power.plot.chisq: Power analysis plot of chi-squared test In powerAnalysis: Power Analysis in Experimental Design

Description

Power analysis plot of chi-squared test

Usage

 ```1 2 3``` ```power.plot.chisq(es = NULL, power = NULL, df = NULL, sig.level = NULL, allele = FALSE, xlab = NULL, ylab = NULL, main = NULL, grid = FALSE, type = c("np", "ne")) ```

Arguments

 `es` effect size. `power` power of study `df` degree of freedom `sig.level` significance level `allele` in genetic association study, whether test allele or genotype `xlab` a title for the x axis `ylab` a title for the y axis `main` an overall title for the plot `grid` add grid lines or not `type` "np": plot sample size vs. power; "ne": plot effevct size vs. sample size

`power.chisq`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18``` ```## 'ne' type ### multiple effect size and multiple power es=seq(from=0.1,to=0.5,by=0.1); power=seq(from=0.7,to=0.9,by=0.1); power.plot.chisq(es=es,power=power,df=1,sig.level=0.05,type="ne") power.plot.chisq(es=es,power=power,df=1,sig.level=0.05,type="np") ### multiple effect size and single power power.plot.chisq(es=seq(0.05,0.3,0.05),power=0.8,df=1,sig.level=0.05,type="ne") power.plot.chisq(es=seq(0.05,0.3,0.05),power=0.8,df=1,sig.level=0.05,type="np") ### single effect size and single power power.plot.chisq(es=0.2,power=0.8,df=1,sig.level=0.05,type="ne") power.plot.chisq(es=0.2,power=0.8,df=1,sig.level=0.05,type="np") ### single effect size and multiple power power.plot.chisq(es=0.2,power=seq(0.5,0.9,0.1),df=1,sig.level=0.05,type="ne") power.plot.chisq(es=0.2,power=seq(0.5,0.9,0.1),df=1,sig.level=0.05,type="np") ```