Details
Original language | English |
---|---|
Pages (from-to) | 1131-1147 |
Number of pages | 17 |
Journal | Statistics in medicine |
Volume | 25 |
Issue number | 7 |
Publication status | Published - 11 Oct 2006 |
Abstract
In this paper, we address the problem of calculating power and sample sizes associated with simultaneous tests for non-inferiority. We consider the case of comparing several experimental treatments with an active control. The approach is based on the ratio view, where the common non-inferiority margin is chosen to be some percentage of the mean of the control treatment. Two power definitions in multiple hypothesis testing, namely, complete power and minimal power, are used in the computations. The sample sizes associated with the ratio-based inference are also compared with that of a comparable inference based on the difference of means for various scenarios. It is found that the sample size required for ratio-based inferences is smaller than that of difference-based inferences when the relative non-inferiority margin is less than one and when large response values indicate better treatment effects. The results are illustrated with examples.
Keywords
- Least favourable configuration, Multiple comparison, Non-central t, Non-inferiority, Ratio-to-control
ASJC Scopus subject areas
- Medicine(all)
- Epidemiology
- Mathematics(all)
- Statistics and Probability
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In: Statistics in medicine, Vol. 25, No. 7, 11.10.2006, p. 1131-1147.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Power and sample size computations in simultaneous tests for non-inferiority based on relative margins
AU - Dilba, Gemechis
AU - Bretz, Frank
AU - Hothorn, Ludwig A.
AU - Guiard, Volker
PY - 2006/10/11
Y1 - 2006/10/11
N2 - In this paper, we address the problem of calculating power and sample sizes associated with simultaneous tests for non-inferiority. We consider the case of comparing several experimental treatments with an active control. The approach is based on the ratio view, where the common non-inferiority margin is chosen to be some percentage of the mean of the control treatment. Two power definitions in multiple hypothesis testing, namely, complete power and minimal power, are used in the computations. The sample sizes associated with the ratio-based inference are also compared with that of a comparable inference based on the difference of means for various scenarios. It is found that the sample size required for ratio-based inferences is smaller than that of difference-based inferences when the relative non-inferiority margin is less than one and when large response values indicate better treatment effects. The results are illustrated with examples.
AB - In this paper, we address the problem of calculating power and sample sizes associated with simultaneous tests for non-inferiority. We consider the case of comparing several experimental treatments with an active control. The approach is based on the ratio view, where the common non-inferiority margin is chosen to be some percentage of the mean of the control treatment. Two power definitions in multiple hypothesis testing, namely, complete power and minimal power, are used in the computations. The sample sizes associated with the ratio-based inference are also compared with that of a comparable inference based on the difference of means for various scenarios. It is found that the sample size required for ratio-based inferences is smaller than that of difference-based inferences when the relative non-inferiority margin is less than one and when large response values indicate better treatment effects. The results are illustrated with examples.
KW - Least favourable configuration
KW - Multiple comparison
KW - Non-central t
KW - Non-inferiority
KW - Ratio-to-control
UR - http://www.scopus.com/inward/record.url?scp=33645465471&partnerID=8YFLogxK
U2 - 10.1002/sim.2359
DO - 10.1002/sim.2359
M3 - Article
C2 - 16217842
AN - SCOPUS:33645465471
VL - 25
SP - 1131
EP - 1147
JO - Statistics in medicine
JF - Statistics in medicine
SN - 0277-6715
IS - 7
ER -