Biostatistics Commons^™

Teaching Of Biostatistics And Epidemiology In Medical Schools: How Do We Fare Compared With Developed Countries, Vijay Tiwari, Kuldeep Kumar, Sherin Raj

Kuldeep Kumar

Background Biostatistics is taught in almost all medical schools at the undergraduate and the postgraduate levels as a core course and is a prerequisite to epidemiology, public health and evidence-based medicine. However, it has to be taught in a different way in medical schools as compared with how it is taught to the students studying MSc (Biostatistics) or in the Statistics Department in universities. Objectives (1) To review the experience of teaching biostatistics in medical schools in India and compares the same with abroad (2) How best the curriculum can be designed as per the need of the medical students …

An Overview Of Statistical Approaches For Comparative Effectiveness Research For Assessing In-Hospital Complications Of Percutaneous Coronary Interventions By Access Site, Lauren Kunz, Sherri Rose, Donna Spiegelman, Sharon-Lise Normand

Sherri Rose

No abstract provided.

Causal Mediation In A Survival Setting With Time-Dependent Mediators, Wenjing Zheng, Mark J. Van Der Laan

Wenjing Zheng

The effect of an expsore on an outcome of interest is often mediated by intermediate variables. The goal of causal mediation analysis is to evaluate the role of these intermediate variables (mediators) in the causal effect of the exposure on the outcome. In this paper, we consider causal mediation of a baseline exposure on a survival (or time-to-event) outcome, when the mediator is time-dependent. The challenge in this setting lies in that the event process takes places jointly with the mediator process; in particular, the length of the mediator history depends on the survival time. As a result, we argue …

Targeted Maximum Likelihood Estimation Of Natural Direct Effect, Wenjing Zheng, Mark Van Der Laan

Wenjing Zheng

In many causal inference problems, one is interested in the direct causal effect of an exposure on an outcome of interest that is not mediated by certain intermediate variables. Robins and Greenland (1992) and Pearl (2000) formalized the definition of two types of direct effects (natural and controlled) under the counterfactual framework. Since then, identifiability conditions for these effects have been studied extensively. By contrast, considerably fewer efforts have been invested in the estimation problem of the natural direct effect. In this article, we propose a semiparametric efficient, multiply robust estimator for the natural direct effect of a binary treatment …

Estimating The Effect Of A Community-Based Intervention With Two Communities, Mark Van Der Laan, Maya Petersen, Wenjing Zheng

Wenjing Zheng

Due to the need to evaluate the effectiveness of community-based programs in practice, there is substantial interest in methods to estimate the causal effects of community-level treatments or exposures on individual level outcomes. The challenge one is confronted with is that different communities have different environmental factors affecting the individual outcomes, and all individuals in a community share the same environment and intervention. In practice, data are often available from only a small number of communities, making it difficult if not impossible to adjust for these environmental confounders. In this paper we consider an extreme version of this dilemma, in …

Targeted Maximum Likelihood Estimation Of Natural Direct Effects, Wenjing Zheng, Mark Van Der Laan

Wenjing Zheng

In many causal inference problems, one is interested in the direct causal effect of an exposure on an outcome of interest that is not mediated by certain intermediate variables. Robins and Greenland (1992) and Pearl (2001) formalized the definition of two types of direct effects (natural and controlled) under the counterfactual framework. The efficient scores (under a nonparametric model) for the various natural effect parameters and their general robustness conditions, as well as an estimating equation based estimator using the efficient score, are provided in Tchetgen Tchetgen and Shpitser (2011b). In this article, we apply the targeted maximum likelihood framework …

On The Statistical Accuracy Of Biomarker Assays Of Hiv Incidence, Ron Brookmeyer

Ron Brookmeyer

Objective: To evaluate the statistical accuracy of estimates of current HIV incidence rates from cross-sectional surveys, and to identify characteristics of assays that improve accuracy.

Methods: Performed mathematical and statistical analysis of the cross-sectional estimator of HIV incidence to evaluate bias and variance. Developed probability models to evaluate impact of long tails of the window period distribution on accuracy.

Results: The standard cross-sectional estimate of HIV incidence rate is estimating a time-lagged incidence where the lag time, called the shadow, depends on the mean and the coefficient of variation of window periods. Equations show how the shadow increases with the …