# R. Chris Fraley | Nov 29 2002
# Estimate statistical power of a correlation
 
# To use this program, simply plug in the expected or hypothesized mean for each group (m1 and m2)
# as well as the hypothesized standard deviation (k) and sample size (n).
# At the end, the program will tell you the proportion of times that you'll obtain
# a p-value less than 5%.

 
m1<- 10    # hypothesized mean for group 1
m2<- 11    # hypothesized mean for group 2

k<-1         # hypothesized sd within each condition
n<-10        # number of people 

#-----------------------------------------------------------
# The rest of this doesn't need to be adjusted by the user.
#-----------------------------------------------------------

trials<-1000

p.vec<-rep(99999,trials)
for(i in 1:trials){
  x1<-rnorm(n,mean=m1,sd=k) # simulate data for cell 1
  x2<-rnorm(n,mean=m2,sd=k) # simulate data for cell 2
	p.vec[i]<-t.test(x1,x2)$p.value

}

cat("Proportion of times the null hypothesis will be rejected ","\n") 
print(table(p.vec<=.05)/trials)