Journal
JOURNAL OF BIOPHARMACEUTICAL STATISTICS
Volume 20, Issue 4, Pages 787-802Publisher
TAYLOR & FRANCIS INC
DOI: 10.1080/10543401003618819
Keywords
Clinical trials; Effect size; Power function; Sample size requirements; Three-way interaction; Two-way interaction
Categories
Funding
- National Institutes of Health [MH060447, MH066270, DA023021, AI051519]
- NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES [P30AI051519] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE OF MENTAL HEALTH [R01MH060447, P30MH066270] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE ON DRUG ABUSE [R25DA023021] Funding Source: NIH RePORTER
Ask authors/readers for more resources
Based on maximum likelihood estimates obtained from mixed-effects linear models, closed-form power functions are derived to detect two-way and three-way interactions that involve longitudinal course of outcome over time in clinical trials. Sample size estimates are shown to decrease with increasing within-subject correlations. It is further shown that when clinical trial designs are balanced in group sizes, the sample size required to detect an effect size for a three-way interaction is exactly fourfold that required to detect the same effect size of a two-way interaction. Furthermore, this fourfold relationship virtually holds for unbalanced allocations of subjects if one factor is balanced in the three-way interaction model. Simulations are presented that verify the sample size estimates for two-way and three-way interactions.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available