Weight calibration to improve efficiency for estimating pure risks from the additive hazards model with the nested case-control design.

ABSTRACT: We study the efficiency of covariate-specific estimates of pure risk (one minus the survival function) when some covariates are only available for case-control samples nested in a cohort. We focus on the semiparametric additive hazards model in which the hazard function equals a baseline hazard plus a linear combination of covariates with either time-varying or time-invariant coefficients. A published approach uses the design-based inclusion probabilities to reweight the nested case-control data. We obtain more efficient estimates of pure risks by calibrating the design weights to data available in the entire cohort, for both time-varying and time-invariant covariate coefficients. We develop explicit variance formulas for the weight-calibrated estimates based on influence functions. Simula

SUBMITTER: Shin YE 

PROVIDER: S-EPMC8172655 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature