tbl_baseline_chg.md
In crane: Supplements the 'gtsummary' Package for Pharmaceutical Reporting

tbl_baseline_chg() works

Code
  as.data.frame(tbl)[1:25, 1:5]
Output
         Visit  Value at Visit Change from Baseline Value at Visit.1 Change from Baseline.1
  1   Baseline            <NA>                 <NA>             <NA>                   <NA>
  2          n               7                 <NA>                7                   <NA>
  3  Mean (SD)   141.14 (1.46)                 <NA>    139.14 (2.19)                   <NA>
  4     Median          141.00                 <NA>           139.00                   <NA>
  5  Min - Max 140.00 - 144.00                 <NA>  136.00 - 142.00                   <NA>
  6     Week 2            <NA>                 <NA>             <NA>                   <NA>
  7          n               7                    7                6                      6
  8  Mean (SD)   140.57 (1.62)           -0.6 (1.9)    138.83 (3.25)              0.2 (3.5)
  9     Median          141.00                 -1.0           140.50                    0.5
  10 Min - Max 138.00 - 142.00           -3.0 - 2.0  133.00 - 141.00             -5.0 - 5.0
  11    Week 4            <NA>                 <NA>             <NA>                   <NA>
  12         n               7                    7                6                      6
  13 Mean (SD)   139.29 (2.81)         -1.86 (2.54)    139.83 (3.54)            1.17 (2.04)
  14    Median          140.00                -1.00           138.50                   0.00
  15 Min - Max 134.00 - 142.00         -7.00 - 0.00  138.00 - 147.00            0.00 - 5.00
  16    Week 6            <NA>                 <NA>             <NA>                   <NA>
  17         n               5                    5                6                      6
  18 Mean (SD)   140.00 (1.87)         -0.40 (1.67)    139.67 (1.97)            1.00 (2.28)
  19    Median          140.00                 0.00           139.00                   0.50
  20 Min - Max 138.00 - 143.00         -2.00 - 2.00  138.00 - 143.00           -1.00 - 5.00
  21    Week 8            <NA>                 <NA>             <NA>                   <NA>
  22         n               5                    5                4                      4
  23 Mean (SD)   140.60 (1.52)          0.20 (1.64)    139.00 (2.16)           -0.50 (2.38)
  24    Median          141.00                 1.00           139.50                  -0.50
  25 Min - Max 139.00 - 142.00         -2.00 - 2.00  136.00 - 141.00           -3.00 - 2.00

tbl_baseline_chg() works with no `by` variable

Code
  as.data.frame(tbl)[1:25, ]
Output
         Visit  Value at Visit Change from Baseline
  1   Baseline            <NA>                 <NA>
  2          n              20                 <NA>
  3  Mean (SD)   139.95 (2.78)                 <NA>
  4     Median          140.00                 <NA>
  5  Min - Max 134.00 - 145.00                 <NA>
  6     Week 2            <NA>                 <NA>
  7          n              19                   19
  8  Mean (SD)   139.68 (2.43)           -0.2 (2.9)
  9     Median          140.00                 -1.0
  10 Min - Max 133.00 - 142.00           -5.0 - 5.0
  11    Week 4            <NA>                 <NA>
  12         n              18                   18
  13 Mean (SD)   139.50 (2.64)         -0.50 (2.85)
  14    Median          139.50                 0.00
  15 Min - Max 134.00 - 147.00         -7.00 - 5.00
  16    Week 6            <NA>                 <NA>
  17         n              15                   15
  18 Mean (SD)   140.00 (2.00)          0.73 (3.10)
  19    Median          139.00                 0.00
  20 Min - Max 138.00 - 144.00         -5.00 - 7.00
  21    Week 8            <NA>                 <NA>
  22         n              12                   12
  23 Mean (SD)   139.67 (2.02)         -0.08 (2.19)
  24    Median          140.00                 1.00
  25 Min - Max 136.00 - 142.00         -4.00 - 2.00

