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Confidence intervals for the risk ratio under inverse sampling
Author(s) -
Tian M.,
Tang M. L.,
Ng H. K. T.,
Chan P. S.
Publication year - 2007
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.3158
Subject(s) - confidence interval , statistics , robust confidence intervals , sampling (signal processing) , mathematics , econometrics , computer science , filter (signal processing) , computer vision
In this paper, we investigate various confidence intervals for the risk ratio under inverse sampling (also known as negative binomial sampling). Three existing confidence intervals (namely, the confidence intervals that are based on Fieller's theorem, the delta method and the F ‐statistic) are reviewed and three new confidence intervals (namely, the score, likelihood ratio and saddlepoint approximation (SA)‐based confidence intervals) are developed. Comparative studies among these confidence intervals through Monte Carlo simulations are evaluated in terms of their coverage probabilities and expected interval widths under different settings. Our simulation results suggest that the SA‐based confidence interval is generally more appealing. We illustrate these confidence interval construction methods with real data sets from a drug comparison study and a congenital heart disease study. Copyright © 2007 John Wiley & Sons, Ltd.