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Inference for Shared-Frailty Survival Models with Left-Truncated Data

  • van den Berg, Gerard J.

    ()

    (University of Mannheim)

  • Drepper, Bettina

    ()

    (Tilburg University)

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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Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 6031.

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Length: 25 pages
Date of creation: Oct 2011
Date of revision:
Publication status: forthcoming in: Econometric Reviews
Handle: RePEc:iza:izadps:dp6031
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  1. Ridder, Geert & Tunali, Insan, 1999. "Stratified partial likelihood estimation," Journal of Econometrics, Elsevier, vol. 92(2), pages 193-232, October.
  2. repec:dgr:uvatin:20060059 is not listed on IDEAS
  3. Mario Cleves & William W. Gould & Roberto G. Gutierrez & Yulia Marchenko, 2010. "An Introduction to Survival Analysis Using Stata," Stata Press books, StataCorp LP, edition 3, number saus3, December.
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