New York University 3 credits Global Public Health
This course will provide students with training and practical experience needed to construct and analyze results from regression models most often applied in epidemiological research to address pressing public health questions. Specifically, this course covers six regression methods commonly utilized in epidemiological research: Linear Regression for continuous outcomes, Logistic Regressions for binary and multinomial outcomes, Ordinal Logistic Regression for ordinal outcomes, as well as Poisson and Negative Binomial models for count data. This course will cover estimation, interpretation, inference, prediction, diagnostics, and model selection for each model type with a focus on application to epidemiological research. Analyses will be taught and performed using Stata. R script will be made available as well. Prerequisites: (GPH-GU 2995 and GPH-GU 5995).
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