t.diff {MSG} | R Documentation |
The differences of P-values in t test assuming equal or unequal variances
Description
Given that the variances of two groups are unequal, we compute the difference of P-values assuming equal or unequal variances respectively by simulation.
Format
A data frame with 1000 rows and 99 columns.
Details
See the Examples section for the generation of this data.
Source
By simulation.
References
Welch B (1947). “The generalization of Student's problem when several different population variances are involved.” Biometrika, 34(1/2), 28–35.
Examples
data(t.diff)
boxplot(t.diff, axes = FALSE, xlab = expression(n[1]))
axis(1)
axis(2)
box()
## reproducing the data
if (interactive()) {
set.seed(123)
t.diff = NULL
for (n1 in 2:100) {
t.diff = rbind(t.diff, replicate(1000, {
x1 = rnorm(n1, mean = 0, sd = runif(1, 0.5, 1))
x2 = rnorm(30, mean = 1, sd = runif(1, 2, 5))
t.test(x1, x2, var.equal = TRUE)$p.value - t.test(x1, x2,
var.equal = FALSE)$p.value
}))
}
t.diff = as.data.frame(t(t.diff))
colnames(t.diff) = 2:100
}
[Package MSG version 0.8 Index]