Linear Regression with Censored Data
Copyright policy )Linear Regression with Censored Data
SUMMARY We give a method of estimating parameters in the linear regression model which allows the dependent variable to be censored and the residual distribution to be unspecified. The method differs from that of Miller (1976) in that the normal equations rather than the sum of squares of residuals are modified and this appears to overcome the inconsistency problems in Miller's approach. Large sample properties of the estimator of slope are derived heuristically and substantiated by simulations. Some of the heart transplant data reported and analysed by Miller are reanalysed using the present method.
- University of Western Australia Australia
- Western University Canada
- Walter and Eliza Hall Institute of Medical Research Australia
least squares, normal equations, Linear regression; mixed models, self-consistency, censored data, Monte Carlo methods, Asymptotic properties of parametric estimators
least squares, normal equations, Linear regression; mixed models, self-consistency, censored data, Monte Carlo methods, Asymptotic properties of parametric estimators
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