pwr.chisq.test: power calculations for chi-squared tests

In pwr: Basic Functions for Power Analysis

Description

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

Usage

pwr.chisq.test(w = NULL, N = NULL, df = NULL, sig.level = 0.05, power = NULL)

Arguments

w	Effect size
N	Total number of observations
df	degree of freedom (depends on the chosen test)
sig.level	Significance level (Type I error probability)
power	Power of test (1 minus Type II error probability)

Details

Exactly one of the parameters 'w','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.

Value

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

Note

'uniroot' is used to solve power equation for unknowns, so you may see errors from it, notably about inability to bracket the root when invalid arguments are given.

Author(s)

Stephane Champely <[e-mail]> but this is a mere copy of Peter Dalgaard work (power.t.test)

References

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

See Also

ES.w1,ES.w2

Examples

## Exercise 7.1 P. 249 from Cohen (1988) 
pwr.chisq.test(w=0.289,df=(4-1),N=100,sig.level=0.05)

## Exercise 7.3 p. 251
pwr.chisq.test(w=0.346,df=(2-1)*(3-1),N=140,sig.level=0.01)

## Exercise 7.8 p. 270
pwr.chisq.test(w=0.1,df=(5-1)*(6-1),power=0.80,sig.level=0.05)

pwr documentation built on March 17, 2020, 5:11 p.m.