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Full-Text Articles in Medicine and Health Sciences

Correcting Instrumental Variables Estimators For Systematic Measurement Error, Stijn Vansteelandt, Manoochehr Babanezhad, Els Goetghebeur Aug 2007

Correcting Instrumental Variables Estimators For Systematic Measurement Error, Stijn Vansteelandt, Manoochehr Babanezhad, Els Goetghebeur

Harvard University Biostatistics Working Paper Series

No abstract provided.


Estimating The Prevalence Of Disease Using Relatives Of Case And Control Probands, Kristin N. Javaras, Nan M. Laird, James I. Hudson, Brian D. Ripley Aug 2007

Estimating The Prevalence Of Disease Using Relatives Of Case And Control Probands, Kristin N. Javaras, Nan M. Laird, James I. Hudson, Brian D. Ripley

COBRA Preprint Series

We introduce a method for estimating the prevalence of disease using data from a case-control family study performed to investigate the aggregation of disease in families. The families are sampled via case and control probands, and the resulting data consist of information on disease status and covariates for the probands and their relatives. We introduce estimators for overall prevalence and for covariate stratum-specific prevalence (e.g., sex-specific prevalence) that yield approximately unbiased estimates of their population counterparts. We also introduce corresponding confidence intervals that have good coverage properties even for small prevalences. The estimators and intervals address the over-representation of diseased …


Empirical Efficiency Maximization, Daniel B. Rubin, Mark J. Van Der Laan Jul 2007

Empirical Efficiency Maximization, Daniel B. Rubin, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

It has long been recognized that covariate adjustment can increase precision, even when it is not strictly necessary. The phenomenon is particularly emphasized in clinical trials, whether using continuous, categorical, or censored time-to-event outcomes. Adjustment is often straightforward when a discrete covariate partitions the sample into a handful of strata, but becomes more involved when modern studies collect copious amounts of baseline information on each subject.

The dilemma helped motivate locally efficient estimation for coarsened data structures, as surveyed in the books of van der Laan and Robins (2003) and Tsiatis (2006). Here one fits a relatively small working model …


Is Mri-Based Volume A Mediator Of The Association Of Cumulative Lead Dose With Cognitive Function?, Brian S. Caffo, Sining Chen, Walter Stewart, Karen Bolla, David Yousem, Christos Davatzikos, Brian S. Schwartz Apr 2007

Is Mri-Based Volume A Mediator Of The Association Of Cumulative Lead Dose With Cognitive Function?, Brian S. Caffo, Sining Chen, Walter Stewart, Karen Bolla, David Yousem, Christos Davatzikos, Brian S. Schwartz

Johns Hopkins University, Dept. of Biostatistics Working Papers

This work considers the pathway through which past occupational lead exposure impacts cognitive function using cross-sectional data. It is motivated by studies linking cumulative lead dose with brain volumes, volumes with cognitive function, and lead dose with cognitive function. It is hypothesized that the brain regions associated with lead mediate a portion of the association between lead dose and cognitive function. The data were derived from an ongoing study of 513 former organolead manufacturing workers. Using MRIs, a novel analysis was performed to investigate Mediation. Volumes associated with cognitive function and lead dose were derived using registered images and used …


Trends In Particulate Matter And Mortality: An Approach To The Assessment Of Unmeasured Confounding, Holly Janes, Francesca Dominici, Scott Zeger Mar 2007

Trends In Particulate Matter And Mortality: An Approach To The Assessment Of Unmeasured Confounding, Holly Janes, Francesca Dominici, Scott Zeger

Johns Hopkins University, Dept. of Biostatistics Working Papers

We propose a method for diagnosing confounding bias under a model which links a spatially and temporally varying exposure and health outcome. We decompose the association into orthogonal components, corresponding to distinct spatial and temporal scales of variation. If the model fully controls for confounding, the exposure effect estimates should be equal at the different temporal and spatial scales. We show that the overall exposure effect estimate is a weighted average of the scale-specific exposure effect estimates.

We use this approach to estimate the association between monthly averages of fine particles (PM2.5) over the preceding 12 months and monthly mortality …


Power Boosting In Genome-Wide Studies Via Methods For Multivariate Outcomes, Mary J. Emond Feb 2007

Power Boosting In Genome-Wide Studies Via Methods For Multivariate Outcomes, Mary J. Emond

UW Biostatistics Working Paper Series

Whole-genome studies are becoming a mainstay of biomedical research. Examples include expression array experiments, comparative genomic hybridization analyses and large case-control studies for detecting polymorphism/disease associations. The tactic of applying a regression model to every locus to obtain test statistics is useful in such studies. However, this approach ignores potential correlation structure in the data that could be used to gain power, particularly when a Bonferroni correction is applied to adjust for multiple testing. In this article, we propose using regression techniques for misspecified multivariate outcomes to increase statistical power over independence-based modeling at each locus. Even when the outcome …


The Causal Effect Of Recent Leisure-Time Physical Activity On All-Cause Mortality Among The Elderly, Oliver Bembom, Mark J. Van Der Laan, Ira B. Tager Feb 2007

The Causal Effect Of Recent Leisure-Time Physical Activity On All-Cause Mortality Among The Elderly, Oliver Bembom, Mark J. Van Der Laan, Ira B. Tager

U.C. Berkeley Division of Biostatistics Working Paper Series

We analyze data collected as part of a prospective cohort study of elderly people living in and around Sonoma, CA, in order to estimate, for each round of interviews, the causal effect of leisure-time physical activity (LTPA) over the past year on the risk of mortality in the following two years. For each round of interviews, this effect is estimated separately for subpopulations defined based on past exercise habits, age, and whether subjects have had cardiac events in the past. This decomposition of the original longitudinal data structure into a series of point-treatment data structures corresponds to an application of …