tests/testthat/_snaps/ard_categorical.md

In cards: Analysis Results Data

ard_categorical() univariate

Code
  class(ard_cat_uni)
Output
  [1] "card"       "tbl_df"     "tbl"        "data.frame"

ard_categorical() univariate & specified denomiator

Code
  class(ard_cat_new_denom)
Output
  [1] "card"       "tbl_df"     "tbl"        "data.frame"

ard_continuous(fmt_fn) argument works

Code
  as.data.frame(dplyr::select(apply_fmt_fn(ard_categorical(mtcars, variables = "am",
    fmt_fn = list(am = list(p = function(x) as.character(round5(x * 100, digits = 3)),
    N = function(x) format(round5(x, digits = 2), nsmall = 2), N_obs = function(x)
      format(round5(x, digits = 2), nsmall = 2))))), variable, variable_level,
  stat_name, stat, stat_fmt))
Output
    variable variable_level stat_name    stat stat_fmt
  1       am              0         n      19       19
  2       am              0         N      32    32.00
  3       am              0         p 0.59375   59.375
  4       am              1         n      13       13
  5       am              1         N      32    32.00
  6       am              1         p 0.40625   40.625

Code
  as.data.frame(dplyr::select(apply_fmt_fn(ard_categorical(mtcars, variables = c(
    "am", "vs"), fmt_fn = list(am = list(p = function(x) round5(x * 100, digits = 3)),
  vs = list(p = function(x) round5(x * 100, digits = 1))))), variable,
  variable_level, stat_name, stat, stat_fmt))
Output
     variable variable_level stat_name    stat stat_fmt
  1        am              0         n      19       19
  2        am              0         N      32       32
  3        am              0         p 0.59375   59.375
  4        am              1         n      13       13
  5        am              1         N      32       32
  6        am              1         p 0.40625   40.625
  7        vs              0         n      18       18
  8        vs              0         N      32       32
  9        vs              0         p  0.5625     56.3
  10       vs              1         n      14       14
  11       vs              1         N      32       32
  12       vs              1         p  0.4375     43.8

ard_categorical() with strata and by arguments

Code
  ard_categorical(ADSL, by = "ARM", variables = "AGEGR1", denominator = dplyr::filter(
    ADSL, ARM %in% "Placebo"))
Condition
  Error in `ard_categorical()`:
  ! The following `by/strata` combinations are missing from the `denominator` data frame: ARM (Xanomeline High Dose) and ARM (Xanomeline Low Dose).

ard_categorical(stat_label) argument works

Code
  unique(dplyr::select(dplyr::filter(as.data.frame(ard_categorical(data = ADSL,
    by = "ARM", variables = c("AGEGR1", "SEX"), stat_label = everything() ~ list(
      c("n", "p") ~ "n (pct)"))), stat_name %in% c("n", "p")), stat_name,
  stat_label))
Output
    stat_name stat_label
  1         n    n (pct)
  2         p    n (pct)

Code
  unique(dplyr::select(dplyr::filter(as.data.frame(ard_categorical(data = ADSL,
    by = "ARM", variables = c("AGEGR1", "SEX"), stat_label = everything() ~ list(
      n = "num", p = "pct"))), stat_name %in% c("n", "p")), stat_name, stat_label))
Output
    stat_name stat_label
  1         n        num
  2         p        pct

Code
  unique(dplyr::select(dplyr::filter(as.data.frame(ard_categorical(data = ADSL,
    by = "ARM", variables = c("AGEGR1", "SEX"), stat_label = AGEGR1 ~ list(c("n",
      "p") ~ "n (pct)"))), stat_name %in% c("n", "p")), variable, stat_name,
  stat_label))
Output
     variable stat_name stat_label
  1    AGEGR1         n    n (pct)
  2    AGEGR1         p    n (pct)
  19      SEX         n          n
  20      SEX         p          %

