Arbeitspapier

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

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.

Language
Englisch

Bibliographic citation
Series: IZA Discussion Papers ; No. 6031

Classification
Wirtschaft
Duration Analysis; Optimal Timing Strategies
Multiple or Simultaneous Equation Models: Truncated and Censored Models; Switching Regression Models
Subject
stata
duration analysis
left-truncation
likelihood function
dynamic selection
hazard rate
unobserved heterogeneity
twin data
Statistische Bestandsanalyse
Inferenzstatistik
Maximum-Likelihood-Methode

Event
Geistige Schöpfung
(who)
van den Berg, Gerard J.
Drepper, Bettina
Event
Veröffentlichung
(who)
Institute for the Study of Labor (IZA)
(where)
Bonn
(when)
2011

Handle
URN
urn:nbn:de:101:1-201110263752
Last update
10.03.2025, 11:42 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • van den Berg, Gerard J.
  • Drepper, Bettina
  • Institute for the Study of Labor (IZA)

Time of origin

  • 2011

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