Joint regression analysis of survival and quality-adjusted survival

In this paper, a semiparametric bivariate linear regression model for survi val and quality-adjusted survival is investigated. Even with a parametric s pecification for the joint distribution, maximum likelihood is not applicab le because of induced informative censoring. We propose inference procedure s based on estimating functions. The estimators are consistent and asymptot ically normal. Hypothesis tests and confidence intervals may be constructed with easy-to-implement resampling techniques. Simultaneous regression mode ling of survival and quality-adjusted survival has not been studied formall y. Our methodology gives parameter estimates that are highly interpretable in the context of a cost-effectiveness analysis. The usefulness of the prop osal is illustrated with a breast cancer dataset.