Nothing
tests/testthat/_snaps/shuffle_card.md
In tfrmt: Applies Display Metadata to Analysis Results Datasets
shuffle/trim works
Code
ard_simple_shuffled
Output
ARM AGE context stat_variable stat_name
1 Placebo Overall AGE continuous AGE N
2 Placebo Overall AGE continuous AGE mean
3 Placebo Overall AGE continuous AGE sd
4 Placebo Overall AGE continuous AGE median
5 Placebo Overall AGE continuous AGE p25
6 Placebo Overall AGE continuous AGE p75
7 Placebo Overall AGE continuous AGE min
8 Placebo Overall AGE continuous AGE max
9 Xanomeline High Dose Overall AGE continuous AGE N
10 Xanomeline High Dose Overall AGE continuous AGE mean
11 Xanomeline High Dose Overall AGE continuous AGE sd
12 Xanomeline High Dose Overall AGE continuous AGE median
13 Xanomeline High Dose Overall AGE continuous AGE p25
14 Xanomeline High Dose Overall AGE continuous AGE p75
15 Xanomeline High Dose Overall AGE continuous AGE min
16 Xanomeline High Dose Overall AGE continuous AGE max
17 Xanomeline Low Dose Overall AGE continuous AGE N
18 Xanomeline Low Dose Overall AGE continuous AGE mean
19 Xanomeline Low Dose Overall AGE continuous AGE sd
20 Xanomeline Low Dose Overall AGE continuous AGE median
21 Xanomeline Low Dose Overall AGE continuous AGE p25
22 Xanomeline Low Dose Overall AGE continuous AGE p75
23 Xanomeline Low Dose Overall AGE continuous AGE min
24 Xanomeline Low Dose Overall AGE continuous AGE max
stat_label stat fmt_fun warning error
1 N 86.000000 0 NULL NULL
2 Mean 75.209302 1 NULL NULL
3 SD 8.590167 1 NULL NULL
4 Median 76.000000 1 NULL NULL
5 Q1 69.000000 1 NULL NULL
6 Q3 82.000000 1 NULL NULL
7 Min 52.000000 1 NULL NULL
8 Max 89.000000 1 NULL NULL
9 N 84.000000 0 NULL NULL
10 Mean 74.380952 1 NULL NULL
11 SD 7.886094 1 NULL NULL
12 Median 76.000000 1 NULL NULL
13 Q1 70.500000 1 NULL NULL
14 Q3 80.000000 1 NULL NULL
15 Min 56.000000 1 NULL NULL
16 Max 88.000000 1 NULL NULL
17 N 84.000000 0 NULL NULL
18 Mean 75.666667 1 NULL NULL
19 SD 8.286051 1 NULL NULL
20 Median 77.500000 1 NULL NULL
21 Q1 71.000000 1 NULL NULL
22 Q3 82.000000 1 NULL NULL
23 Min 51.000000 1 NULL NULL
24 Max 88.000000 1 NULL NULL
Code
ard_shuffled[1:5, ]
Output
ARM AGE AGEGR1 context stat_variable stat_name
1 Placebo <NA> <NA> categorical ARM n
2 Placebo <NA> <NA> categorical ARM N
3 Placebo <NA> <NA> categorical ARM p
4 Xanomeline High Dose <NA> <NA> categorical ARM n
5 Xanomeline High Dose <NA> <NA> categorical ARM N
stat_label stat
1 n 86.0000000
2 N 254.0000000
3 % 0.3385827
4 n 84.0000000
5 N 254.0000000
Code
ard_shuff_trim[1:5, ]
Output
ARM AGE AGEGR1 context stat_variable stat_name
1 Placebo <NA> <NA> categorical ARM n
2 Placebo <NA> <NA> categorical ARM N
3 Placebo <NA> <NA> categorical ARM p
4 Xanomeline High Dose <NA> <NA> categorical ARM n
5 Xanomeline High Dose <NA> <NA> categorical ARM N
stat_label stat
1 n 86.0000000
2 N 254.0000000
3 % 0.3385827
4 n 84.0000000
5 N 254.0000000
shuffle_card notifies user about warnings/errors before dropping
Code
shuffle_card(cards::ard_continuous(cards::ADSL, variables = AGEGR1))
Message
"warning" column contains messages that will be removed.
