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Joint Analysis of Current Status and Marker Data: An Extension of a Bivariate Threshold Model

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Listed:
  • Tong Xingwei

    (Beijing Normal University)

  • He Xin

    (The Ohio State University)

  • Sun Jianguo

    (University of Missouri)

  • Lee Mei-Ling T

    (University of Maryland)

Abstract

This paper considers joint analysis of current status and marker data using a threshold model based on first hitting times. A failure time is defined as the time at which a subject's latent health status process first decreases to zero. We extend the bivariate Wiener process model in Whitmore et al. (1998) to the case when only current status data are available. We develop maximum likelihood estimation procedures and provide simulation studies. We apply our methods to a motivating example involving liver tumors in mice.

Suggested Citation

  • Tong Xingwei & He Xin & Sun Jianguo & Lee Mei-Ling T, 2008. "Joint Analysis of Current Status and Marker Data: An Extension of a Bivariate Threshold Model," The International Journal of Biostatistics, De Gruyter, vol. 4(1), pages 1-12, October.
    • Handle: RePEc:bpj:ijbist:v:4:y:2008:i:1:n:21
    DOI: 10.2202/1557-4679.1122
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    References listed on IDEAS

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    1. Mel‐Ling Ting Lee & Victor DeGruttola & David Schoenfeld, 2000. "A model for markers and latent health status," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 747-762.
    2. Ian Diamond & John McDonald & Iqbal Shah, 1986. "Proportional hazards models for current status data: Application to the study of differentials in age at weaning in Pakistan," Demography, Springer;Population Association of America (PAA), vol. 23(4), pages 607-620, November.
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    Cited by:

    1. Jonathan A. Race & Michael L. Pennell, 2021. "Semi-parametric survival analysis via Dirichlet process mixtures of the First Hitting Time model," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 27(1), pages 177-194, January.

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