# power.chisq: Power calculations for chi-squared test In powerAnalysis: Power Analysis in Experimental Design

## Description

Power calculations for chi-squared test

## Usage

 ```1 2``` ```power.chisq(es = NULL, df = NULL, n = NULL, power = NULL, sig.level = NULL) ```

## Arguments

 `es` effect size. A numeric value or output of ES.chisq.gof, ES.chisq.assoc `df` degree of freedom `n` total number of observations `power` power of study `sig.level` significance level

`ES.chisq.gof`

`ES.chisq.assoc`

`power.plot.chisq`

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```## calculate power power.chisq(es=0.16,df=1,n=530,sig.level=0.05) ## calculate sig.level power.chisq(es=0.16,df=1,n=530,power=0.9576) ## calculate sample size power.chisq(es=0.16,df=1,power=0.9576,sig.level=0.05) ## calculate effect size power.chisq(df=1,n=530,power=0.9576,sig.level=0.05) ```

### Example output

```     Chi squared power calculation

Power = 0.9576021
Effect_Size = 0.16
df = 1
n = 530
sig.level = 0.05

NOTE: 'n' is the number of observations

Chi squared power calculation

Power = 0.9576
Effect_Size = 0.16
df = 1
n = 530
sig.level = 0.05001906

NOTE: 'n' is the number of observations

Chi squared power calculation

Power = 0.9576
Effect_Size = 0.16
df = 1
n = 530
sig.level = 0.05

NOTE: 'n' is the number of observations

Chi squared power calculation

Power = 0.9576
Effect_Size = 0.1600017
df = 1
n = 530
sig.level = 0.05

NOTE: 'n' is the number of observations
```

powerAnalysis documentation built on May 2, 2019, 12:40 p.m.