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The same demographics summary as cdisc_saf_demo, but in the long Analysis Results Data (ARD) format produced by cards::ard_stack(). One row per (treatment arm, variable, statistic). Shipped as a teaching dataset that shows the upstream shape users typically have when they start from cards. Convert it to the wide form tabular() accepts via pivot_across() — tabular itself does not consume the long ARD format, since pre-summarised wide data is the package boundary.

Usage

cdisc_saf_demo_ard

Format

A card-classed tibble with columns group1, group1_level, variable, variable_level, context, stat_name, stat_label, stat. group1 == "TRT01A" and group1_level carries the original pharmaverseadam arm labels ("Placebo", "Xanomeline Low Dose", "Xanomeline High Dose"). cards::ard_stack(.overall = TRUE) adds overall rows with group1_level = NA; pivot_across() renders those into a Total column.

Source

Derived in data-raw/bundle-demo.R via cards::ard_stack(.by = "TRT01A", .overall = TRUE) over pharmaverseadam::adsl.

Details

Continuous variables: AGE, WEIGHT, HEIGHT, BMI (each emitting N, mean, sd, median, p25, p75, min, max). Categorical variables: AGEGR1, SEX, RACE, ETHNIC, BMI_CAT (each emitting n, N, p).

This is the package's canonical flat ARD demo. Its hierarchical counterpart is cdisc_saf_aesocpt_ard; together they cover both shapes pivot_across() must handle.

See also

pivot_across() for the long-to-wide bridge; cdisc_saf_demo for the wide companion.

Examples

# 95% demographics pattern: cards ARD -> wide -> rendered table.
n <- stats::setNames(cdisc_saf_n$n, cdisc_saf_n$arm_short)
cdisc_saf_demo_ard |>
  pivot_across(
    statistic = list(
      continuous  = "{mean} ({sd})",
      categorical = "{n} ({p}%)"
    ),
    label = c(AGE = "Age (years)", SEX = "Sex", RACE = "Race")
  ) |>
  tabular(
    titles = c(
      "Table 14.1.1",
      "Demographics",
      "Safety Population"
    )
  )

 

Table 14.1.1

Demographics

Safety Population

 

variablestat_labelPlaceboXanomeline High DoseXanomeline Low DoseTotal
Age (years)AGE75.2 (8.59)73.8 (7.94)76.0 (8.11)75.1 (8.25)
WEIGHTWEIGHT62.8 (12.77)69.5 (14.35)68.0 (14.50)66.6 (14.13)
HEIGHTHEIGHT162.6 (11.52)165.9 (10.28)163.7 (10.30)163.9 (10.76)
BMIBMI23.6 (3.67)25.2 (3.97)25.2 (4.40)24.7 (4.09)
AGEGR1  18-6414 (16%)11 (15%)8 (8%)33 (13%)
AGEGR1  >6472 (84%)61 (85%)88 (92%)221 (87%)
Sex  F53 (62%)35 (49%)55 (57%)143 (56%)
Sex  M33 (38%)37 (51%)41 (43%)111 (44%)
Race  WHITE78 (91%)62 (86%)90 (94%)230 (91%)
Race  BLACK OR AFRICAN AMERICAN8 (9%)9 (12%)6 (6%)23 (9%)
Race  ASIAN0000
Race  AMERICAN INDIAN OR ALASKA NATIVE01 (1%)01 (0%)
ETHNIC  HISPANIC OR LATINO3 (3%)3 (4%)6 (6%)12 (5%)
ETHNIC  NOT HISPANIC OR LATINO83 (97%)69 (96%)90 (94%)242 (95%)
ETHNIC  NOT REPORTED0000
BMI_CAT  Underweight (<18.5)3 (3%)1 (1%)4 (4%)8 (3%)
BMI_CAT  Normal (18.5-24.9)57 (66%)39 (54%)46 (48%)142 (56%)
BMI_CAT  Overweight (25-29.9)20 (23%)23 (32%)32 (34%)75 (30%)
BMI_CAT  Obese (>=30)6 (7%)9 (12%)13 (14%)28 (11%)