This paper deals with the question how to model health effects after the cessation of a randomised controlled trial (RCT). Using clinical trial data on severe congestive heart failure patients we illustrate how survival beyond the cessation of a RCT can be predicted based on parametric survival...

This paper shows that there exists a close relation between the net benefit and Fieller's methods for calculation of confidence intervals and performing hypothesis testing in cost-effectiveness analysis. The prices at which the net benefit confidence interval limits are equal to zero are...

This paper discusses the definition, computation and interpretation of cost-effectiveness acceptability curves. A formal definition of the cost-effectiveness acceptability curve based on the net benefit approach is provided. The curve can be computed using parametric or non-parametric techniques...

How to obtain confidence intervals for cost-effectiveness ratios is complicated by the statistical problems to obtain a confidence interval for a ratio of random variables. Different approaches have been suggested in the literature, but no consensus has been reached. In this note we propose an...

This paper presents a Monte Carlo simulation study of the bootstrap algorithm proposed by Löthgren and Tambour (1997) for calculation of bootstrap confidence intervals for the firm-specific Data Envelopment Analysis (DEA) Malmquist productivity index. The simulation results indicate that the...

This paper deals with the question how to model health effects after the cessation of a randomised controlled trial (RCT). Using clinical trial data on severe congestive heart failure patients we illustrate how survival beyond the cessation of a RCT can be predicted based on parametric survival...

This paper evaluates the performance of three bootstrap algorithms for the data envelopment analysis (DEA) estimator using a Monte Carlo simulation study. The Löthgren and Tambour (1997) (LT) algorithm; the Simar and Wilson (1997b) (SW) algorithm; and a combination of the LT and SW algorithms...

The double bootstrap provides a useful tool for bootstrapping approximately pivotal quantities by using an "inner" bootstrap loop to estimate the variance. When the estimators are computationally intensive, the double bootstrap may become infeasible. We propose the use of a new variance...