Public Health Statistics

UC Berkeley Course , Prof. Alan Hubbard

72 students enrolled

Overview

The course covers the statistical issues surrounding estimation of effects using data on subjects followed through time. The course emphasizes a regression model approach and discusses disease incidence modeling and both continuous outcome data/linear models and longitudinal extensions to nonlinear models (e.g., logistic and Poisson). The primary focus is from the analysis side, but mathematical intuition behind the procedures will also be discussed. The statistical/mathematical material includes some survival analysis, linear models, logistic and Poisson regression, and matrix algebra for statistics. The course will conclude with an introduction to recently developed causal regression techniques (e.g., marginal structural models). Time permitting, serially correlated data on ecological units will also be discussed

Lecture 1:

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        2.8 (5 Ratings)

        Lecture Details

        Longitudinal Data Analysis

        LECTURES



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        2.8

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