Output
# A tibble: 8 x 6
AGEGR1 context stat_variable stat_name stat_label stat
<chr> <chr> <chr> <chr> <chr> <chr>
1 Overall AGEGR1 continuous AGEGR1 N N 254
2 Overall AGEGR1 continuous AGEGR1 mean Mean <NA>
3 Overall AGEGR1 continuous AGEGR1 sd SD <NA>
4 Overall AGEGR1 continuous AGEGR1 median Median <NA>
5 Overall AGEGR1 continuous AGEGR1 p25 Q1 65-80
6 Overall AGEGR1 continuous AGEGR1 p75 Q3 >80
7 Overall AGEGR1 continuous AGEGR1 min Min 65-80
8 Overall AGEGR1 continuous AGEGR1 max Max >80
shuffle_card fills missing group levels if the group is meaningful
Code
shuffle_card(dplyr::filter(cards::bind_ard(cards::ard_continuous(cards::ADSL,
by = "ARM", variables = "AGE", statistic = ~ cards::continuous_summary_fns(
"mean")), dplyr::tibble(group1 = "ARM", variable = "AGE", stat_name = "p",
stat_label = "p", stat = list(0.05))), dplyr::row_number() <= 5L))
Output
# A tibble: 4 x 7
ARM AGE context stat_variable stat_name stat_label stat
<chr> <chr> <chr> <chr> <chr> <chr> <dbl>
1 Placebo Overall~ contin~ AGE mean Mean 75.2
2 Xanomeline High Dose Overall~ contin~ AGE mean Mean 74.4
3 Xanomeline Low Dose Overall~ contin~ AGE mean Mean 75.7
4 Overall ARM Overall~ <NA> AGE p p 0.05
Code
shuffle_card(dplyr::filter(cards::bind_ard(cards::ard_continuous(cards::ADSL,
variables = "AGE", statistic = ~ cards::continuous_summary_fns("mean")), dplyr::tibble(
group1 = "ARM", variable = "AGE", stat_name = "p", stat_label = "p", stat = list(
0.05))), dplyr::row_number() <= 5L))
Output
# A tibble: 2 x 7
ARM AGE context stat_variable stat_name stat_label stat
<chr> <chr> <chr> <chr> <chr> <chr> <dbl>
1 <NA> Overall AGE continuous AGE mean Mean 75.1
2 Overall ARM Overall AGE <NA> AGE p p 0.05
Code
as.data.frame(shuffle_card(cards::bind_ard(dplyr::slice(cards::ard_categorical(
cards::ADSL, by = ARM, variables = AGEGR1), 1), dplyr::slice(cards::ard_categorical(
cards::ADSL, variables = AGEGR1), 1), dplyr::slice(cards::ard_continuous(
cards::ADSL, by = SEX, variables = AGE), 1), dplyr::slice(cards::ard_continuous(
cards::ADSL, variables = AGE), 1)), by = c("ARM", "SEX")))
Output
ARM SEX AGEGR1 AGE context stat_variable
1 Placebo <NA> 65-80 <NA> categorical AGEGR1
2 Overall ARM <NA> 65-80 <NA> categorical AGEGR1
3 <NA> Overall SEX <NA> Overall AGE continuous AGE
4 <NA> F <NA> Overall AGE continuous AGE
stat_name stat_label stat
1 n n 42
2 n n 144
3 N N 254
4 N N 143
Code
as.data.frame(shuffle_card(cards::bind_ard(dplyr::slice(cards::ard_categorical(
cards::ADSL, by = ARM, variables = AGEGR1), 1), dplyr::slice(cards::ard_categorical(
cards::ADSL, variables = AGEGR1), 1), dplyr::slice(cards::ard_continuous(
cards::ADSL, by = SEX, variables = AGE), 1), dplyr::slice(cards::ard_continuous(
cards::ADSL, variables = AGE), 1)), by = c("ARM", "SEX"), fill_overall = "{colname}"))
Output
ARM SEX AGEGR1 AGE context stat_variable stat_name stat_label stat
1 Placebo <NA> 65-80 <NA> categorical AGEGR1 n n 42
2 ARM <NA> 65-80 <NA> categorical AGEGR1 n n 144
3 <NA> SEX <NA> AGE continuous AGE N N 254
4 <NA> F <NA> AGE continuous AGE N N 143
Code
shuffle_card(cards::bind_ard(dplyr::slice(cards::ard_categorical(cards::ADSL,
by = c(ARM, SEX), variables = AGEGR1), 1), dplyr::slice(cards::ard_categorical(
cards::ADSL, by = SEX, variables = AGEGR1), 1), dplyr::slice(cards::ard_categorical(
cards::ADSL, variables = AGEGR1), 1)), by = c("ARM", "SEX"))
Output
# A tibble: 3 x 8
ARM SEX AGEGR1 context stat_variable stat_name stat_label stat
<chr> <chr> <chr> <chr> <chr> <chr> <chr> <int>
1 Placebo F 65-80 catego~ AGEGR1 n n 22
2 Overall ARM F 65-80 catego~ AGEGR1 n n 78
3 Overall ARM Overall S~ 65-80 catego~ AGEGR1 n n 144
Code
shuffle_card(cards::bind_ard(dplyr::slice(cards::ard_categorical(cards::ADSL,
by = c(ARM, SEX), variables = AGEGR1), 1), dplyr::slice(cards::ard_categorical(
cards::ADSL, by = SEX, variables = AGEGR1), 1), dplyr::slice(cards::ard_categorical(
cards::ADSL, variables = AGEGR1), 1)), by = c("ARM", "SEX"), fill_overall = "total")
Output
# A tibble: 3 x 8
ARM SEX AGEGR1 context stat_variable stat_name stat_label stat
<chr> <chr> <chr> <chr> <chr> <chr> <chr> <int>
1 Placebo F 65-80 categorical AGEGR1 n n 22
2 total F 65-80 categorical AGEGR1 n n 78
3 total total 65-80 categorical AGEGR1 n n 144
Code
shuffle_card(cards::bind_ard(dplyr::slice(cards::ard_categorical(cards::ADSL,
by = c(ARM, SEX), variables = AGEGR1), 1), dplyr::slice(cards::ard_categorical(
cards::ADSL, by = SEX, variables = AGEGR1), 1), dplyr::slice(cards::ard_categorical(
cards::ADSL, variables = AGEGR1), 1)), by = c("ARM", "SEX"), fill_overall = NA)
Output
# A tibble: 3 x 8
ARM SEX AGEGR1 context stat_variable stat_name stat_label stat
<chr> <chr> <chr> <chr> <chr> <chr> <chr> <int>
1 Placebo F 65-80 categorical AGEGR1 n n 22
2 <NA> F 65-80 categorical AGEGR1 n n 78
3 <NA> <NA> 65-80 categorical AGEGR1 n n 144
Code
shuffle_card(cards::bind_ard(cards::ard_continuous(adsl_new, variables = "AGE",
statistic = ~ cards::continuous_summary_fns("mean")), cards::ard_continuous(
adsl_new, by = "ARM", variables = "AGE", statistic = ~ cards::continuous_summary_fns(
"mean"))), by = "ARM")
Message
i "Overall ARM" already exists in the `ARM` column. Using "Overall ARM.1".
