Biostatistics Commons^™

A Small Sample Correction For Estimating Attributable Risk In Case-Control Studies, Daniel B. Rubin

U.C. Berkeley Division of Biostatistics Working Paper Series

The attributable risk, often called the population attributable risk, is in many epidemiological contexts a more relevant measure of exposure-disease association than the excess risk, relative risk, or odds ratio. When estimating attributable risk with case-control data and a rare disease, we present a simple correction to the standard approach making it essentially unbiased, and also less noisy. As with analogous corrections given in Jewell (1986) for other measures of association, the adjustment often won't make a substantial difference unless the sample size is very small or point estimates are desired within fine strata, but we discuss the possible utility …

Calibrating Parametric Subject-Specific Risk Estimation, Tianxi Cai, Lu Tian, Hajime Uno, Scott D. Solomon, L. J. Wei

Harvard University Biostatistics Working Paper Series

No abstract provided.

Evaluating Subject-Level Incremental Values Of New Markers For Risk Classification Rule, Tianxi Cai, Lu Tian, Donald M. Lloyd-Jones, L. J. Wei

Harvard University Biostatistics Working Paper Series

No abstract provided.

Nonparametric Regression Using Local Kernel Estimating Equations For Correlated Failure Time Data, Zhangsheng Yu, Xihong Lin

Harvard University Biostatistics Working Paper Series

No abstract provided.

A Comparison Of Methods For Estimating The Causal Effect Of A Treatment In Randomized Clinical Trials Subject To Noncompliance, Rod Little, Qi Long, Xihong Lin

Harvard University Biostatistics Working Paper Series

No abstract provided.

Semiparametric Maximum Likelihood Estimation In Normal Transformation Models For Bivariate Survival Data, Yi Li, Ross L. Prentice, Xihong Lin

Harvard University Biostatistics Working Paper Series

No abstract provided.

Knowledge, Perceptions, Beliefs And Behaviors Related To The Prevention Of Hypertension Among Black Seventh-Day Adventists Living In London, Maxine A. Newell

Loma Linda University Electronic Theses, Dissertations & Projects

This study was a cross-sectional survey of the hypertension (HTN) knowledge and risk behaviors of Black Seventh-day Adventists (SDA) in London. Recruitment took take place in 17 predominantly Black SDA churches in London. A questionnaire assessed knowledge and lay-beliefs about HTN and perceptions towards HTN using the health belief model (HBM) constructs of susceptibility, severity, benefits, barriers, and self-efficacy. Cohen’s Perceived Stress Scale was incorporated into the questionnaire. Blood pressure, height, weight and waist circumference were and current lifestyles practices were evaluated for the presence of HTN risk factors.

Of the 312 volunteers, ages 25 to 79, 55% were born …

Targeted Methods For Biomarker Discovery, The Search For A Standard, Catherine Tuglus, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

More often than not biomarker studies analyze large quantities of variables with complicated and generally unknown correlation structure. There are numerous statistical methods which attempt to unravel these variables and determine the underlying mechanism through identification of causally related biomarkers. Results from these methods are generally difficult to interpret and nearly impossible to compare across studies. The FDA has currently called for a standardization of methods and protocol for biomarker detection. In response, we propose targeted variable importance (tVIM) as a standardized method for biomarker discovery. Through the use of targeted Maximum Likelihood, tVIM provides double robust estimates of variable …

On Matched Pairs Sign Test Using Bivariate Ranked Set Sampling: An Application To Environmental Issues, Hani M. Samawi, Mohammad F. Al-Saleh, Obaid Al-Saidy

Biostatistics: Faculty Publications

The matched pairs sign test using bivariate ranked set sampling (BVRSS) is introduced and investigated. We show that this test is asymptotically more efficient than its counterpart sign test based on a bivariate simple random sample (BVSRS). The asymptotic null distribution and the efficiency of the test are derived. The Pitman asymptotic relative efficiency is used to compare the asymptotic performance of the matched pairs sign test using BVRSS versus using BVSRS. For small sample sizes, the bootstrap method is used to estimate P-values. Numerical comparisons are used to gain insight about the efficiency of the BVRSS sign test compared …

