Analyzing the robustness of semi-parametric duration models for the study of repeated events

Janet M. Box-Steffensmeier, Suzanna Linn, Corwin D. Smidt

Research output: Contribution to journalArticle

6 Scopus citations

Abstract

Estimators within the Cox family are often used to estimate models for repeated events. Yet, there is much we still do not know about the performance of these estimators. In particular, we do not know how they perform given time dependence, different censoring rates, and a varying number of events and sample sizes. We use Monte Carlo simulations to demonstrate the performance of a variety of popular semiparametric estimators as these data aspects change and under conditions of event dependence and heterogeneity, both, or neither. We conclude that the conditional frailty model outperforms other standard estimators under a wide array of data-generating processes, and data limitations rarely alter its performance.

Original languageEnglish (US)
Article numbermpt015
Pages (from-to)183-204
Number of pages22
JournalPolitical Analysis
Volume22
Issue number2
DOIs
StatePublished - Apr 2014

All Science Journal Classification (ASJC) codes

  • Sociology and Political Science
  • Political Science and International Relations

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