Article first published online: 19 JUN 2012
Copyright © 2012 John Wiley & Sons, Ltd.
Statistics in Medicine
Volume 31, Issue 21, pages 2374–2385, 20 September 2012
How to Cite
Nysen, R., Aerts, M. and Faes, C. (2012), Testing goodness of fit of parametric models for censored data. Statist. Med., 31: 2374–2385. doi: 10.1002/sim.5368
- Issue published online: 30 AUG 2012
- Article first published online: 19 JUN 2012
- Manuscript Accepted: 20 FEB 2012
- Manuscript Received: 20 OCT 2011
- bootstrap test;
- censored data;
- goodness-of-fit test;
- order selection test;
- semi-nonparametric estimator
We propose and study a goodness-of-fit test for left-censored, right-censored, and interval-censored data assuming random censorship. Main motivation comes from dietary exposure assessment in chemical risk assessment, where the determination of an appropriate distribution for concentration data is of major importance. We base the new goodness-of-fit test procedure proposed in this paper on the order selection test. As part of the testing procedure, we extend the null model to a series of nested alternative models for censored data. Then, we use a modified AIC model selection to select the best model to describe the data. If a model with one or more extra parameters is selected, then we reject the null hypothesis. As an alternative to the use of the asymptotic null distribution of the test statistic, we define a bootstrap-based procedure. We illustrate the applicability of the test procedure on data of cadmium concentrations and on data from the Signal Tandmobiel study and demonstrate its performance characteristics through simulation studies. Copyright © 2012 John Wiley & Sons, Ltd.