Regression Methods

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Note: This course is not available for the current semester.

Course No: 19.674; Last Offered: No Data;

Course Description

This course is an intermediate-level statistics course focusing on regression models for both discrete and continuous outcomes. Our objective will be an understanding of statistical methods suitable for the practice of health sciences research (including epidemiology and clinical medicine). Main objectives will be the following:a solid practical understanding of multiple linear regression, a working understanding of logistic regression, a survey of additional topics in modern regression. The first goal includes F-tests, ANOVA, the construction and interpretation of indicator variables, methods of assessing model assumptions, problems of model selection for casual inference and comparison of alternative models. The second goal comprises the most common regression technique applied to binary event data (e.g. diseased vs. nondiseased, or treatment success vs. treatment failure). The final goal addresses the question of what to do when standard statistical assumptions fail, and entails an introduction to semiparametric models and robust methods.

Prerequisites & Notes

  • Prerequisites:
  • Special Notes:
  • Credits: 3;

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