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process_stats <- function(test_type, test_stat, df1, df2, reported_p,
p_comparison, test_comparison, p_dec, test_dec,
OneTailedInTxt,
# options:
two_tailed, alpha, pZeroError, pEqualAlphaSig,
OneTailedTxt, OneTailedTests){
# compute p-value ----------------------------------------------------------
computed_p <- compute_p(test_type = test_type,
test_stat = test_stat,
df1 = df1,
df2 = df2,
two_tailed = two_tailed)
# check if the result is an error ------------------------------------------
error <- error_test(reported_p = reported_p,
test_type = test_type,
test_stat = test_stat,
df1 = df1,
df2 = df2,
p_comparison = p_comparison,
test_comparison = test_comparison,
p_dec = p_dec,
test_dec = test_dec,
two_tailed = two_tailed,
alpha = alpha,
pZeroError = pZeroError)
# check if the result is a decision error ----------------------------------
if(!error){
# if a result is not an error, it's automatically also not a decision error
decision_error <- FALSE
} else {
# only if a result is an error, it makes sense to check if it's also a
# decision error
decision_error <- decision_error_test(reported_p = reported_p,
computed_p = computed_p,
test_comparison = test_comparison,
p_comparison = p_comparison,
alpha = alpha,
pEqualAlphaSig = pEqualAlphaSig)
}
# correct for one-tailed tests in text ------------------------------------
# OneTailedTxt is an option that determines whether statcheck should
# try to correct for 1-tailed tests as follows:
# if the phrase one-tailed/one-sided/directional is in the full text,
# AND if the reported p-value would have been correct if it was a one-
# tailed test, classify the result as consistent
# don't apply this correction if OneTailedTests == FALSE, because this already
# forces statcheck to treat all results as one-tailed tests
if(OneTailedTxt == TRUE & OneTailedTests == FALSE){
# select only results where the phrase "one-tailed", "one-sided" or
# "directional" was mentioned in text, and that were an error when
# we assumed two-tailed tests
upForCorrection <- error & OneTailedInTxt
# only start correction procedure if the result fits the criteria above
if (upForCorrection){
# for this case, recompute the p-value, but this time assuming a
# one-tailed test
computed_p_1tail <- compute_p(test_type = test_type,
test_stat = test_stat,
df1 = df1,
df2 = df2,
two_tailed = FALSE)
# check whether result would still be an error if 1-tailed
error_1tail <-
error_test(reported_p = reported_p,
test_type = test_type,
test_stat = test_stat,
df1 = df1,
df2 = df2,
p_comparison = p_comparison,
test_comparison = test_comparison,
p_dec = p_dec,
test_dec = test_dec,
two_tailed = FALSE,
alpha = alpha,
pZeroError = pZeroError)
if(!error_1tail){
# if a result is not an error, it's automatically also not a decision error
decision_error_1tail <- FALSE
} else {
# only if a result is an error, it makes sense to check if it's also a
# decision error
decision_error_1tail <-
decision_error_test(reported_p = reported_p,
computed_p = computed_p_1tail,
test_comparison = test_comparison,
p_comparison = p_comparison,
alpha = alpha,
pEqualAlphaSig = pEqualAlphaSig)
}
# if the 1-tailed p-value is no longer an error, the original values of
# error, decisionerror, and computed_p should be overwritten with the 1-
# tailed versions
if(error != error_1tail){
computed_p <- computed_p_1tail
error <- error_1tail
decision_error <- decision_error_1tail
}
}
}
result <- data.frame(computed_p = computed_p,
error = error,
decision_error = decision_error)
return(result)
}
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