Augmented pseudo-likelihood estimation for two-phase studies.

ABSTRACT: In many public health and medical research settings, information on key covariates may not be readily available or too expensive to gather for all individuals in the study. In such settings, the two-phase design provides a way forward by first stratifying an initial (large) phase I sample on the basis of covariates readily available (including, possibly, the outcome), and sub-sampling participants at phase II to collect the expensive measure(s). When the outcome of interest is binary, several methods have been proposed for estimation and inference for the parameters of a logistic regression model, including weighted likelihood, pseudo-likelihood and maximum likelihood. Although these methods yield consistent estimation and valid inference, they do so solely on the basis of the phase I stra

SUBMITTER: Rivera-Rodriguez C 

PROVIDER: S-EPMC7659466 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature