Semiparametric Regression Estimation for Recurrent Event Data with Errors in Covariates under Informative Censoring.

ABSTRACT: Recurrent event data arise frequently in many longitudinal follow-up studies. Hence, evaluating covariate effects on the rates of occurrence of such events is commonly of interest. Examples include repeated hospitalizations, recurrent infections of HIV, and tumor recurrences. In this article, we consider semiparametric regression methods for the occurrence rate function of recurrent events when the covariates may be measured with errors. In contrast to the existing works, in our case the conventional assumption of independent censoring is violated since the recurrent event process is interrupted by some correlated events, which is called informative drop-out. Further, some covariates may be measured with errors. To accommodate for both informative censoring and measurement error, the occur

SUBMITTER: Yu H 

PROVIDER: S-EPMC5490505 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature