tests/testthat/_snaps/tbl_ard_summary.md

In ddsjoberg/gtsummary: Presentation-Ready Data Summary and Analytic Result Tables

tbl_ard_summary() works

Code
  as.data.frame(tbl_ard_summary(cards::ard_stack(data = cards::ADSL, .by = ARM,
  cards::ard_categorical(variables = "AGEGR1"), cards::ard_continuous(variables = "AGE"),
  .attributes = TRUE, .missing = TRUE), by = ARM))
Output
    **Characteristic**       **Placebo** **Xanomeline High Dose**
  1 Pooled Age Group 1              <NA>                     <NA>
  2              65-80        42 (48.8%)               55 (65.5%)
  3                <65        14 (16.3%)               11 (13.1%)
  4                >80        30 (34.9%)               18 (21.4%)
  5                Age 76.0 (69.0, 82.0)        76.0 (70.5, 80.0)
    **Xanomeline Low Dose**
  1                    <NA>
  2              47 (56.0%)
  3                8 (9.5%)
  4              29 (34.5%)
  5       77.5 (71.0, 82.0)

Code
  as.data.frame(tbl_ard_summary(cards::ard_stack(data = cards::ADSL, cards::ard_categorical(
    variables = "AGEGR1"), cards::ard_continuous(variables = "AGE"), .attributes = TRUE,
  .missing = TRUE, .total_n = TRUE)))
Output
    **Characteristic**       **Overall**
  1 Pooled Age Group 1              <NA>
  2              65-80       144 (56.7%)
  3                <65        33 (13.0%)
  4                >80        77 (30.3%)
  5                Age 77.0 (70.0, 81.0)

tbl_ard_summary(cards)

Code
  as.data.frame(tbl_ard_summary(cards::ard_stack(data = cards::ADSL, .by = ARM,
  cards::ard_continuous(variables = "AGE"), .attributes = FALSE, .missing = FALSE),
  by = ARM, missing = "no"))
Output
    **Characteristic**       **Placebo** **Xanomeline High Dose**
  1                AGE 76.0 (69.0, 82.0)        76.0 (70.5, 80.0)
    **Xanomeline Low Dose**
  1       77.5 (71.0, 82.0)

Code
  as.data.frame(tbl_ard_summary(cards::ard_continuous(trial, by = trt, variables = age),
  by = trt))
Output
    **Characteristic**        **Drug A**        **Drug B**
  1                age 46.0 (37.0, 60.0) 48.0 (39.0, 56.0)

tbl_ard_summary(cards) error messages

Code
  tbl_ard_summary(cards::ard_stack(data = cards::ADSL, .by = c(ARM, AGEGR1),
  cards::ard_continuous(variables = "AGE"), .attributes = TRUE, .missing = TRUE),
  by = ARM)
Condition
  Error in `tbl_ard_summary()`:
  ! The `cards` object may only contain a single stratifying variable.
  i But contains "group2" and "group2_level".

Code
  tbl_ard_summary(cards::ard_stack(data = cards::ADSL, .by = ARM, cards::ard_continuous(
    variables = "AGE"), .attributes = FALSE, .missing = FALSE), by = ARM,
  missing = "ifany")
Condition
  Error in `FUN()`:
  ! Argument `missing = "ifany"` requires results from `cards::ard_missing()`, but they are missing for variable "AGE".
  i Set `missing = "no"` to avoid printing missing counts.

tbl_ard_summary(by) messaging

Code
  tbl_ard_summary(cards::bind_ard(cards::ard_continuous(trial, by = trt,
    variables = age), cards::ard_continuous(trial, by = grade, variables = age)),
  by = trt)
Condition
  Error in `tbl_ard_summary()`:
  ! For `by = "trt"`, columns "group1" and "group1_level" must be present in `cards` and "group1" must be equal to "trt".

Code
  tbl_ard_summary(cards::ard_stack(data = cards::ADSL, .by = ARM, cards::ard_continuous(
    variables = "AGE"), .attributes = TRUE, .missing = TRUE))
Condition
  Error in `tbl_ard_summary()`:
  ! The `cards` object may not have group columns when the `by` is empty.

tbl_ard_summary(statistic) argument works

Code
  as.data.frame(tbl_ard_summary(ard, statistic = list(all_continuous() ~
    "{median}", all_categorical() ~ "{n} / {N} (Total {N_obs})")))
Output
    **Characteristic**           **Overall**
  1 Pooled Age Group 1                  <NA>
  2              65-80 144 / 254 (Total 254)
  3                <65  33 / 254 (Total 254)
  4                >80  77 / 254 (Total 254)
  5                Age                  77.0

Code
  as.data.frame(tbl_ard_summary(ard, type = list(all_continuous() ~ "continuous2"),
  statistic = list(all_continuous() ~ c("{median}", "{mean}"))))
Output
    **Characteristic** **Overall**
  1 Pooled Age Group 1        <NA>
  2              65-80 144 (56.7%)
  3                <65  33 (13.0%)
  4                >80  77 (30.3%)
  5                Age        <NA>
  6             Median        77.0
  7               Mean        75.1

tbl_ard_summary(type) error messages

Code
  tbl_ard_summary(cards::ard_stack(data = cards::ADSL, .by = ARM, cards::ard_continuous(
    variables = "AGE"), .attributes = TRUE, .missing = TRUE), by = ARM, type = list(
    AGE = "categorical"))
Condition
  Error in `tbl_ard_summary()`:
  ! Summary type for variable "AGE" must be one of "continuous" and "continuous2", not "categorical".
  i If your variable has "variable_level" values, you may need `type = list("AGE"="dichotomous")`.

Code
  tbl_ard_summary(cards::ard_stack(data = cards::ADSL, .by = ARM, cards::ard_categorical(
    variables = "AGEGR1"), .attributes = TRUE, .missing = TRUE), by = ARM, type = list(
    AGEGR1 = "continuous"))
Condition
  Error in `tbl_ard_summary()`:
  ! Summary type for variable "AGEGR1" must be "categorical", not "continuous".

tbl_ard_summary(statistic) error messages

Code
  tbl_ard_summary(cards::ard_stack(data = cards::ADSL, .by = ARM, cards::ard_continuous(
    variables = "AGE"), .attributes = TRUE, .missing = TRUE), by = ARM,
  statistic = list(AGE = "{not_a_valid_summary_statistic}"))
Condition
  Error in `tbl_ard_summary()`:
  ! Statistic "not_a_valid_summary_statistic" is not available for variable "AGE".
  i Select among "N", "mean", "sd", "median", "p25", "p75", "min", "max", "N_obs", "N_miss", "N_nonmiss", "p_miss", and "p_nonmiss".

Code
  tbl_ard_summary(cards::ard_stack(data = cards::ADSL, .by = ARM, cards::ard_continuous(
    variables = "AGE"), .attributes = TRUE, .missing = TRUE), by = ARM,
  statistic = list(AGE = c("{mean}", "{median}")))
Condition
  Error in `tbl_ard_summary()`:
  ! Variable "AGE" is type `continuous` and `statistic` argument value must be a string of length one.

tbl_ard_summary() non-standard ARDs (ie not 'continuous', 'categorical', etc)

Code
  as.data.frame(tbl_ard_summary(ard, by = trt, statistic = ~"{estimate}"))
Output
    **Characteristic** **Drug A** **Drug B**
  1               time       <NA>       <NA>
  2                 12       90.8       86.3
  3                 24       46.9       41.2
  4                age       47.0       47.4

ddsjoberg/gtsummary documentation built on March 1, 2025, 7:52 p.m.