Output
# A tibble: 4 x 7
ARM AGE context stat_variable stat_name stat_label stat
<chr> <chr> <chr> <chr> <chr> <chr> <dbl>
1 Overall ARM.1 Overall~ contin~ AGE mean Mean 75.1
2 Overall ARM Overall~ contin~ AGE mean Mean 75.2
3 Xanomeline High Dose Overall~ contin~ AGE mean Mean 74.4
4 Xanomeline Low Dose Overall~ contin~ AGE mean Mean 75.7
shuffle_card fills missing group levels if the group is meaningful for cardx output
Code
as.data.frame(shuffle_card(ard_cardx))
Output
ARM SEX AGEGR1 context stat_variable
1 Overall ARM <NA> Overall AGEGR1 stats_chisq_test AGEGR1
2 Overall ARM <NA> Overall AGEGR1 stats_chisq_test AGEGR1
3 <NA> Overall SEX Overall AGEGR1 stats_chisq_test AGEGR1
4 <NA> Overall SEX Overall AGEGR1 stats_chisq_test AGEGR1
stat_name stat_label stat
1 statistic X-squared Statistic 5.07944167
2 p.value p-value 0.07888842
3 statistic X-squared Statistic 1.03944200
4 p.value p-value 0.59468644
shuffle_card() messages about 'Overall ' or 'Any '
Code
dplyr::mutate(test_data, dplyr::across(ARM:TRTA, ~ .derive_overall_labels(.x,
fill_overall = "Overall {colname}", fill_hierarchical_overall = "Any {colname}")))
Message
i "Overall ARM" already exists in the `ARM` column. Using "Overall ARM.1".
Output
# A tibble: 5 x 2
ARM TRTA
<chr> <chr>
1 Overall ARM.1 <NA>
2 Overall ARM <NA>
3 <NA> Any TRTA
4 BB C
5 <NA> C
Code
shuffled_ard <- shuffle_card(ard)
Message
i "Overall TRTA" already exists in the `TRTA` column. Using "Overall TRTA.1".
i "Any AESOC" already exists in the `AESOC` column. Using"Any AESOC.1".
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tfrmt documentation built on Nov. 5, 2025, 6:12 p.m.
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shuffle/trim works
Code
ard_simple_shuffled
Output
ARM AGE context stat_variable stat_name
1 Placebo Overall AGE continuous AGE N
2 Placebo Overall AGE continuous AGE mean
3 Placebo Overall AGE continuous AGE sd
4 Placebo Overall AGE continuous AGE median
5 Placebo Overall AGE continuous AGE p25
6 Placebo Overall AGE continuous AGE p75
7 Placebo Overall AGE continuous AGE min
8 Placebo Overall AGE continuous AGE max
9 Xanomeline High Dose Overall AGE continuous AGE N
10 Xanomeline High Dose Overall AGE continuous AGE mean
11 Xanomeline High Dose Overall AGE continuous AGE sd
12 Xanomeline High Dose Overall AGE continuous AGE median
13 Xanomeline High Dose Overall AGE continuous AGE p25
14 Xanomeline High Dose Overall AGE continuous AGE p75
15 Xanomeline High Dose Overall AGE continuous AGE min
16 Xanomeline High Dose Overall AGE continuous AGE max
17 Xanomeline Low Dose Overall AGE continuous AGE N
18 Xanomeline Low Dose Overall AGE continuous AGE mean
19 Xanomeline Low Dose Overall AGE continuous AGE sd
20 Xanomeline Low Dose Overall AGE continuous AGE median
21 Xanomeline Low Dose Overall AGE continuous AGE p25
22 Xanomeline Low Dose Overall AGE continuous AGE p75
