Course details

HS 852 - Scientific Methods for Health Sciences: Linear Modeling

Prerequisite: HS 851 or permission of instructor

Credits: 4

This course introduces commonly used linear, generalized linear, and linear mixed models to graduate students who need to understand research reports/scientific papers, analyze empirical data, or interpret their results. The topics covered by this course include SAS tutorial, SAS Graphics, analysis of variance (ANOVA), simple linear regression, multiple linear regression, logistic regression, multi-nominal logistic regression, survival models, analysis of covariance (ANCOVA), nonparametric methods, linear mixed effects models, generalized estimating equations (GEE), and other statistical methods. The emphasis of the curriculum is on the practical aspect of the statistical methods with the mathematical models and computation introduced at a minimal technical level. Students will learn to be users of these statistical methods through real data examples, hands on experiences, and critique of scientific papers published in their subject fields. HS852 is a 4 credits course (3 credits for lectures + 1 credit for lab/discussion).

View all courses