Medical Biomathematics and Biometrics Commons^™

Imputation Of Missing Longitudinal Data: A Comparison Of Methods, Paula Diehr, Jean Mundahl Engels

Paula Diehr

BACKGROUND AND OBJECTIVES: Missing information is inevitable in longitudinal studies, and can result in biased estimates and a loss of power. One approach to this problem is to impute the missing data to yield a more complete data set. Our goal was to compare the performance of 14 methods of imputing missing data on depression, weight, cognitive functioning, and self-rated health in a longitudinal cohort of older adults. METHODS: We identified situations where a person had a known value following one or more missing values, and treated the known value as a "missing value." This "missing value" was imputed using …