23 Xanomeline Low Dose Overall AGE continuous AGE min
24 Xanomeline Low Dose Overall AGE continuous AGE max
stat_label stat fmt_fun warning error
1 N 86.000000 0 NULL NULL
2 Mean 75.209302 1 NULL NULL
3 SD 8.590167 1 NULL NULL
4 Median 76.000000 1 NULL NULL
5 Q1 69.000000 1 NULL NULL
6 Q3 82.000000 1 NULL NULL
7 Min 52.000000 1 NULL NULL
8 Max 89.000000 1 NULL NULL
9 N 84.000000 0 NULL NULL
10 Mean 74.380952 1 NULL NULL
11 SD 7.886094 1 NULL NULL
12 Median 76.000000 1 NULL NULL
13 Q1 70.500000 1 NULL NULL
14 Q3 80.000000 1 NULL NULL
15 Min 56.000000 1 NULL NULL
16 Max 88.000000 1 NULL NULL
17 N 84.000000 0 NULL NULL
18 Mean 75.666667 1 NULL NULL
19 SD 8.286051 1 NULL NULL
20 Median 77.500000 1 NULL NULL
21 Q1 71.000000 1 NULL NULL
22 Q3 82.000000 1 NULL NULL
23 Min 51.000000 1 NULL NULL
24 Max 88.000000 1 NULL NULL
Code
ard_shuffled[1:5, ]
Output
ARM AGE AGEGR1 context stat_variable stat_name
1 Placebo <NA> <NA> categorical ARM n
2 Placebo <NA> <NA> categorical ARM N
3 Placebo <NA> <NA> categorical ARM p
4 Xanomeline High Dose <NA> <NA> categorical ARM n
5 Xanomeline High Dose <NA> <NA> categorical ARM N
stat_label stat
1 n 86.0000000
2 N 254.0000000
3 % 0.3385827
4 n 84.0000000
5 N 254.0000000
Code
ard_shuff_trim[1:5, ]
Output
ARM AGE AGEGR1 context stat_variable stat_name
1 Placebo <NA> <NA> categorical ARM n
2 Placebo <NA> <NA> categorical ARM N
3 Placebo <NA> <NA> categorical ARM p
4 Xanomeline High Dose <NA> <NA> categorical ARM n
5 Xanomeline High Dose <NA> <NA> categorical ARM N
stat_label stat
1 n 86.0000000
2 N 254.0000000
3 % 0.3385827
4 n 84.0000000
5 N 254.0000000
shuffle_card notifies user about warnings/errors before dropping
Code
shuffle_card(cards::ard_continuous(cards::ADSL, variables = AGEGR1))
Message
"warning" column contains messages that will be removed.
Output
# A tibble: 8 x 6
AGEGR1 context stat_variable stat_name stat_label stat
<chr> <chr> <chr> <chr> <chr> <chr>
1 Overall AGEGR1 continuous AGEGR1 N N 254
2 Overall AGEGR1 continuous AGEGR1 mean Mean <NA>
3 Overall AGEGR1 continuous AGEGR1 sd SD <NA>
4 Overall AGEGR1 continuous AGEGR1 median Median <NA>
5 Overall AGEGR1 continuous AGEGR1 p25 Q1 65-80
6 Overall AGEGR1 continuous AGEGR1 p75 Q3 >80
7 Overall AGEGR1 continuous AGEGR1 min Min 65-80
8 Overall AGEGR1 continuous AGEGR1 max Max >80
shuffle_card fills missing group levels if the group is meaningful
Code
shuffle_card(dplyr::filter(cards::bind_ard(cards::ard_continuous(cards::ADSL,
by = "ARM", variables = "AGE", statistic = ~ cards::continuous_summary_fns(
"mean")), dplyr::tibble(group1 = "ARM", variable = "AGE", stat_name = "p",
stat_label = "p", stat = list(0.05))), dplyr::row_number() <= 5L))
Output
# A tibble: 4 x 7
ARM AGE context stat_variable stat_name stat_label stat
<chr> <chr> <chr> <chr> <chr> <chr> <dbl>
1 Placebo Overall~ contin~ AGE mean Mean 75.2
