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Proportional exponentiated link transformed hazards (ELTH) models for discrete time survival data with application

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  • Hee-Koung Joeng

    (University of Connecticut)

  • Ming-Hui Chen

    (University of Connecticut)

  • Sangwook Kang

    (Yonsei University)

Abstract

Discrete survival data are routinely encountered in many fields of study including behavior science, economics, epidemiology, medicine, and social science. In this paper, we develop a class of proportional exponentiated link transformed hazards (ELTH) models. We carry out a detailed examination of the role of links in fitting discrete survival data and estimating regression coefficients. Several interesting results are established regarding the choice of links and baseline hazards. We also characterize the conditions for improper survival functions and the conditions for existence of the maximum likelihood estimates under the proposed ELTH models. An extensive simulation study is conducted to examine the empirical performance of the parameter estimates under the Cox proportional hazards model by treating discrete survival times as continuous survival times, and the model comparison criteria, AIC and BIC, in determining links and baseline hazards. A SEER breast cancer dataset is analyzed in details to further demonstrate the proposed methodology.

Suggested Citation

  • Hee-Koung Joeng & Ming-Hui Chen & Sangwook Kang, 2016. "Proportional exponentiated link transformed hazards (ELTH) models for discrete time survival data with application," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 22(1), pages 38-62, January.
    • Handle: RePEc:spr:lifeda:v:22:y:2016:i:1:d:10.1007_s10985-015-9326-z
    DOI: 10.1007/s10985-015-9326-z
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    References listed on IDEAS

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    1. Sungduk Kim & Ming-Hui Chen & Dipak K. Dey, 2008. "Flexible generalized t-link models for binary response data," Biometrika, Biometrika Trust, vol. 95(1), pages 93-106.
    2. L. Biggeri & M. Bini & L. Grilli, 2001. "The transition from university to work: a multilevel approach to the analysis of the time to obtain the first job," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 164(2), pages 293-305.
    3. Samuel Manda & Renate Meyer, 2005. "Age at first marriage in Malawi: a Bayesian multilevel analysis using a discrete time‐to‐event model," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(2), pages 439-455, March.
    4. Wulczyn, Fred & Chen, Lijun & Courtney, Mark, 2011. "Family reunification in a social structural context," Children and Youth Services Review, Elsevier, vol. 33(3), pages 424-430, March.
    5. Bengt Muthén & Katherine Masyn, 2005. "Discrete-Time Survival Mixture Analysis," Journal of Educational and Behavioral Statistics, , vol. 30(1), pages 27-58, March.
    6. William J. Browne & Fiona Steele & Mousa Golalizadeh & Martin J. Green, 2009. "The use of simple reparameterizations to improve the efficiency of Markov chain Monte Carlo estimation for multilevel models with applications to discrete time survival models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(3), pages 579-598, June.
    7. Abidemi K. Adeniji & Steven H. Belle & Abdus S. Wahed, 2014. "Incorporating diagnostic accuracy into the estimation of discrete survival function," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(1), pages 60-72, January.
    8. Judith D. Singer & John B. Willett, 1993. "It’s About Time: Using Discrete-Time Survival Analysis to Study Duration and the Timing of Events," Journal of Educational and Behavioral Statistics, , vol. 18(2), pages 155-195, June.
    9. Chae Woo Nam & Tong Suk Kim & Nam Jung Park & Hoe Kyung Lee, 2008. "Bankruptcy prediction using a discrete-time duration model incorporating temporal and macroeconomic dependencies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(6), pages 493-506.
    10. Leonardo Grilli, 2005. "The random‐effects proportional hazards model with grouped survival data: a comparison between the grouped continuous and continuation ratio versions," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(1), pages 83-94, January.
    11. Kani Chen, 2002. "Semiparametric analysis of transformation models with censored data," Biometrika, Biometrika Trust, vol. 89(3), pages 659-668, August.
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    Cited by:

    1. Hee-Koung Joeng & Abidemi K. Adeniji & Naitee Ting & Ming-Hui Chen, 2022. "Estimation of Discrete Survival Function through Modeling Diagnostic Accuracy for Mismeasured Outcome Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 14(1), pages 105-138, April.

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