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Estimating the cumulative mean function for history process with time‐dependent covariates and censoring mechanism
Author(s) -
Deng Dianliang
Publication year - 2016
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.6998
Subject(s) - censoring (clinical trials) , covariate , estimator , inverse probability weighting , computer science , inverse probability , weighting , statistics , consistency (knowledge bases) , cumulative distribution function , econometrics , mathematics , probability density function , artificial intelligence , medicine , posterior probability , bayesian probability , radiology
In this paper, an approach to estimating the cumulative mean function for history process with time dependent covariates and right censored time‐to‐event variable is developed using the combined technique of joint modeling and inverse probability weighting method. The consistency of proposed estimator is derived. Theoretical analysis and simulation studies indicate that the estimator given in this paper is quite recommendable to practical applications because of its simplicity and accuracy. A real data set from a multicenter automatic defibrillator implantation trial is used to illustrate the proposed methodology. Copyright © 2016 John Wiley & Sons, Ltd.