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Maximum likelihood estimation for semiparametric transformation models with interval-censored data.
Biometrika 2016; 103(2):253-271B

Abstract

Interval censoring arises frequently in clinical, epidemiological, financial and sociological studies, where the event or failure of interest is known only to occur within an interval induced by periodic monitoring. We formulate the effects of potentially time-dependent covariates on the interval-censored failure time through a broad class of semiparametric transformation models that encompasses proportional hazards and proportional odds models. We consider nonparametric maximum likelihood estimation for this class of models with an arbitrary number of monitoring times for each subject. We devise an EM-type algorithm that converges stably, even in the presence of time-dependent covariates, and show that the estimators for the regression parameters are consistent, asymptotically normal, and asymptotically efficient with an easily estimated covariance matrix. Finally, we demonstrate the performance of our procedures through simulation studies and application to an HIV/AIDS study conducted in Thailand.

Authors+Show Affiliations

Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina 27599, U.S.A. , dzeng@bios.unc.edu , lmao@live.unc.edu.Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina 27599, U.S.A. , dzeng@bios.unc.edu , lmao@live.unc.edu.Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina 27599, U.S.A. , dzeng@bios.unc.edu , lmao@live.unc.edu.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

27279656

Citation

Zeng, Donglin, et al. "Maximum Likelihood Estimation for Semiparametric Transformation Models With Interval-censored Data." Biometrika, vol. 103, no. 2, 2016, pp. 253-271.
Zeng D, Mao L, Lin DY. Maximum likelihood estimation for semiparametric transformation models with interval-censored data. Biometrika. 2016;103(2):253-271.
Zeng, D., Mao, L., & Lin, D. Y. (2016). Maximum likelihood estimation for semiparametric transformation models with interval-censored data. Biometrika, 103(2), pp. 253-271.
Zeng D, Mao L, Lin DY. Maximum Likelihood Estimation for Semiparametric Transformation Models With Interval-censored Data. Biometrika. 2016;103(2):253-271. PubMed PMID: 27279656.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Maximum likelihood estimation for semiparametric transformation models with interval-censored data. AU - Zeng,Donglin, AU - Mao,Lu, AU - Lin,D Y, Y1 - 2016/05/24/ PY - 2016/6/10/entrez PY - 2016/6/10/pubmed PY - 2016/6/10/medline KW - Current-status data KW - EM algorithm KW - Interval censoring KW - Linear transformation model KW - Nonparametric likelihood KW - Proportional hazards KW - Proportional odds KW - Semiparametric efficiency KW - Time-dependent covariate SP - 253 EP - 271 JF - Biometrika JO - Biometrika VL - 103 IS - 2 N2 - Interval censoring arises frequently in clinical, epidemiological, financial and sociological studies, where the event or failure of interest is known only to occur within an interval induced by periodic monitoring. We formulate the effects of potentially time-dependent covariates on the interval-censored failure time through a broad class of semiparametric transformation models that encompasses proportional hazards and proportional odds models. We consider nonparametric maximum likelihood estimation for this class of models with an arbitrary number of monitoring times for each subject. We devise an EM-type algorithm that converges stably, even in the presence of time-dependent covariates, and show that the estimators for the regression parameters are consistent, asymptotically normal, and asymptotically efficient with an easily estimated covariance matrix. Finally, we demonstrate the performance of our procedures through simulation studies and application to an HIV/AIDS study conducted in Thailand. SN - 0006-3444 UR - https://www.unboundmedicine.com/medline/citation/27279656/Maximum_likelihood_estimation_for_semiparametric_transformation_models_with_interval_censored_data_ L2 - https://academic.oup.com/biomet/article-lookup/doi/10.1093/biomet/asw013 DB - PRIME DP - Unbound Medicine ER -