Partly conditional estimation of the effect of a time-dependent factor in the presence of dependent censoring.

ABSTRACT: We propose semiparametric methods for estimating the effect of a time-dependent covariate on treatment-free survival. The data structure of interest consists of a longitudinal sequence of measurements and a potentially censored survival time. The factor of interest is time-dependent. Treatment-free survival is of interest and is dependently censored by the receipt of treatment. Patients may be removed from consideration for treatment, temporarily or permanently. The proposed methods combine landmark analysis and partly conditional hazard regression. A set of calendar time cross-sections is specified, and survival time (from cross-section date) is modeled through weighted Cox regression. The assumed model for death is marginal in the sense that time-varying covariates are taken as fixed at

SUBMITTER: Gong Q 

PROVIDER: S-EPMC3692598 | biostudies-literature | 2013 Jun

REPOSITORIES: biostudies-literature