Semiparametric Analysis of Interval-Censored Survival Data with Median Regression Model

Jianchang Lin, Debajyoti Sinha, Stuart Lipsitz, Adriano Polpo

Research output: Chapter in Book/Conference paperConference paper

Abstract

Analysis of interval censored survival data has become increasingly popular and important in many areas including clinical trials and biomedical research. Generally, right censored survival data can be seen as a special case of interval censored data. However, due to the fundamentally special and complex nature of interval censoring, most of the commonly used survival analysis methods for right censored data, including methods based on martingale-theory (Andersen et al., Statistical models based on counting processes. Springer, New York, 1992), can not be used for analyzing interval censored survival data. Most of the popular semiparametric models for interval censored survival data focus on modeling the hazard function. In this chapter, we develop a semiparametric model dealing with the median regression function for interval censored survival data, which introduce many practical advantages in real applications. Both semiparametric maximum likelihood estimator (MLE) and the Markov chain Monte Carlo (MCMC) based semiparametric Bayesian estimator, including how to incorporate the historical information, have been proposed and presented. We illustrate the case study through a real breast cancer data example and make a comparison between different models. Key findings and recommendations are also discussed to provide further guidance on application in clinical trials.
Original languageEnglish
Title of host publicationStatistical Applications from Clinical Trials and Personalized Medicine to Finance and Business Analytics
Subtitle of host publicationSelected Papers from the 2015 ICSA/Graybill Applied Statistics Symposium, Colorado State University, Fort Collins
EditorsJianchang Lin, Bushi Wang, Xiaowen Hu, Kun Chen, Ray Liu
Place of PublicationCham, Switzerland
PublisherSpringer
Chapter13
Pages149-163
ISBN (Electronic)9783319425689
ISBN (Print)9783319425672
DOIs
Publication statusPublished - 14 Nov 2016
Externally publishedYes
Event24th ICSA Applied Statistics Symposium and 13th Graybill Conference - Fort Collins, United States
Duration: 14 Jun 201517 Jun 2015

Publication series

NameStatistical Applications from Clinical Trials and Personalized Medicine to Finance and Business Analytics
ISSN (Print)2199-0980
ISSN (Electronic)2199-0999

Conference

Conference24th ICSA Applied Statistics Symposium and 13th Graybill Conference
CountryUnited States
Period14/06/1517/06/15

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  • Cite this

    Lin, J., Sinha, D., Lipsitz, S., & Polpo, A. (2016). Semiparametric Analysis of Interval-Censored Survival Data with Median Regression Model. In J. Lin, B. Wang, X. Hu, K. Chen, & R. Liu (Eds.), Statistical Applications from Clinical Trials and Personalized Medicine to Finance and Business Analytics: Selected Papers from the 2015 ICSA/Graybill Applied Statistics Symposium, Colorado State University, Fort Collins (pp. 149-163). (Statistical Applications from Clinical Trials and Personalized Medicine to Finance and Business Analytics). Springer. https://doi.org/10.1007/978-3-319-42568-9_13