Bind a set of tidytlg tables together with formatting variables

bind_table combines analysis results with formatting variables (indentme, newrows, newpage) based on by variables (tablebyvar, rowbyvar), such that appropriate formatting (indentation, line break, page break) can be applied while creating the output. It can also attach the column metadata attribute, which will be automatically used in gentlg for creating output.

Usage

bind_table(
  ...,
  colvar = NULL,
  tablebyvar = NULL,
  rowbyvar = NULL,
  prefix = NULL,
  add_count = FALSE,
  add_format = TRUE,
  column_metadata_file = NULL,
  column_metadata = NULL,
  tbltype = NULL
)

Arguments

...: (required) a set of tidytlg tables to bind together
colvar: (required) treatment variable within df to use to summarize. Required if add_count is TRUE.
tablebyvar: (optional) repeat entire table by variable within df.
rowbyvar: (optional) any rowbyvar values used to create the table.
prefix: (optional) text to prefix the values of tablebyvar with.
add_count: (optional) Should a count be included in the tablebyvar? (default = TRUE)
add_format: (optional) Should format be added to the output table? This is done using the add_format function. (default = TRUE)
column_metadata_file: (optional) An excel file for column_metadata. Does not change the behavior of the function binds the column metadata for gentlg. If a column_metadata dataframe is passed in too, this is ignored.
column_metadata: (optional) A dataframe containing the column metadata. This will be used in place of column_metadata_file.
tbltype: (optional) A value used to subset the column_metadata_file.

Value

The tidytlg tables bound together reflecting the tablebyvars used.

Examples

library(magrittr)
#> 
#> Attaching package: ‘magrittr’
#> The following objects are masked from ‘package:testthat’:
#> 
#>     equals, is_less_than, not

# bind tables together
t1 <- cdisc_adsl %>%
  freq(
    colvar = "TRT01PN",
    rowvar = "ITTFL",
    statlist = statlist("n"),
    subset = ITTFL == "Y",
    rowtext = "Analysis set: ITT"
  )

t2 <- cdisc_adsl %>%
  univar(
    colvar = "TRT01PN",
    rowvar = "AGE",
    decimal = 0,
    row_header = "Age, years"
  )

bind_table(t1, t2)
#> # A tibble: 7 × 10
#>   label       `0`   `54`  `81`  row_type  anbr indentme roworder newrows newpage
#>   <chr>       <chr> <chr> <chr> <chr>    <dbl>    <dbl>    <int>   <dbl>   <dbl>
#> 1 Analysis s… "5"   "5"   "5"   HEADER       1        0        1       0       0
#> 2 Age, years  ""    ""    ""    HEADER       2        0        1       1       0
#> 3 N           "5"   "5"   "5"   N            2        1        2       0       0
#> 4 Mean (SD)   "69.… "75.… "72.… VALUE        2        2        3       0       0
#> 5 Median      "64.… "74.… "75.… VALUE        2        2        4       0       0
#> 6 Range       "(52… "(68… "(57… VALUE        2        2        5       0       0
#> 7 IQ range    "(63… "(71… "(71… VALUE        2        2        6       0       0

# bind tables together w/by groups
t1 <- cdisc_adsl %>%
  freq(
    colvar = "TRT01PN",
    rowvar = "ITTFL",
    rowbyvar = "SEX",
    statlist = statlist("n"),
    subset = ITTFL == "Y",
    rowtext = "Analysis set: ITT"
  )

t2 <- cdisc_adsl %>%
  univar(
    colvar = "TRT01PN",
    rowvar = "AGE",
    rowbyvar = "SEX",
    decimal = 0,
    row_header = "Age, years"
  )

bind_table(t1, t2, rowbyvar = "SEX")
#> # A tibble: 18 × 10
#>    label      `0`   `54`  `81`  row_type  anbr indentme roworder newrows newpage
#>    <chr>      <chr> <chr> <chr> <chr>    <dbl>    <dbl>    <int>   <dbl>   <dbl>
#>  1 F          ""    ""    ""    BY_HEAD…     1        0        1       0       0
#>  2 Analysis … "2"   "1"   "3"   VALUE        1        1        2       0       0
#>  3 M          ""    ""    ""    BY_HEAD…     1        0        1       1       0
#>  4 Analysis … "3"   "4"   "2"   VALUE        1        1        2       0       0
#>  5 F          ""    ""    ""    BY_HEAD…     2        0        1       1       0
#>  6 Age, years ""    ""    ""    HEADER       2        0        2       0       0
#>  7 N          "2"   "1"   "3"   N            2        1        3       0       0
#>  8 Mean (SD)  "74.… "81.… "77.… VALUE        2        2        4       0       0
#>  9 Median     "74.… "81.… "77.… VALUE        2        2        5       0       0
#> 10 Range      "(63… "(81… "(75… VALUE        2        2        6       0       0
#> 11 IQ range   "(63… "(81… "(75… VALUE        2        2        7       0       0
#> 12 M          ""    ""    ""    BY_HEAD…     2        0        1       1       0
#> 13 Age, years ""    ""    ""    HEADER       2        0        2       0       0
#> 14 N          "3"   "4"   "2"   N            2        1        3       0       0
#> 15 Mean (SD)  "66.… "74.… "64.… VALUE        2        2        4       0       0
#> 16 Median     "64.… "72.… "64.… VALUE        2        2        5       0       0
#> 17 Range      "(52… "(68… "(57… VALUE        2        2        6       0       0
#> 18 IQ range   "(52… "(69… "(57… VALUE        2        2        7       0       0

