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A class of semiparametric cure models with current status data.
Lifetime Data Anal 2019; 25(1):26-51LD

Abstract

Current status data occur in many biomedical studies where we only know whether the event of interest occurs before or after a particular time point. In practice, some subjects may never experience the event of interest, i.e., a certain fraction of the population is cured or is not susceptible to the event of interest. We consider a class of semiparametric transformation cure models for current status data with a survival fraction. This class includes both the proportional hazards and the proportional odds cure models as two special cases. We develop efficient likelihood-based estimation and inference procedures. We show that the maximum likelihood estimators for the regression coefficients are consistent, asymptotically normal, and asymptotically efficient. Simulation studies demonstrate that the proposed methods perform well in finite samples. For illustration, we provide an application of the models to a study on the calcification of the hydrogel intraocular lenses.

Authors+Show Affiliations

Department of Statistics, George Mason University, Fairfax, VA, USA. gdiao@gmu.edu.Department of Biostatistics, Bioinformatics and Biomathematics, Georgetown University, Washington, DC, USA.

Pub Type(s)

Journal Article
Research Support, N.I.H., Extramural

Language

eng

PubMed ID

29423775

Citation

Diao, Guoqing, and Ao Yuan. "A Class of Semiparametric Cure Models With Current Status Data." Lifetime Data Analysis, vol. 25, no. 1, 2019, pp. 26-51.
Diao G, Yuan A. A class of semiparametric cure models with current status data. Lifetime Data Anal. 2019;25(1):26-51.
Diao, G., & Yuan, A. (2019). A class of semiparametric cure models with current status data. Lifetime Data Analysis, 25(1), pp. 26-51. doi:10.1007/s10985-018-9420-0.
Diao G, Yuan A. A Class of Semiparametric Cure Models With Current Status Data. Lifetime Data Anal. 2019;25(1):26-51. PubMed PMID: 29423775.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - A class of semiparametric cure models with current status data. AU - Diao,Guoqing, AU - Yuan,Ao, Y1 - 2018/02/08/ PY - 2016/11/19/received PY - 2018/02/02/accepted PY - 2020/01/01/pmc-release PY - 2018/2/10/pubmed PY - 2018/2/10/medline PY - 2018/2/10/entrez KW - Box–Cox transformation KW - Cure fraction KW - Empirical process KW - NPMLE KW - Proportional hazards cure model KW - Proportional odds cure model KW - Semiparametric efficiency SP - 26 EP - 51 JF - Lifetime data analysis JO - Lifetime Data Anal VL - 25 IS - 1 N2 - Current status data occur in many biomedical studies where we only know whether the event of interest occurs before or after a particular time point. In practice, some subjects may never experience the event of interest, i.e., a certain fraction of the population is cured or is not susceptible to the event of interest. We consider a class of semiparametric transformation cure models for current status data with a survival fraction. This class includes both the proportional hazards and the proportional odds cure models as two special cases. We develop efficient likelihood-based estimation and inference procedures. We show that the maximum likelihood estimators for the regression coefficients are consistent, asymptotically normal, and asymptotically efficient. Simulation studies demonstrate that the proposed methods perform well in finite samples. For illustration, we provide an application of the models to a study on the calcification of the hydrogel intraocular lenses. SN - 1572-9249 UR - https://www.unboundmedicine.com/medline/citation/29423775/A_class_of_semiparametric_cure_models_with_current_status_data_ L2 - https://doi.org/10.1007/s10985-018-9420-0 DB - PRIME DP - Unbound Medicine ER -