Simulating Type S and Type M errors

typesm

## probable effect size derived from past studies:
D<-15
## SE from the study of interest:
se<-46
stddev<-se*sqrt(37)
nsim<-10000
drep<-rep(NA,nsim)
for(i in 1:nsim){
drep[i]<-mean(rnorm(37,mean=D,sd=stddev))
}

## which cells in drep are significant at alpha=0.05?
signif<-which(abs(drep/se)>2)
## Type S error rate | signif:
types_sig<-mean(drep[signif]<0)
## Type S error rate | non-signif: 
types_nonsig<-mean(drep[-signif]<0)
## Type M error rate | signif: 
typem_sig<-mean(abs(drep[signif])/D)
## Type M error rate | not-signif: 
typem_nonsig<-mean(abs(drep[-signif])/D)