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

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

See Also

power.chisq

Examples

## '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")

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