Backward multiple imputation estimation of the conditional lifetime expectancy function with application to censored human longevity data.

Abstract:

:The conditional lifetime expectancy function (LEF) is the expected lifetime of a subject given survival past a certain time point and the values of a set of explanatory variables. This function is attractive to researchers because it summarizes the entire residual life distribution and has an easy interpretation compared with the popularly used hazard function. In this paper, we propose a general framework of backward multiple imputation for estimating the conditional LEF and the variance of the estimator in the right-censoring setting. Simulation studies are conducted to investigate the empirical properties of the proposed estimator and the corresponding variance estimator. We demonstrate the method on the Beaver Dam Eye Study data, where the expected human lifetime is modeled with smoothing-spline ANOVA given the covariates information including sex, lifestyle factors, and disease variables.

authors

Kong J,Klein BE,Klein R,Wahba G

doi

10.1073/pnas.1512237112

subject

Has Abstract

pub_date

2015-09-29 00:00:00

pages

12069-74

issue

39

eissn

0027-8424

issn

1091-6490

pii

1512237112

journal_volume

112

pub_type

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