Abstract
In this article, we present a simple method to calculate sample size and power for a simulation-based multiple testing procedure which gives a sharper critical value than the standard Bonferroni method. The method is especially useful when several highly correlated test statistics are involved in a multiple-testing procedure. The formula for sample size calculation will be useful in designing clinical trials with multiple endpoints or correlated outcomes. We illustrate our method with a quality-of-life study for patients with early stage prostate cancer. Our method can also be used for comparing multiple independent groups.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 957-967 |
| Number of pages | 11 |
| Journal | Journal of Biopharmaceutical Statistics |
| Volume | 15 |
| Issue number | 6 |
| DOIs | |
| State | Published - 2005 |
| Externally published | Yes |
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Keywords
- Bonferroni
- Global test
- Multiple endpoints
- Multiple testing
- Sample size
- Simulation
ASJC Scopus subject areas
- Pharmacology (medical)
- Pharmacology, Toxicology and Pharmaceutics(all)
Cite this
Sample size calculation for simulation-based multiple-testing procedures. / Bang, Heejung; Jung, Sin Ho; George, Stephen L.
In: Journal of Biopharmaceutical Statistics, Vol. 15, No. 6, 2005, p. 957-967.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Sample size calculation for simulation-based multiple-testing procedures
AU - Bang, Heejung
AU - Jung, Sin Ho
AU - George, Stephen L.
PY - 2005
Y1 - 2005
N2 - In this article, we present a simple method to calculate sample size and power for a simulation-based multiple testing procedure which gives a sharper critical value than the standard Bonferroni method. The method is especially useful when several highly correlated test statistics are involved in a multiple-testing procedure. The formula for sample size calculation will be useful in designing clinical trials with multiple endpoints or correlated outcomes. We illustrate our method with a quality-of-life study for patients with early stage prostate cancer. Our method can also be used for comparing multiple independent groups.
AB - In this article, we present a simple method to calculate sample size and power for a simulation-based multiple testing procedure which gives a sharper critical value than the standard Bonferroni method. The method is especially useful when several highly correlated test statistics are involved in a multiple-testing procedure. The formula for sample size calculation will be useful in designing clinical trials with multiple endpoints or correlated outcomes. We illustrate our method with a quality-of-life study for patients with early stage prostate cancer. Our method can also be used for comparing multiple independent groups.
KW - Bonferroni
KW - Global test
KW - Multiple endpoints
KW - Multiple testing
KW - Sample size
KW - Simulation
UR - http://www.scopus.com/inward/record.url?scp=27544509477&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=27544509477&partnerID=8YFLogxK
U2 - 10.1080/10543400500265710
DO - 10.1080/10543400500265710
M3 - Article
VL - 15
SP - 957
EP - 967
JO - Journal of Biopharmaceutical Statistics
JF - Journal of Biopharmaceutical Statistics
SN - 1054-3406
IS - 6
ER -