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Inference for cumulative incidence functions with informatively coarsened discrete event‐time data
Author(s) -
Shardell Michelle,
Scharfstein Daniel O.,
Vlahov David,
Galai Noya
Publication year - 2008
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.3397
Subject(s) - censoring (clinical trials) , frequentist inference , bayesian probability , econometrics , inference , statistics , cumulative incidence , null hypothesis , computer science , bayesian inference , mathematics , artificial intelligence , cohort
We consider the problem of comparing cumulative incidence functions of non‐mortality events in the presence of informative coarsening and the competing risk of death. We extend frequentist‐based hypothesis tests previously developed for non‐informative coarsening and propose a novel Bayesian method based on comparing a posterior parameter transformation with its expected distribution under the null hypothesis of equal cumulative incidence functions. Both methods use estimates derived by extending previously published estimation procedures to accommodate censoring by death. The data structure and analysis goal are exemplified by the AIDS Link to the Intravenous Experience (ALIVE) study, where researchers are interested in comparing incidence of human immunodeficiency virus seroconversion by risk behavior categories. Coarsening in the forms of interval and right censoring and censoring by death in ALIVE is thought to be informative; thus, we perform a sensitivity analysis by incorporating elicited expert information about the relationship between seroconversion and censoring into the model. Copyright © 2008 John Wiley & Sons, Ltd.