size.equiv.mean.ps: Sample size for a paired-samples mean equivalence test

In statpsych: Statistical Methods for Psychologists

Sample size for a paired-samples mean equivalence test

Description

Computes the sample size required to perform an equivalence test for the difference in population means with desired power in a paired-samples design. The value of h specifies a range of practical equivalence, -h to h, for the difference in population means. The planning value for the absolute mean difference must be less than h. Equivalence tests often require a very large sample size. Equivalence tests usually use 2 x alpha rather than alpha (e.g., use alpha = .10 rather alpha = .05). Set the Pearson correlation value to the smallest value within a plausible range, and set the variance planning value to the largest value within a plausible range for a conservatively large sample size.

Usage

size.equiv.mean.ps(alpha, pow, var, es, cor, h)

Arguments

alpha	alpha level for hypothesis test
pow	desired power
var	planning value of average variance of the two measurements
es	planning value of mean difference
cor	planning value of the correlation between measurements
h	upper limit for range of practical equivalence

Value

Returns the required sample size

Examples

size.equiv.mean.ps(.10, .85, 15, .5, .7, 1.5)

# Should return:
#      Sample size
# [1,]          68
 

statpsych documentation built on July 9, 2023, 6:50 p.m.