Approximates the power of a paired-samples test of equal proportions for a planned sample size

Source: R/statpsych3.R

Computes the approximate power of a test for equal population proportions in a paired-samples design (the McNemar test). This function requires planning values for both proportions and a phi coefficient that describes the correlation between the two dichotomous measurements. The proportion planning values can set to .5 for a conservatively low power estimate. The planning value for the proportion difference (effect size) could be set to the difference of the two proportion planning values or it could be set to a minimally interesting effect size. Set the phi correlation planning value to the smallest value within a plausible range for a conservatively low power estimate.

power.prop.ps(alpha, n, p1, p2, phi, es)

Arguments

alpha

alpha level for hypothesis test

n

planned sample size

p1

planning value of proportion for measurement 1

p2

planning value of proportion for measurement 2

phi

planning value of phi correlation

es

planning value of proportion difference

Value

Returns the approximate power of the test

Examples

power.prop.ps(.05, 45, .5, .5, .4, .2)
#>      Power
#>  0.6877704

# Should return:
#     Power
# 0.6877704