ABSTRACT
In this chapter, we focus on the case when the surrogate is a continuous, normally-distributed endpoint measured repeatedly over time and the true endpoint is a failure-time endpoint. Technically, the evaluation of the candidate surrogate requires a joint model for longitudinal measurements and failure-time data. Methodology for such joint modeling has been considerably developed in recent years (see, e.g., the recent monograph by Rizopoulos, 2012). The proposed joint models couple the failure-time model, which is usually of primary interest, with a suitable model for the longitudinal measurements of a covariate. We follow the meta-analytic approach developed by Renard et al. (2003), which uses the joint model proposed by Henderson, Diggle, and Dobson (2000).