add_overall.tbl_baseline_chg() works

Code
  as.data.frame(tbl)[1:25, c(1, 4:9)]
Output
         Visit  Value at Visit Change from Baseline Value at Visit.1 Change from Baseline.1 Value at Visit.2 Change from Baseline.2
  1   Baseline            <NA>                 <NA>             <NA>                   <NA>             <NA>                   <NA>
  2          n               7                 <NA>                6                   <NA>               20                   <NA>
  3  Mean (SD)   139.14 (2.19)                 <NA>    139.50 (4.23)                   <NA>    139.95 (2.78)                   <NA>
  4     Median          139.00                 <NA>           138.50                   <NA>           140.00                   <NA>
  5  Min - Max 136.00 - 142.00                 <NA>  134.00 - 145.00                   <NA>  134.00 - 145.00                   <NA>
  6     Week 2            <NA>                 <NA>             <NA>                   <NA>             <NA>                   <NA>
  7          n               6                    6                6                      6               19                     19
  8  Mean (SD)   138.83 (3.25)            0.2 (3.5)    139.50 (2.35)              0.0 (3.7)    139.68 (2.43)             -0.2 (2.9)
  9     Median          140.50                  0.5           139.50                   -0.5           140.00                   -1.0
  10 Min - Max 133.00 - 141.00           -5.0 - 5.0  136.00 - 142.00             -5.0 - 5.0  133.00 - 142.00             -5.0 - 5.0
  11    Week 4            <NA>                 <NA>             <NA>                   <NA>             <NA>                   <NA>
  12         n               6                    6                5                      5               18                     18
  13 Mean (SD)   139.83 (3.54)          1.17 (2.04)    139.40 (1.34)           -0.60 (3.51)    139.50 (2.64)           -0.50 (2.85)
  14    Median          138.50                 0.00           140.00                   0.00           139.50                   0.00
  15 Min - Max 138.00 - 147.00          0.00 - 5.00  138.00 - 141.00           -5.00 - 4.00  134.00 - 147.00           -7.00 - 5.00
  16    Week 6            <NA>                 <NA>             <NA>                   <NA>             <NA>                   <NA>
  17         n               6                    6                4                      4               15                     15
  18 Mean (SD)   139.67 (1.97)          1.00 (2.28)    140.50 (2.65)            1.75 (5.38)    140.00 (2.00)            0.73 (3.10)
  19    Median          139.00                 0.50           140.00                   2.50           139.00                   0.00
  20 Min - Max 138.00 - 143.00         -1.00 - 5.00  138.00 - 144.00           -5.00 - 7.00  138.00 - 144.00           -5.00 - 7.00
  21    Week 8            <NA>                 <NA>             <NA>                   <NA>             <NA>                   <NA>
  22         n               4                    4                3                      3               12                     12
  23 Mean (SD)   139.00 (2.16)         -0.50 (2.38)    139.00 (2.65)            0.00 (3.46)    139.67 (2.02)           -0.08 (2.19)
  24    Median          139.50                -0.50           140.00                   2.00           140.00                   1.00
  25 Min - Max 136.00 - 141.00         -3.00 - 2.00  136.00 - 141.00           -4.00 - 2.00  136.00 - 142.00           -4.00 - 2.00

add_overall.tbl_baseline_chg() messaging

Code
  tbl <- add_overall(tbl_baseline_chg(data = df, baseline_level = "Baseline", denominator = cards::ADSL))
Message
  Original table was not stratified, and overall columns cannot be added.
  i Table has been returned unaltered.

Code
  tbl <- add_overall(modify_table_body(tbl_baseline_chg(data = df, by = "TRTA", baseline_level = "Baseline", denominator = cards::ADSL), ~ dplyr::filter(.x, dplyr::row_number() %in% 1:5)))
Message
  ! The structures of the original table and the overall table are not identical, and the resulting table may be malformed.

tbl_baseline_chg() throws error when required arguments are missing

Code
  tbl <- tbl_baseline_chg(data = test_data, baseline_level = "Baseline",
    denominator = cards::ADSL)
Condition
  Error in `tbl_baseline_chg()`:
  ! Columns "USUBJID" and "AVISIT" do not uniquely identify the rows in `data`.
  i See row number 140.

tbl_baseline_chg() messaging

Code
  tbl <- tbl_baseline_chg(data = dplyr::mutate(df, TRTA = as.character(TRTA)), baseline_level = "Baseline", by = "TRTA", denominator = cards::ADSL)
Message
  i Converting column "TRTA" to a factor.

gather_ard() works on output table

Code
  gather_ard(tbl)
Output
  $tbl_baseline_chg
Message
  {cards} data frame: 620 x 12
Output
     group1 group1_level variable variable_level stat_name stat_label    stat
  1    TRTA      Placebo     AVAL       Baseline      mean       Mean 141.143
  2    TRTA      Placebo     AVAL       Baseline        sd         SD   1.464
  3    TRTA      Placebo     AVAL       Baseline    median     Median     141
  4    TRTA      Placebo     AVAL       Baseline       min        Min     140
  5    TRTA      Placebo     AVAL       Baseline       max        Max     144
  6    TRTA      Placebo     AVAL         Week 2      mean       Mean 140.571
  7    TRTA      Placebo     AVAL         Week 2        sd         SD   1.618
  8    TRTA      Placebo     AVAL         Week 2    median     Median     141
  9    TRTA      Placebo     AVAL         Week 2       min        Min     138
  10   TRTA      Placebo     AVAL         Week 2       max        Max     142
Message
  i 610 more rows
  i Use `print(n = ...)` to see more rows
  i 5 more variables: context, fmt_fun, warning, error, gts_column
Output

  $add_overall
Message
  {cards} data frame: 229 x 10
Output
     variable variable_level context stat_name stat_label    stat
  1      AVAL       Baseline summary      mean       Mean  139.95
  2      AVAL       Baseline summary        sd         SD   2.781
  3      AVAL       Baseline summary    median     Median     140
  4      AVAL       Baseline summary       min        Min     134
  5      AVAL       Baseline summary       max        Max     145
  6      AVAL         Week 2 summary      mean       Mean 139.684
  7      AVAL         Week 2 summary        sd         SD   2.428
  8      AVAL         Week 2 summary    median     Median     140
  9      AVAL         Week 2 summary       min        Min     133
  10     AVAL         Week 2 summary       max        Max     142
Message
  i 219 more rows
  i Use `print(n = ...)` to see more rows
  i 4 more variables: fmt_fun, warning, error, gts_column
Output