Inference On Overlapping Coefficients In Two Exponential Populations, Mohammad F. Al-Saleh, Hani M. Samawi

Biostatistics: Faculty Publications

Three measures of overlap, namely Matusita’s measureρ , Morisita’s measure λ and Weitzman’s measure Δ are investigated in this article for two exponential populations with different means. It is well that the estimators of those measures of overlap are biased. The bias is of these estimators depends on the unknown overlap parameters. There are no closed-form, exact formulas, for those estimators variances or their exact sampling distributions. Monte Carlo evaluations are used to study the bias and precision of the proposed overlap measures. Bootstrap method and Taylor series approximation are used to construct confidence intervals for the overlap measures.

Incidence, Patterns And Severity Of Reported Unintentional Injuries In Pakistan For Persons Five Years And Older: Results Of The National Health Survey Of Pakistan 1990–94, Zafar Fatmi, Wilbur C. Hadden, Junaid A. Razzak, Huma Qureshi, Adnan A. Hyder, Gregory Pappas

Community Health Sciences

Background

National level estimates of injuries are not readily available for developing countries. This study estimated the annual incidence, patterns and severity of unintentional injuries among persons over five years of age in Pakistan.

Methods

National Health Survey of Pakistan (NHSP 1990–94) is a nationally representative survey of the household. Through a two-stage stratified design, 18, 315 persons over 5 years of age were interviewed to estimate the overall annual incidence, patterns and severity of unintentional injuries for males and females in urban and rural areas over the preceding one year. Weighted estimates were computed adjusting for complex survey design …

Adjusting For Covariates In Studies Of Diagnostic, Screening, Or Prognostic Markers: An Old Concept In A New Setting, Holly Janes, Margaret Pepe

UW Biostatistics Working Paper Series

The concept of covariate adjustment is well established in therapeutic and etiologic studies. However, it has received little attention in the growing area of medical research devoted to the development of markers for disease diagnosis, screening, or prognosis, where classification accuracy, rather than association, is of primary interest. In this paper, we demonstrate the need for covariate adjustment in studies of classification accuracy, discuss methods for adjusting for covariates, and distinguish covariate adjustment from several other related but fundamentally different uses for covariates. We draw analogies and contrasts throughout with studies of association.

The Association Between Lifestyle Factors And Inflammatory Markers, Kerry Ann Stonebrook

Loma Linda University Electronic Theses, Dissertations & Projects

Background: Cardiovascular disease (CVD) is the leading cause of death for both men and women in the United States. While smoking, high blood pressure, and elevated cholesterol levels are established risk factors for CVD, inflammation is being evaluated as a potential independent risk factor. A key cytokine regulator of the inflammatory response, interleukin-1 (IL-1), has emerged as playing a particularly important role at the genetic level in determining the degree to which the inflammation pathway is turned on. How an individual’s genetic make-up affects inflammation, CVD risk, and response to lifestyle intervention is an area of research that is in …

A Likelihood Based Method For Real Time Estimation Of The Serial Interval And Reproductive Number Of An Epidemic, Laura Forsberg White, Marcello Pagano

Harvard University Biostatistics Working Paper Series

No abstract provided.

Semiparametric Regression Of Multi-Dimensional Genetic Pathway Data: Least Squares Kernel Machines And Linear Mixed Models, Dawei Liu, Xihong Lin, Debashis Ghosh

Harvard University Biostatistics Working Paper Series

No abstract provided.

Causal Comparisons In Randomized Trials Of Two Active Treatments: The Effect Of Supervised Exercise To Promote Smoking Cessation, Jason Roy, Joseph W. Hogan

COBRA Preprint Series

In behavioral medicine trials, such as smoking cessation trials, two or more active treatments are often compared. Noncompliance by some subjects with their assigned treatment poses a challenge to the data analyst. Causal parameters of interest might include those defined by subpopulations based on their potential compliance status under each assignment, using the principal stratification framework (e.g., causal effect of new therapy compared to standard therapy among subjects that would comply with either intervention). Even if subjects in one arm do not have access to the other treatment(s), the causal effect of each treatment typically can only be identified from …

