Inference in a survival cure model with mismeasured covariates using a simulation-extrapolation approach
- Publication Type:
- Journal Article
- Citation:
- Biometrika, 2017, 104 (1), pp. 31 - 50
- Issue Date:
- 2017-03-01
Closed Access
| Filename | Description | Size | |||
|---|---|---|---|---|---|
| Inference in a survival cure model with mismeasured covariates using a simulation-extrapolation approach.pdf | Published Version | 246.38 kB |
Copyright Clearance Process
- Recently Added
- In Progress
- Closed Access
This item is closed access and not available.
© 2017 Biometrika Trust. In many situations in survival analysis, it may happen that a fraction of individuals will never experience the event of interest: They are considered to be cured. The promotion time cure model takes this into account. We consider the case where one or more explanatory variables in the model are subject to measurement error, which should be taken into account to avoid biased estimators. A general approach is the simulation-extrapolation algorithm, a method based on simulations which allows one to estimate the effect of measurement error on the bias of the estimators and to reduce this bias. We extend this approach to the promotion time cure model. We explain how the algorithm works, and we show that the proposed estimator is approximately consistent and asymptotically normally distributed, and that it performs well in finite samples. Finally, we analyse a database in cardiology: Among the explanatory variables of interest is the ejection fraction, which is known to be measured with error.
Please use this identifier to cite or link to this item: