Nonparametric estimation of regression parameters from censored data with a discrete covariate

Mohammad H. Rahbar and Joseph C. Gardiner

Statistics & Probability Letters, 1995, vol. 24, issue 1, 13-20

Abstract: A noniterative method of estimation is presented in a simple linear regression model where the independent variable (covariate) assumes only a finite number of values and the dependent variable (response) is randomly right censored. The censoring distribution may depend on the covariate values. The efficiency of our estimator is compared with another noniterative estimator in the literature using simulations. The asymptotic normality of the estimators of the regression parameters are established. In addition, the distribution of estimator of the asymptotic variance is obtained.

Keywords: Kaplan-Meier; estimator; Asymptotic; normality; and; right; censored; data (search for similar items in EconPapers)
Date: 1995
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Citations: View citations in EconPapers (2)

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