Semiparametric Latent Variable Regression Models For Spatio-Temporal Modeling Of Mobile Source Particles In The Greater Boston Area, Alexandros Gryparis, Brent A. Coull, Joel Schwartz, Helen H. Suh

Harvard University Biostatistics Working Paper Series

Traffic particle concentrations show considerable spatial variability within a metropolitan area. We consider latent variable semiparametric regression models for modeling the spatial and temporal variability of black carbon and elemental carbon concentrations in the greater Boston area. Measurements of these pollutants, which are markers of traffic particles, were obtained from several individual exposure studies conducted at specific household locations as well as 15 ambient monitoring sites in the city. The models allow for both flexible, nonlinear effects of covariates and for unexplained spatial and temporal variability in exposure. In addition, the different individual exposure studies recorded different surrogates of traffic …

Reliability, Effect Size, And Responsiveness And Intraclass Correlation Of Health Status Measures Used In Randomized And Cluster-Randomized Trials, Paula Diehr, Lu Chen, Donald L. Patrick, Ziding Feng, Yutaka Yasui

UW Biostatistics Working Paper Series

Background: New health status instruments are described by psychometric properties, such as Reliability, Effect Size, and Responsiveness. For cluster-randomized trials, another important statistic is the Intraclass Correlation for the instrument within clusters. Studies using better instruments can be performed with smaller sample sizes, but better instruments may be more expensive in terms of dollars, lost opportunities, or poorer data quality due to the response burden of longer instruments. Investigators often need to estimate the psychometric properties of a new instrument, or of an established instrument in a new setting. Optimal sample sizes for estimating these properties have not been studied …

Gpnn: Power Studies And Applications Of A Neural Network Method For Detecting Gene-Gene Interactions In Studies Of Human Disease, Alison A. Motsinger, Stephen L. Lee, George Mellick, Marylyn D. Ritchie

Dartmouth Scholarship

The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinson's disease.

Population Intervention Models In Causal Inference, Alan E. Hubbard, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Marginal structural models (MSM) provide a powerful tool for estimating the causal effect of a] treatment variable or risk variable on the distribution of a disease in a population. These models, as originally introduced by Robins (e.g., Robins (2000a), Robins (2000b), van der Laan and Robins (2002)), model the marginal distributions of treatment-specific counterfactual outcomes, possibly conditional on a subset of the baseline covariates, and its dependence on treatment. Marginal structural models are particularly useful in the context of longitudinal data structures, in which each subject's treatment and covariate history are measured over time, and an outcome is recorded at …

Gauss-Seidel Estimation Of Generalized Linear Mixed Models With Application To Poisson Modeling Of Spatially Varying Disease Rates, Subharup Guha, Louise Ryan

Harvard University Biostatistics Working Paper Series

Generalized linear mixed models (GLMMs) provide an elegant framework for the analysis of correlated data. Due to the non-closed form of the likelihood, GLMMs are often fit by computational procedures like penalized quasi-likelihood (PQL). Special cases of these models are generalized linear models (GLMs), which are often fit using algorithms like iterative weighted least squares (IWLS). High computational costs and memory space constraints often make it difficult to apply these iterative procedures to data sets with very large number of cases.

This paper proposes a computationally efficient strategy based on the Gauss-Seidel algorithm that iteratively fits sub-models of the GLMM …

Is The Number Of Sick Persons In A Cohort Constant Over Time?, Paula Diehr, Ann Derleth, Anne Newman, Liming Cai

UW Biostatistics Working Paper Series

Objectives: To estimate the number of persons in a cohort who are sick, over time.

Methods: We calculated the number of sick persons in the Cardiovascular Health Study (CHS), a cohort study of older adults followed up to 14 years, using eight definitions of “healthy” and “sick”. We projected the number in each health state over time for a birth cohort.

