Description Usage Arguments Value Author(s)
Quick no-nonsens adaptive permutation decision rule
1 2 3 4 | adaptive_permdr(x1, x2, xE, g1, g2, gE, test_statistic, alpha, permutations,
restricted, stratified, atest_type = c("non-randomized", "mid-p",
"davison_hinkley", "CER"), cer_type = c("non-randomized", "randomized",
"uniform"))
|
x1 |
first stage observations |
x2 |
second stage observations |
xE |
extended stage observations |
g1 |
frist stage treatment assignments |
g2 |
second stage treatment assignments |
gE |
extended stage treatment assignments |
test_statistic |
test statistic to use |
alpha |
significance level |
permutations |
number of permutations to use |
restricted |
should the treatment group sizes be fixed |
stratified |
should permutation be stratified by stage |
atest_type |
if 'CER' compute only conditional error rate, else type of adaptive test should be performed (see |
cer_type |
what type of conditional error rate function should be used (see |
pvalue
Florian Klinglmueller
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