Nothing
compute_p <- function(test_type, test_stat, df1, df2, two_tailed){
stopifnot(test_type %in% c("t", "F", "Z", "r", "Chi2", "Q", "Qb", "Qw"))
# compute p-values ---------------------------------------------------------
if(test_type == "t"){
computed <- stats::pt(-1 * abs(test_stat), df2)
} else if(test_type == "F"){
computed <- stats::pf(test_stat, df1, df2, lower.tail = FALSE)
} else if(test_type == "Z"){
computed <- stats::pnorm(abs(test_stat), lower.tail = FALSE)
} else if(test_type == "r"){
t <- r2t(test_stat, df2)
computed <- stats::pt(-1 * abs(t), df2)
} else if(test_type == "Chi2" |
test_type == "Q" | test_type == "Qb" | test_type == "Qw"){
computed <- stats::pchisq(test_stat, df1, lower.tail = FALSE)
}
# compute two-tailed ------------------------------------------------------
if (!is.na(computed) &
(test_type == "t" | test_type == "Z" | test_type == "r") &
two_tailed) {
computed <- computed * 2
}
# return ------------------------------------------------------------------
return(computed)
}
# Function to transform correlations into t-values by use of raw r and degrees of freedom.
r2t <- function(r, df){
t <- r / (sqrt((1 - r^2) / df))
return(t)
}
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