Results: The number of sick persons in CHS was approximately constant for 14 years, for all definitions of “sick”. The estimated number of sick persons in the birth cohort was approximately constant from ages 55-75, after which it decreased. …

Direct Effect Models, Mark J. Van Der Laan, Maya L. Petersen

U.C. Berkeley Division of Biostatistics Working Paper Series

The causal effect of a treatment on an outcome is generally mediated by several intermediate variables. Estimation of the component of the causal effect of a treatment that is mediated by a given intermediate variable (the indirect effect of the treatment), and the component that is not mediated by that intermediate variable (the direct effect of the treatment) is often relevant to mechanistic understanding and to the design of clinical and public health interventions. Under the assumption of no-unmeasured confounders for treatment and the intermediate variable, Robins & Greenland (1992) define an individual direct effect as the counterfactual effect of …

Causal Inference In Longitudinal Studies With History-Restricted Marginal Structural Models, Romain Neugebauer, Mark J. Van Der Laan, Ira B. Tager

U.C. Berkeley Division of Biostatistics Working Paper Series

Causal Inference based on Marginal Structural Models (MSMs) is particularly attractive to subject-matter investigators because MSM parameters provide explicit representations of causal effects. We introduce History-Restricted Marginal Structural Models (HRMSMs) for longitudinal data for the purpose of defining causal parameters which may often be better suited for Public Health research. This new class of MSMs allows investigators to analyze the causal effect of a treatment on an outcome based on a fixed, shorter and user-specified history of exposure compared to MSMs. By default, the latter represents the treatment causal effect of interest based on a treatment history defined by the …

Body Weight And Mortality Among Adults Who Never Smoked, Pramil N. Singh

Loma Linda University Electronic Theses, Dissertations & Projects

Most prospective studies identify an increased mortality risk for adults of high body mass index (> 27 kg/m²) that is commonly attributed to the effects of excess body fat, and also identify an increased mortality risk for adults of low body mass index (< 21 kg/m²), an association that, if causal among healthy adults, is without adequate pathophysiologic support.

In this dissertation, I have conducted three studies that continue the investigation of adiposity in relation to mortality among never-smoking adults of the California Seventh-day Adventist population. Among never-smoking adults of the Adventist Mortality Study (1960-1985), the relation between …

Student Evaluations Of Teaching Effectiveness: The Interpretation Of Observational Data And The Principle Of Faute De Mieux, B. Burt Gerstman

Faculty Publications

Student opinion surveys are important but widely misunderstood tools for evaluating teaching effectiveness. In this brief review, an analogy is drawn between the use and interpretation of observational data for public health and biomedical research and the use of student opinion data in evaluating teach ing effectiveness. Sources of systematic error in the form of selection bias, information bias, and confounding are defined and illustrated. Original data concerning intermittent "quid pro quo" confounding (i.e., the effect of expected grades on student evaluations of teaching) are presented. Finally, the principle of faute de mieux ("lack of anything better") and the interpretation …

Chronic Respiratory Disease Symptom Effects Of Long-Term Cumulative Exposure To Passive Tobacco Smoke And To Ambient Levels Of Tsp, Oxidants, So2, And No2 In Southern California, Gary L. Euler

Loma Linda University Electronic Theses, Dissertations & Projects

To assess risk of chronic respiratory disease symptoms due to long-term exposure to the ambient levels of TSP, oxidants, SO2 and NO2 in photochemical air pollution, symptoms were ascertained using NHLBI questions on 8,572 Southern California Seventh-day Adventist, nonsmokers, 25 years and older, who lived eleven years or longer in their 1977 residential area. Tobacco smoke, active and passive, and occupational exposures were measured by questionnaires, as well as lifestyle characteristics relative to pollution exposure such as time spent outside and residence history. A pulmonary function feasibility study was done on a subsample of 86 women 50-64 years of age …

Sources Of Nosocomial Infections In Immunocompromised Patients (Letter), B. Burt Gerstman

Faculty Publications

No abstract provided.

Exploration Of The Incidence Of Identified Emotional Disorders In Selected General Hospitals Of Nebraska, Arlene M. Van Horn

Loma Linda University Electronic Theses, Dissertations & Projects

A descriptive-comparative survey using content analysis of medical records has been done to determine the frequency with which emotional disorders are identified by medical personnel in the population hospitalized in small general hospitals in north-central Nebraska.

A systematic, random sample of medical records was taken from two hospitals arbitrarily included in the study on the basis of bed capacity and distance from mental health facilities.

Each medical record that was reviewed has been placed in a category based on whether an emotional disorder was identified in it by the medical personnel, or whether it contained recorded behaviors that could indicate …