APPLIED MULTIPLE REGRESSION ANALYSIS AND CAUSAL MODELING FOR THE BEHAVIORAL AND COMMUNITY HEALTH SCI
This course was designed to teach advanced graduate students how to use applied multivariate regression analysis to design, propose, and test complex research questions using a causal modeling framework. The course will include a brief review of simple linear regression, and quickly move to advanced multiple regression analysis topics including multiple predictor regression, stepwise regression approaches, the analysis of longitudinal data with regression, and examining mediators, moderators and confounding variables and their relationship to the independent and dependent variables of interest. The course will also include several other brief seminars on regression diagnostics, dichotomous predictors and outcome variables, power analysis, and an introduction to other multivariate analysis frameworks including structural equation modeling and longitudinal growth modeling. Students will be required to bring their own multivariate data set and research questions to use for class assignments, preferably data directly related to their dissertation project.