ard_categorical(denominator='row') works

Code
  as.data.frame(dplyr::select(apply_fmt_fn(ard_with_args), -fmt_fn, -warning,
  -error))
Output
     group1         group1_level variable variable_level     context stat_name
  1     ARM              Placebo   AGEGR1          65-80 categorical         n
  2     ARM              Placebo   AGEGR1          65-80 categorical         N
  3     ARM Xanomeline High Dose   AGEGR1          65-80 categorical         n
  4     ARM Xanomeline High Dose   AGEGR1          65-80 categorical         N
  5     ARM  Xanomeline Low Dose   AGEGR1          65-80 categorical         n
  6     ARM  Xanomeline Low Dose   AGEGR1          65-80 categorical         N
  7     ARM              Placebo   AGEGR1            <65 categorical         n
  8     ARM              Placebo   AGEGR1            <65 categorical         N
  9     ARM Xanomeline High Dose   AGEGR1            <65 categorical         n
  10    ARM Xanomeline High Dose   AGEGR1            <65 categorical         N
  11    ARM  Xanomeline Low Dose   AGEGR1            <65 categorical         n
  12    ARM  Xanomeline Low Dose   AGEGR1            <65 categorical         N
  13    ARM              Placebo   AGEGR1            >80 categorical         n
  14    ARM              Placebo   AGEGR1            >80 categorical         N
  15    ARM Xanomeline High Dose   AGEGR1            >80 categorical         n
  16    ARM Xanomeline High Dose   AGEGR1            >80 categorical         N
  17    ARM  Xanomeline Low Dose   AGEGR1            >80 categorical         n
  18    ARM  Xanomeline Low Dose   AGEGR1            >80 categorical         N
     stat_label stat stat_fmt
  1           n   42    42.00
  2           N  144      144
  3           n   55    55.00
  4           N  144      144
  5           n   47    47.00
  6           N  144      144
  7           n   14    14.00
  8           N   33       33
  9           n   11    11.00
  10          N   33       33
  11          n    8     8.00
  12          N   33       33
  13          n   30    30.00
  14          N   77       77
  15          n   18    18.00
  16          N   77       77
  17          n   29    29.00
  18          N   77       77

ard_categorical(denominator=) works

Code
  ard_categorical(ADSL, by = ARM, variables = AGEGR1, denominator = data.frame(
    ARM = c("Placebo", "Placebo", "Xanomeline High Dose", "Xanomeline Low Dose"),
    ...ard_N... = c(86, 86, 84, 84)))
Condition
  Error in `ard_categorical()`:
  ! Specified counts in column "'...ard_N...'" are not unique in the `denominator` argument across the `by` and `strata` columns.

Code
  ard_categorical(ADSL, by = ARM, variables = AGEGR1, denominator = data.frame(
    ARM = "Placebo", ...ard_N... = 86))
Condition
  Error in `ard_categorical()`:
  ! The following `by/strata` combinations are missing from the `denominator` data frame: ARM (Xanomeline High Dose) and ARM (Xanomeline Low Dose).

ard_categorical() and all NA columns

Code
  ard_categorical(dplyr::mutate(ADSL, AGEGR1 = NA_character_), variables = AGEGR1)
Condition
  Error in `ard_categorical()`:
  ! Column "AGEGR1" is all missing and cannot by tabulated.
  i Only columns of class <logical> and <factor> can be tabulated when all values are missing.

ard_categorical(by) messages about protected names

Code
  ard_categorical(mtcars2, by = variable, variables = gear)
Condition
  Error in `ard_categorical()`:
  ! The `by` argument cannot include variables named "variable" and "variable_level".

Code
  ard_categorical(mtcars2, by = variable, variables = by)
Condition
  Error in `ard_categorical()`:
  ! The `by` argument cannot include variables named "variable" and "variable_level".

ard_categorical() errors with incomplete factor columns

Code
  ard_categorical(dplyr::mutate(mtcars, am = factor(am, levels = character(0))),
  variables = am)
Condition
  Error in `ard_categorical()`:
  ! Factors with empty "levels" attribute are not allowed, which was identified in column "am".

Code
  ard_categorical(dplyr::mutate(mtcars, am = factor(am, levels = c(0, 1, NA),
  exclude = NULL)), variables = am)
Condition
  Error in `ard_categorical()`:
  ! Factors with NA levels are not allowed, which are present in column "am".

cards documentation built on Oct. 4, 2024, 1:09 a.m.