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Analysis of linear transformation models with covariate measurement error and interval censoring.
- Source :
- Statistics in Medicine; 10/15/2019, Vol. 38 Issue 23, p4642-4655, 14p
- Publication Year :
- 2019
-
Abstract
- Among several semiparametric models, the Cox proportional hazard model is widely used to assess the association between covariates and the time-to-event when the observed time-to-event is interval-censored. Often, covariates are measured with error. To handle this covariate uncertainty in the Cox proportional hazard model with the interval-censored data, flexible approaches have been proposed. To fill a gap and broaden the scope of statistical applications to analyze time-to-event data with different models, in this paper, a general approach is proposed for fitting the semiparametric linear transformation model to interval-censored data when a covariate is measured with error. The semiparametric linear transformation model is a broad class of models that includes the proportional hazard model and the proportional odds model as special cases. The proposed method relies on a set of estimating equations to estimate the regression parameters and the infinite-dimensional parameter. For handling interval censoring and covariate measurement error, a flexible imputation technique is used. Finite sample performance of the proposed method is judged via simulation studies. Finally, the suggested method is applied to analyze a real data set from an AIDS clinical trial. [ABSTRACT FROM AUTHOR]
- Subjects :
- ERRORS-in-variables models
LINEAR statistical models
PROPORTIONAL hazards models
INTERVAL measurement
MEASUREMENT errors
COMPUTER simulation
HIV infections
ANTI-HIV agents
RESEARCH
CLINICAL trials
RESEARCH methodology
EVALUATION research
MEDICAL cooperation
COMPARATIVE studies
BLIND experiment
RESEARCH funding
PROBABILITY theory
Subjects
Details
- Language :
- English
- ISSN :
- 02776715
- Volume :
- 38
- Issue :
- 23
- Database :
- Complementary Index
- Journal :
- Statistics in Medicine
- Publication Type :
- Academic Journal
- Accession number :
- 138540047
- Full Text :
- https://doi.org/10.1002/sim.8323