganalisis kemampuan mengemudi pada pengemudi lanjut usia (lansia) dibandingkan dengan usia muda di Jepang dan melihat keterampilan mengemudi yang kurang sehingga dapat memengaruhi risiko kecelakaan di jalan raya. Subjek penelitian adalah pengemudi usia muda dan lansia, terdiri dari 10 mahasiswa (20 - 24 tahun) dan 25 pengemudi lansia (14 laki-laki dan 11 perempuan) berasal dari The Silver Menpower Center, organisasi bagi lansia > 60 tahun. Pengemudi lansia dibagi menjadi dua kelompok, yaitu lansia 1 berusia 60 - 65 tahun (10 orang) dan lansia 2 berusia > 65 tahun (15 orang). Kemampuan mengemudi dievaluasi dengan simulator permainan mengemudi dalam laboratorium. Analisis …