2 Xanomeline High Dose Overall~ contin~ AGE mean Mean 74.4
3 Xanomeline Low Dose Overall~ contin~ AGE mean Mean 75.7
4 Overall ARM Overall~ <NA> AGE p p 0.05
Code
shuffle_card(dplyr::filter(cards::bind_ard(cards::ard_continuous(cards::ADSL,
variables = "AGE", statistic = ~ cards::continuous_summary_fns("mean")), dplyr::tibble(
group1 = "ARM", variable = "AGE", stat_name = "p", stat_label = "p", stat = list(
0.05))), dplyr::row_number() <= 5L))
Output
# A tibble: 2 x 7
ARM AGE context stat_variable stat_name stat_label stat
<chr> <chr> <chr> <chr> <chr> <chr> <dbl>
1 <NA> Overall AGE continuous AGE mean Mean 75.1
2 Overall ARM Overall AGE <NA> AGE p p 0.05
Code
as.data.frame(shuffle_card(cards::bind_ard(dplyr::slice(cards::ard_categorical(
cards::ADSL, by = ARM, variables = AGEGR1), 1), dplyr::slice(cards::ard_categorical(
cards::ADSL, variables = AGEGR1), 1), dplyr::slice(cards::ard_continuous(
cards::ADSL, by = SEX, variables = AGE), 1), dplyr::slice(cards::ard_continuous(
cards::ADSL, variables = AGE), 1)), by = c("ARM", "SEX")))
Output
ARM SEX AGEGR1 AGE context stat_variable
1 Placebo <NA> 65-80 <NA> categorical AGEGR1
2 Overall ARM <NA> 65-80 <NA> categorical AGEGR1
3 <NA> Overall SEX <NA> Overall AGE continuous AGE
4 <NA> F <NA> Overall AGE continuous AGE
stat_name stat_label stat
1 n n 42
2 n n 144
3 N N 254
4 N N 143
Code
as.data.frame(shuffle_card(cards::bind_ard(dplyr::slice(cards::ard_categorical(
cards::ADSL, by = ARM, variables = AGEGR1), 1), dplyr::slice(cards::ard_categorical(
cards::ADSL, variables = AGEGR1), 1), dplyr::slice(cards::ard_continuous(
cards::ADSL, by = SEX, variables = AGE), 1), dplyr::slice(cards::ard_continuous(
cards::ADSL, variables = AGE), 1)), by = c("ARM", "SEX"), fill_overall = "{colname}"))
Output
ARM SEX AGEGR1 AGE context stat_variable stat_name stat_label stat
1 Placebo <NA> 65-80 <NA> categorical AGEGR1 n n 42
2 ARM <NA> 65-80 <NA> categorical AGEGR1 n n 144
3 <NA> SEX <NA> AGE continuous AGE N N 254
4 <NA> F <NA> AGE continuous AGE N N 143
Code
shuffle_card(cards::bind_ard(dplyr::slice(cards::ard_categorical(cards::ADSL,
by = c(ARM, SEX), variables = AGEGR1), 1), dplyr::slice(cards::ard_categorical(
cards::ADSL, by = SEX, variables = AGEGR1), 1), dplyr::slice(cards::ard_categorical(
cards::ADSL, variables = AGEGR1), 1)), by = c("ARM", "SEX"))
Output
# A tibble: 3 x 8
ARM SEX AGEGR1 context stat_variable stat_name stat_label stat
<chr> <chr> <chr> <chr> <chr> <chr> <chr> <int>
1 Placebo F 65-80 catego~ AGEGR1 n n 22
2 Overall ARM F 65-80 catego~ AGEGR1 n n 78
3 Overall ARM Overall S~ 65-80 catego~ AGEGR1 n n 144
Code
shuffle_card(cards::bind_ard(dplyr::slice(cards::ard_categorical(cards::ADSL,
by = c(ARM, SEX), variables = AGEGR1), 1), dplyr::slice(cards::ard_categorical(
cards::ADSL, by = SEX, variables = AGEGR1), 1), dplyr::slice(cards::ard_categorical(
