RM.pwr.chisq.test: RM.pwr.chisq.test

In magoulet93/RM.pwr: Calculate effective number of participant when repeating measurements

Description

This function calculates the effective number of participants in a power analysis for a chi-square test after considering the effect of the number of measurement for each dependent variable and the intra-class correlation of these measurements.

Arguments

w	Effect size w
sig.level	Alpha level
power	Desired statistical power
df	Degrees of freedom
corr	Intra-class correlation between the replicated measurements.
m	Number of replicated measurements.

Details

The function returns the effective number of participants to attain the specified statistical power. You do not need to specify that n is NULL. For more details about this statistical power adjustment, see Goulet & Cousineau (2019).

References

Goulet, M.A. & Cousineau, D. (2019). The power of replicated measures to increase statistical power. Advances in Methods and Practices in Psychological Sciences, 2(3), 199-213. DOI:10.1177/2515245919849434

See Also

pwr.chisq.test

Examples

# Calculating the effective sample size for a chi-square test.
# Intra-class correlation is .3 and number of replicated measurements is 20.

RM.pwr.chisq.test(
 w = 0.4, # Want to detect a W of 0.4
 df = 4,
 sig.level = .05,
 power = .90,
 corr = .3,
 m = 20
)

magoulet93/RM.pwr documentation built on May 5, 2020, 7:18 a.m.