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Activity Number: 321
Type: Contributed
Date/Time: Tuesday, August 6, 2013 : 8:30 AM to 10:20 AM
Sponsor: Biopharmaceutical Section
Abstract - #309620
Title: M&N, Wald, and Skellam: Who Excels in Rare-Event, Small-Sample, Interval Estimation of Risk Differences?
Author(s): Oliver Bautista*+ and Josh Chen and Ivan S. F. Chan
Companies: Merck Sharp & Dohme Corp and Merck and Merck Research Laboratories
Keywords: Confidence interval ; Incidence rate difference ; Small samples ; Rare events
Abstract:

Interval estimation of risk differences in settings of rare-events (i.e., low incidence rates) is common in many vaccine trials. A number of authors have proposed interval estimators of difference of exposure-adjusted incidence rates (EAIR), or estimators of difference of independent Poisson rates. We compared these interval estimates previously proposed with one that has not been previously proposed, based on the Skellam distribution, herein referred as "qSkellam-based" interval estimator. The Wald-based estimator does well in terms of coverage and interval length in large sample size settings even when the incidence rates are low, but not so well in small sample size settings. The Mittienen and Nurminen (M&N)-based and qSkellam-based estimators do well in moderately small sample size settings. The qSkellam-based estimator excels in terms of coverage and interval length in very small sample size and low incidence rate settings. The qSkellam-based estimator of difference of EAIR can be valuable in sub-group analyses involving rare events, where sample sizes can be very small.


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