# bind tables together w/table by groups
t1 <- cdisc_adsl %>%
  freq(
    colvar = "TRT01PN",
    rowvar = "ITTFL",
    tablebyvar = "SEX",
    statlist = statlist("n"),
    subset = ITTFL == "Y",
    rowtext = "Analysis set: ITT"
  )

t2 <- cdisc_adsl %>%
  univar(
    colvar = "TRT01PN",
    rowvar = "AGE",
    tablebyvar = "SEX",
    decimal = 0,
    row_header = "Age, years"
  )

bind_table(t1, t2, tablebyvar = "SEX")
#> # A tibble: 16 × 10
#>    label      `0`   `54`  `81`  row_type  anbr indentme roworder newrows newpage
#>    <chr>      <chr> <chr> <chr> <chr>    <dbl>    <dbl>    <int>   <dbl>   <dbl>
#>  1 F           NA    NA    NA   TABLE_B…     0        0        1       1       0
#>  2 Analysis … "2"   "1"   "3"   VALUE        1        2        1       1       0
#>  3 Age, years ""    ""    ""    HEADER       2        1        1       1       0
#>  4 N          "2"   "1"   "3"   N            2        2        2       0       0
#>  5 Mean (SD)  "74.… "81.… "77.… VALUE        2        3        3       0       0
#>  6 Median     "74.… "81.… "77.… VALUE        2        3        4       0       0
#>  7 Range      "(63… "(81… "(75… VALUE        2        3        5       0       0
#>  8 IQ range   "(63… "(81… "(75… VALUE        2        3        6       0       0
#>  9 M           NA    NA    NA   TABLE_B…     0        0        1       0       1
#> 10 Analysis … "3"   "4"   "2"   VALUE        1        2        1       1       0
#> 11 Age, years ""    ""    ""    HEADER       2        1        1       1       0
#> 12 N          "3"   "4"   "2"   N            2        2        2       0       0
#> 13 Mean (SD)  "66.… "74.… "64.… VALUE        2        3        3       0       0
#> 14 Median     "64.… "72.… "64.… VALUE        2        3        4       0       0
#> 15 Range      "(52… "(68… "(57… VALUE        2        3        5       0       0
#> 16 IQ range   "(52… "(69… "(57… VALUE        2        3        6       0       0

# w/prefix
bind_table(t1, t2, tablebyvar = "SEX", prefix = "Gender: ")
#> # A tibble: 16 × 10
#>    label      `0`   `54`  `81`  row_type  anbr indentme roworder newrows newpage
#>    <chr>      <chr> <chr> <chr> <chr>    <dbl>    <dbl>    <int>   <dbl>   <dbl>
#>  1 Gender: F   NA    NA    NA   TABLE_B…     0        0        1       1       0
#>  2 Analysis … "2"   "1"   "3"   VALUE        1        2        1       1       0
#>  3 Age, years ""    ""    ""    HEADER       2        1        1       1       0
#>  4 N          "2"   "1"   "3"   N            2        2        2       0       0
#>  5 Mean (SD)  "74.… "81.… "77.… VALUE        2        3        3       0       0
#>  6 Median     "74.… "81.… "77.… VALUE        2        3        4       0       0
#>  7 Range      "(63… "(81… "(75… VALUE        2        3        5       0       0
#>  8 IQ range   "(63… "(81… "(75… VALUE        2        3        6       0       0
#>  9 Gender: M   NA    NA    NA   TABLE_B…     0        0        1       0       1
#> 10 Analysis … "3"   "4"   "2"   VALUE        1        2        1       1       0
#> 11 Age, years ""    ""    ""    HEADER       2        1        1       1       0
#> 12 N          "3"   "4"   "2"   N            2        2        2       0       0
#> 13 Mean (SD)  "66.… "74.… "64.… VALUE        2        3        3       0       0
#> 14 Median     "64.… "72.… "64.… VALUE        2        3        4       0       0
#> 15 Range      "(52… "(68… "(57… VALUE        2        3        5       0       0
#> 16 IQ range   "(52… "(69… "(57… VALUE        2        3        6       0       0

# w/counts
bind_table(t1, t2, tablebyvar = "SEX", add_count = TRUE, colvar = "TRT01PN")
#> # A tibble: 16 × 10
#>    label      `0`   `54`  `81`  row_type  anbr indentme roworder newrows newpage
#>    <chr>      <chr> <chr> <chr> <chr>    <dbl>    <dbl>    <int>   <dbl>   <dbl>
#>  1 F          "2"   "1"   "3"   TABLE_B…    NA        0        1       1       0
#>  2 Analysis … "2"   "1"   "3"   VALUE        1        2        1       1       0
#>  3 Age, years ""    ""    ""    HEADER       2        1        1       1       0
#>  4 N          "2"   "1"   "3"   N            2        2        2       0       0
#>  5 Mean (SD)  "74.… "81.… "77.… VALUE        2        3        3       0       0
#>  6 Median     "74.… "81.… "77.… VALUE        2        3        4       0       0
#>  7 Range      "(63… "(81… "(75… VALUE        2        3        5       0       0
#>  8 IQ range   "(63… "(81… "(75… VALUE        2        3        6       0       0
#>  9 M          "3"   "4"   "2"   TABLE_B…    NA        0        1       0       1
#> 10 Analysis … "3"   "4"   "2"   VALUE        1        2        1       1       0
#> 11 Age, years ""    ""    ""    HEADER       2        1        1       1       0
#> 12 N          "3"   "4"   "2"   N            2        2        2       0       0
#> 13 Mean (SD)  "66.… "74.… "64.… VALUE        2        3        3       0       0
#> 14 Median     "64.… "72.… "64.… VALUE        2        3        4       0       0
#> 15 Range      "(52… "(68… "(57… VALUE        2        3        5       0       0
#> 16 IQ range   "(52… "(69… "(57… VALUE        2        3        6       0       0