ks-test large samples.R

# number of subjects in each condition
n <- 10000
# number of replications of the study in order to check the Type I error rate
nsamp <- 10000

ps <- replicate(nsamp, {
    #population mean = 0, sd = 1 for both samples, therefore, no real effect
    y1 <- rnorm(n, 0, 1) 
    y2 <- rnorm(n, 0, 1)
    tt <- ks.test(y1, y2)
    tt$p.value
})
sum(ps < .05) / nsamp
# that gave me the expected 0.0466 and 0.0491 on rerun



# number of subjects in each condition
n <- 10000
# number of replications of the study in order to check the Type I error rate
nsamp <- 10000

ps <- replicate(nsamp, {
    #population mean = 0, sd = 1 for both samples, therefore, no real effect
    y1 <- rnorm(n, 0, 1) 
    tt <- ks.test(y1, 'pnorm')
    tt$p.value
})
sum(ps < .05) / nsamp
# that gave me 0.0484, 0.0504 and 0.0484