Statistical Analysis of Noninferiority Trials with a Rate Ratio in Small-sample Matched-pair Designs

• Activity Number: 119
• Type: Contributed
• Date/Time: Monday, August 9, 2004 : 10:30 AM to 12:20 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Ivan S.F. Chan*+ and Nian-Sheng Taug and Man-Lai Taug and Ping-Shing Chan
• Companies: Merck & Co., Inc. and Center for Applied Statistics and Harvard Medical School and Chinese University of Hong Kong

Abstract

Asymptotic methods have recently been developed for analyzing noninferiority trials with rate ratios under the matched-pair design. In small samples, however, the performance of these asymptotic methods may not be reliable. We investigate alternative methods that are desirable for assessing noninferiority trials under small-sample matched-pair designs. We propose an exact and an approximate exact unconditional test and the corresponding confidence intervals based on the score statistic. The exact unconditional method guarantees the Type I error rate not to exceed the nominal level, and it is recommended if strict control of Type I error (protection against any inflated risk of accepting inferior treatments) is required. However, the exact method tends to be overly conservative (thus less powerful) and computationally demanding. Through empirical studies, we demonstrate that the approximate exact score method, which is computationally simple to implement, controls the Type I error rate reasonably well and has high power for hypothesis testing. On balance, the approximate exact method offers a very good alternative for analyzing correlated binary data from matched-pair designs with small sample sizes. We illustrate these methods using real examples taken from a crossover study of soft lenses and a Pneumocystis carinii pneumonia study.