Description

The first part of the course is to familiarize the participants with, and teach them to apply, the general linear model as it is commonly manifested in biomedical research. Specific applications include, but not limited to, multiple regression analysis, t-tests, one-way ANOVA, factorial ANOVA (balanced and unbalanced), ANCOVA and two-group discriminant function analysis.

The second part of the course is intended to familiarize participants with statistical procedures for analyzing categorical outcome data, a type of data often collected in health-related studies. Participants will have opportunities to use SAS to implement those statistical procedures and interpret the results of SAS outputs. In addition, this course will also place emphasis to certain degree on general statistical mechanisms underlying those statistical procedures.

Prerequisite

• Completion of A Course in Commonly Used Statistical Methodologies in Clinical Research
• Completion of Foundation Course in Statistical Analysis Software (SAS) Programming

Learning Outcomes

After completing this course, the participants will be able to

• Identify appropriate linear model techniques to be used to analyze the clinical data.
• Identify appropriate statistical methodologies that are applied to analyze the categorical outcome data.
• Use appropriate procedures in the SAS system to conduct methodologies outlined above and interpret the analytical results.

Topics of Study

• Simple Linear Regression
• Multiple Linear Regression
• Analysis of Variance
• Analysis of Covariance (ANCOVA)
• Introduction to Categorical Analysis
• The 2 x 2 Contingency Table
• Sets of 2 x 2 Contingency Tables
• Sets of 2 x r and s x 2 Tables
• The s x r Tables
• Sets of s x r Tables
• Nonparametric Methods
• Logistic Regression Analysis: Dichotomous Response
• Conditional Logistic Regression Analysis (optional)