pwr (version 1.2-0)

pwr.r.test: Power calculations for correlation test

Description

Compute power of test or determine parameters to obtain target power (same as power.anova.test).

Usage

pwr.r.test(n = NULL, r = NULL, sig.level = 0.05, power = NULL,  alternative = c("two.sided", "less","greater"))

Arguments

n

Number of observations

r

Linear correlation coefficient

sig.level

Significance level (Type I error probability)

power

Power of test (1 minus Type II error probability)

alternative

a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less"

Value

Object of class '"power.htest"', a list of the arguments (including the computed one) augmented with 'method' and 'note' elements.

Details

These calculations use the Z' transformation of correlation coefficient : Z'=arctanh(r)+r/(2*(n-1)) (see Cohen (1988) p.546).

Exactly one of the parameters 'r','n','power' and 'sig.level' must be passed as NULL, and that parameter is determined from the others. Notice that the last one has non-NULL default so NULL must be explicitly passed if you want to compute it.

References

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale,NJ: Lawrence Erlbaum.

Examples

## Exercise 3.1 p. 96 from Cohen (1988)
pwr.r.test(r=0.3,n=50,sig.level=0.05,alternative="two.sided")
pwr.r.test(r=0.3,n=50,sig.level=0.05,alternative="greater")

## Exercise 3.4 p. 208
pwr.r.test(r=0.3,power=0.80,sig.level=0.05,alternative="two.sided")
pwr.r.test(r=0.5,power=0.80,sig.level=0.05,alternative="two.sided")
pwr.r.test(r=0.1,power=0.80,sig.level=0.05,alternative="two.sided")