This course is designed to provide the student with the basics of methods for analyzing data with missing data and misspecified data. This course will cover the following topics: missing data in experiments, complete case analysis, weighted complete case analysis, available case analysis, single imputation methods such as mean, regression, last value varied forward, hot deck imputation, cold deck imputation, Bayes Imputation, Multiple imputation, and non-ignorable missing data models. Prerequisite: A minimum grade of “B” in BIOS 9131. Co-requisite: BIOS 9231.
Vogel, Robert, "BIOS 9433 - Analysis with Missing & Miss-specified Data" (2015). Jiann-Ping Hsu College of Public Health Syllabi. 30.