Inference for shared-frailty survival models with left-truncated data


Berg, Gerard J. van den ; Drepper, Bettina


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URL: https://ub-madoc.bib.uni-mannheim.de/30729
URN: urn:nbn:de:bsz:180-madoc-307290
Document Type: Working paper
Year of publication: 2012
The title of a journal, publication series: Working Paper Series
Volume: 12-05
Place of publication: Mannheim
Publication language: English
Institution: School of Law and Economics > Alexander v. Humboldt Professor in Econometrics and Empirical Economics (van den Berg 2009-2016)
MADOC publication series: Department of Economics > Working Paper Series
Subject: 330 Economics
Classification: JEL: C41 , C34,
Keywords (English): Stata , duration analysis , hazard rate , unobserved heterogeneity , left-truncation , likelihood function , dynamic selection , twin data
Abstract: Shared-frailty survival models specify that systematic unobserved determinants of duration outcomes are identical within groups of individuals. We consider random-effects likelihood-based statistical inference if the duration data are subject to left-truncation. Such inference with left-truncated data can be performed in the Stata software package. We show that with left-truncated data, the commands ignore the weeding-out process before the left-truncation points, affecting the distribution of unobserved determinants among group members in the data, that is, among the group members who survive until their truncation points. We critically examine studies in the statistical literature on this issue as well as published empirical studies that use the commands. Simulations illustrate the size of the (asymptotic) bias and its dependence on the degree of truncation. We provide a Stata command file that maximizes the likelihood function that properly takes account of the interplay between truncation and dynamic selection.

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