ES.w2: Effect size calculation in the chi-squared test for... In pwr: Basic Functions for Power Analysis

Description

Compute effect size w for a two-way probability table corresponding to the alternative hypothesis in the chi-squared test of association in two-way contingency tables

Usage

 `1` ```ES.w2(P) ```

Arguments

 `P` A two-way probability table (alternative hypothesis)

Value

The corresponding effect size w

Author(s)

Stephane CHAMPELY

References

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

pwr.chisq.test

Examples

 ```1 2 3 4``` ```prob<-matrix(c(0.225,0.125,0.125,0.125,0.16,0.16,0.04,0.04),nrow=2,byrow=TRUE) prob ES.w2(prob) pwr.chisq.test(w=ES.w2(prob),df=(2-1)*(4-1),N=200) ```

Example output

```      [,1]  [,2]  [,3]  [,4]
[1,] 0.225 0.125 0.125 0.125
[2,] 0.160 0.160 0.040 0.040
[1] 0.2558646

Chi squared power calculation

w = 0.2558646
N = 200
df = 3
sig.level = 0.05
power = 0.8733222

NOTE: N is the number of observations
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pwr documentation built on March 17, 2020, 5:11 p.m.