The estimation of a confidence interval for attributable risk from the logistic model based on data from case-control studies is a problem for which an accepted solution is lacking. Two methods, one based on the delta method and one bootstrap on the population base, have been described but their acc
A comparison of approaches to estimating confidence intervals for willingness to pay measures
β Scribed by Arne Risa Hole
- Publisher
- John Wiley and Sons
- Year
- 2007
- Tongue
- English
- Weight
- 162 KB
- Volume
- 16
- Category
- Article
- ISSN
- 1057-9230
- DOI
- 10.1002/hec.1197
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β¦ Synopsis
Abstract
This paper describes four approaches to estimating confidence intervals for willingness to pay measures: the delta, Fieller, Krinsky Robb and bootstrap methods. The accuracy of the various methods is compared using a number of simulated datasets. In the majority of the scenarios considered all four methods are found to be reasonably accurate as well as yielding similar results. The delta method is the most accurate when the data is wellβconditioned, while the bootstrap is more robust to noisy data and misspecification of the model. These conclusions are illustrated by empirical data from a study of willingness to pay for a reduction in waiting time for a general practitioner appointment in which all the methods produce fairly similar confidence intervals. Copyright Β© 2007 John Wiley & Sons, Ltd.
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