cards::ADSL, variables = AGEGR1), 1)), by = c("ARM", "SEX"), fill_overall = "total")
Output
# A tibble: 3 x 8
ARM SEX AGEGR1 context stat_variable stat_name stat_label stat
<chr> <chr> <chr> <chr> <chr> <chr> <chr> <int>
1 Placebo F 65-80 categorical AGEGR1 n n 22
2 total F 65-80 categorical AGEGR1 n n 78
3 total total 65-80 categorical AGEGR1 n n 144
Code
shuffle_card(cards::bind_ard(dplyr::slice(cards::ard_categorical(cards::ADSL,
by = c(ARM, SEX), variables = AGEGR1), 1), dplyr::slice(cards::ard_categorical(
cards::ADSL, by = SEX, variables = AGEGR1), 1), dplyr::slice(cards::ard_categorical(
cards::ADSL, variables = AGEGR1), 1)), by = c("ARM", "SEX"), fill_overall = NA)
Output
# A tibble: 3 x 8
ARM SEX AGEGR1 context stat_variable stat_name stat_label stat
<chr> <chr> <chr> <chr> <chr> <chr> <chr> <int>
1 Placebo F 65-80 categorical AGEGR1 n n 22
2 <NA> F 65-80 categorical AGEGR1 n n 78
3 <NA> <NA> 65-80 categorical AGEGR1 n n 144
Code
shuffle_card(cards::bind_ard(cards::ard_continuous(adsl_new, variables = "AGE",
statistic = ~ cards::continuous_summary_fns("mean")), cards::ard_continuous(
adsl_new, by = "ARM", variables = "AGE", statistic = ~ cards::continuous_summary_fns(
"mean"))), by = "ARM")
Message
i "Overall ARM" already exists in the `ARM` column. Using "Overall ARM.1".
Output
# A tibble: 4 x 7
ARM AGE context stat_variable stat_name stat_label stat
<chr> <chr> <chr> <chr> <chr> <chr> <dbl>
1 Overall ARM.1 Overall~ contin~ AGE mean Mean 75.1
2 Overall ARM Overall~ contin~ AGE mean Mean 75.2
3 Xanomeline High Dose Overall~ contin~ AGE mean Mean 74.4
4 Xanomeline Low Dose Overall~ contin~ AGE mean Mean 75.7
shuffle_card fills missing group levels if the group is meaningful for cardx output
Code
as.data.frame(shuffle_card(ard_cardx))
Output
ARM SEX AGEGR1 context stat_variable
1 Overall ARM <NA> Overall AGEGR1 stats_chisq_test AGEGR1
2 Overall ARM <NA> Overall AGEGR1 stats_chisq_test AGEGR1
3 <NA> Overall SEX Overall AGEGR1 stats_chisq_test AGEGR1
4 <NA> Overall SEX Overall AGEGR1 stats_chisq_test AGEGR1
stat_name stat_label stat
1 statistic X-squared Statistic 5.07944167
2 p.value p-value 0.07888842
3 statistic X-squared Statistic 1.03944200
4 p.value p-value 0.59468644
shuffle_card() messages about 'Overall ' or 'Any '
Code
dplyr::mutate(test_data, dplyr::across(ARM:TRTA, ~ .derive_overall_labels(.x,
fill_overall = "Overall {colname}", fill_hierarchical_overall = "Any {colname}")))
Message
i "Overall ARM" already exists in the `ARM` column. Using "Overall ARM.1".
Output
# A tibble: 5 x 2
ARM TRTA
<chr> <chr>
1 Overall ARM.1 <NA>
2 Overall ARM <NA>
3 <NA> Any TRTA
4 BB C
5 <NA> C
Code
shuffled_ard <- shuffle_card(ard)
Message
i "Overall TRTA" already exists in the `TRTA` column. Using "Overall TRTA.1".
i "Any AESOC" already exists in the `AESOC` column. Using"Any AESOC.1".
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