# pwr.chisq.test: power calculations for chi-squared tests In heliosdrm/pwr: Basic Functions for Power Analysis

## Description

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

## Usage

 `1` ```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 <champely@univ-lyon1.fr> 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.

 ```1 2 3 4 5 6 7 8``` ```## 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) ```