Medicine and Health Sciences 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 …

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 …

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 …