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Summarize Variables in Columns

Source: R/summarize_colvars.R
summarize_colvars.Rd

[Stable]

This Analyze Function uses the new S3 generic function s_summary() to summarize different variables that are arranged in columns. Additional standard formatting arguments are available.

Usage 

summarize_colvars(
  lyt,
  ...,
  .stats = c("n", "mean_sd", "median", "range", "count_fraction"),
  .formats = NULL,
  .labels = NULL,
  .indent_mods = NULL
)

Arguments

lyt

(layout)
input layout where analyses will be added to.

...

arguments passed to s_summary().

.stats

(character)
statistics to select for the table.

.formats

(named character or list)
formats for the statistics.

.labels

(named character)
labels for the statistics (without indent).

.indent_mods

(named integer)
indent modifiers for the labels.

Formatting arguments

These additional formatting arguments can be passed to the layout creating function:

.stats

(character)
names of the statistics to use

.indent_mods

(integer)
named vector of indent modifiers for the labels

.formats

(character or list)
named vector of formats for the statistics

.labels

(character)
named vector of labels for the statistics (without indent)

See also

rtables::split_cols_by_multivar()

Examples 


dta_test <- data.frame(
  USUBJID = rep(1:6, each = 3),
  PARAMCD = rep("lab", 6 * 3),
  AVISIT = rep(paste0("V", 1:3), 6),
  ARM = rep(LETTERS[1:3], rep(6, 3)),
  AVAL = c(9:1, rep(NA, 9)),
  CHG = c(1:9, rep(NA, 9))
)

## Default output within a `rtables` pipeline.
basic_table() %>%
  split_cols_by("ARM") %>%
  split_rows_by("AVISIT") %>%
  split_cols_by_multivar(vars = c("AVAL", "CHG")) %>%
  summarize_colvars() %>%
  build_table(dta_test)
#>                         A                       B                 C     
#>                 AVAL         CHG        AVAL         CHG      AVAL   CHG
#> ————————————————————————————————————————————————————————————————————————
#> V1                                                                      
#>   n               2           2           1           1        0      0 
#>   Mean (SD)   7.5 (2.1)   2.5 (2.1)   3.0 (NA)    7.0 (NA)     NA    NA 
#>   Median         7.5         2.5         3.0         7.0       NA    NA 
#>   Min - Max   6.0 - 9.0   1.0 - 4.0   3.0 - 3.0   7.0 - 7.0    NA    NA 
#> V2                                                                      
#>   n               2           2           1           1        0      0 
#>   Mean (SD)   6.5 (2.1)   3.5 (2.1)   2.0 (NA)    8.0 (NA)     NA    NA 
#>   Median         6.5         3.5         2.0         8.0       NA    NA 
#>   Min - Max   5.0 - 8.0   2.0 - 5.0   2.0 - 2.0   8.0 - 8.0    NA    NA 
#> V3                                                                      
#>   n               2           2           1           1        0      0 
#>   Mean (SD)   5.5 (2.1)   4.5 (2.1)   1.0 (NA)    9.0 (NA)     NA    NA 
#>   Median         5.5         4.5         1.0         9.0       NA    NA 
#>   Min - Max   4.0 - 7.0   3.0 - 6.0   1.0 - 1.0   9.0 - 9.0    NA    NA 

## Selection of statistics, formats and labels also work.
basic_table() %>%
  split_cols_by("ARM") %>%
  split_rows_by("AVISIT") %>%
  split_cols_by_multivar(vars = c("AVAL", "CHG")) %>%
  summarize_colvars(
    .stats = c("n", "mean_sd"),
    .formats = c("mean_sd" = "xx.x, xx.x"),
    .labels = c(n = "n", mean_sd = "Mean, SD")
  ) %>%
  build_table(dta_test)
#>                       A                    B               C     
#>                AVAL       CHG       AVAL       CHG     AVAL   CHG
#> —————————————————————————————————————————————————————————————————
#> V1                                                               
#>   n             2          2          1         1       0      0 
#>   Mean, SD   7.5, 2.1   2.5, 2.1   3.0, NA   7.0, NA    NA    NA 
#> V2                                                               
#>   n             2          2          1         1       0      0 
#>   Mean, SD   6.5, 2.1   3.5, 2.1   2.0, NA   8.0, NA    NA    NA 
#> V3                                                               
#>   n             2          2          1         1       0      0 
#>   Mean, SD   5.5, 2.1   4.5, 2.1   1.0, NA   9.0, NA    NA    NA 

## Use arguments interpreted by `s_summary`.
basic_table() %>%
  split_cols_by("ARM") %>%
  split_rows_by("AVISIT") %>%
  split_cols_by_multivar(vars = c("AVAL", "CHG")) %>%
  summarize_colvars(na.rm = FALSE) %>%
  build_table(dta_test)
#>                         A                       B                 C     
#>                 AVAL         CHG        AVAL         CHG      AVAL   CHG
#> ————————————————————————————————————————————————————————————————————————
#> V1                                                                      
#>   n               2           2           1           1        0      0 
#>   Mean (SD)   7.5 (2.1)   2.5 (2.1)   3.0 (NA)    7.0 (NA)     NA    NA 
#>   Median         7.5         2.5         3.0         7.0       NA    NA 
#>   Min - Max   6.0 - 9.0   1.0 - 4.0   3.0 - 3.0   7.0 - 7.0    NA    NA 
#> V2                                                                      
#>   n               2           2           1           1        0      0 
#>   Mean (SD)   6.5 (2.1)   3.5 (2.1)   2.0 (NA)    8.0 (NA)     NA    NA 
#>   Median         6.5         3.5         2.0         8.0       NA    NA 
#>   Min - Max   5.0 - 8.0   2.0 - 5.0   2.0 - 2.0   8.0 - 8.0    NA    NA 
#> V3                                                                      
#>   n               2           2           1           1        0      0 
#>   Mean (SD)   5.5 (2.1)   4.5 (2.1)   1.0 (NA)    9.0 (NA)     NA    NA 
#>   Median         5.5         4.5         1.0         9.0       NA    NA 
#>   Min - Max   4.0 - 7.0   3.0 - 6.0   1.0 - 1.0   9.0 - 9.0    NA    NA