Censored count data regression with missing censoring information

We investigate estimation in the Poisson regression model when the count response is right-censored and the censoring indicators are missing at random. We propose several estimators based on the regression calibration, multiple imputation and augmented inverse probability weighting methods. Under ap...

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Bibliographic Details
Published in:Electronic journal of statistics 2021-01, Vol.15 (2), p.4343-4383
Main Authors: Bousselmi, Bilel, Dupuy, Jean-François, Karoui, Abderrazek
Format: Article
Language:English
Subjects:
Methodology
Statistics
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Summary:We investigate estimation in the Poisson regression model when the count response is right-censored and the censoring indicators are missing at random. We propose several estimators based on the regression calibration, multiple imputation and augmented inverse probability weighting methods. Under appropriate regularity conditions, we prove the consistency of our estimators and we derive their asymptotic distributions. Simulation experiments are carried out to investigate the finite sample behaviour and relative performance of the proposed estimates.
ISSN:1935-7524
1935-7524
DOI:10.1214/21-EJS1897