COMPUTING CONFIDENCE-BOUNDS FOR POWER AND SAMPLE-SIZE OF THE GENERAL LINEAR UNIVARIATE MODEL

The power of a test, the probability of rejecting the null hypothesis in favor of an alternative, may be computed using estimates of one or more distributional parameters, Statisticians frequently fix mean valu es and calculate power or sample size using a variance estimate from a n existing study, Hence computed power becomes a random variable for a fixed sample size. Likewise, the sample size necessary to achieve a f ixed power varies randomly. Standard statistical practice requires rep orting uncertainty associated with such point estimates. Previous auth ors studied an asymptotically unbiased method of obtaining confidence intervals for noncentrality and power of the general linear univariate model in this setting. We provide exact confidence intervals for nonc entrality, power, and sample size. Such confidence intervals, particul arly ope-sided intervals, help in planning a future study and in evalu ating existing studies.