Nonparametric Maximum Likelihood Estimators of Time-Dependent Accuracy Measures for Survival Outcome Under Two-Stage Sampling Designs.

ABSTRACT: Large prospective cohort studies of rare chronic diseases require thoughtful planning of study designs, especially for biomarker studies when measurements are based on stored tissue or blood specimens. Two-phase designs, including nested case-control (Thomas, 1977) and case-cohort (Prentice, 1986) sampling designs, provide cost-effective strategies for conducting biomarker evaluation studies. Existing literature for biomarker assessment under two-phase designs largely focuses on simple inverse probability weighting (IPW) estimators (Cai and Zheng, 2011; Liu et al., 2012). Drawing on recent theoretical development on the maximum likelihood estimators for relative risk parameters in two-phase studies (Scheike and Martinussen, 2004; Zeng et al., 2006), we propose nonparametric maximum likelih

SUBMITTER: Liu D 

PROVIDER: S-EPMC6291304 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature