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Summarize Variables in Columns

Source: R/summarize_colvars.R
summarize_colvars.Rd

[Stable]

This analyze function uses the S3 generic function s_summary() to summarize different variables that are arranged in columns. Additional standard formatting arguments are available. It is a minimal wrapper for rtables::analyze_colvars().

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.

Value

A layout object suitable for passing to further layouting functions, or to rtables::build_table(). Adding this function to an rtable layout will summarize the given variables, arrange the output in columns, and add it to the table layout.

See also

rtables::split_cols_by_multivar() and analyze_colvars_functions.

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