Asymptotic normality of corrected estimator in Cox proportional hazards model with measurement error
Volume 1, Issue 1 (2014), pp. 13–32
Pub. online: 27 June 2014
Type: Research Article
Open Access
Received
16 March 2014
16 March 2014
Revised
29 May 2014
29 May 2014
Accepted
5 June 2014
5 June 2014
Published
27 June 2014
27 June 2014
Abstract
Cox proportional hazards model is considered. In Kukush et al. (2011), Journal of Statistical Research, Vol. 45, No. 2, 77–94 simultaneous estimators $\lambda _{n}(\cdot )$ and $\beta _{n}$ of baseline hazard rate $\lambda (\cdot )$ and regression parameter β are studied. The estimators maximize the objective function that corrects the log-likelihood function for measurement errors and censoring. Parameter sets for $\lambda (\cdot )$ and β are convex compact sets in $C[0,\tau ]$ and ${\mathbb{R}}^{k}$, respectively. In present paper the asymptotic normality for $\beta _{n}$ and linear functionals of $\lambda _{n}(\cdot )$ is shown. The results are valid as well for a model without measurement errors. A way to compute the estimators is discussed based on the fact that $\lambda _{n}(\cdot )$ is a linear spline.
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