Joint Modeling of Survival Data and Longitudinal Measurements Under Nested Case-Control Sampling

Abstract

Nested case-control (NCC) design is a popular sampling method in large epidemiological studies for its cost effectiveness. In this talk, we demonstrate a joint modeling approach for the survival times and the longitudinal measurements of the risk factor under the nested case-control sampling. This approach allows repeated measures of the potential risk factor, where the standard conditional logistic regression approach is not applicable. We employ the EM-algorithm to carry out the maximum likelihood estimation and use an EM-aided profile likelihood approach to estimate the standard errors. Simulations are also conducted to show the validity and efficiency of our method.