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The effect of classification errors in survival data analysis

Author

Listed:
  • Adriano Paggiaro

    (Universitá di Padova)

  • Nicola Torelli

    (Universitá di Trieste)

Abstract

. Survival data analysis aims at collecting data on durations spent in a state by a sample of units, in order to analyse the process of transition to a different state. Survival analysis applied to social and economic phenomena typically relies upon data on transitions collected, for a sample of units, in one or more follow-up surveys. We explore the effect of misclassification of the transition indicator on parameter estimates in an appropriate statistical model for the duration spent in an origin state. Some empirical investigations about the bias induced when ignoring misclassification are reported, extending the model to include the possibility that the rate of misclassification can vary across units according to the value of some covariates. Finally it is shown how a Bayesian approach can lead to parameter estimates.

Suggested Citation

  • Adriano Paggiaro & Nicola Torelli, 2004. "The effect of classification errors in survival data analysis," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 13(2), pages 213-225, September.
    • Handle: RePEc:spr:stmapp:v:13:y:2004:i:2:d:10.1007_s10260-003-0079-6
    DOI: 10.1007/s10260-003-0079-6
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    Cited by:

    1. Abdurrahman Aydemir & George J. Borjas, 2011. "Attenuation Bias in Measuring the Wage Impact of Immigration," Journal of Labor Economics, University of Chicago Press, vol. 29(1), pages 69-113, January.

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