Adding new standard column structure functions

[gmbecker]

Pull Request

Fixes #432

Checks

• (Have you updated the NEWS.md ?)
• (Have you added proper tests for new functions/features ?)
• (Have you added new functions to the pkgdown.yml ?)
• (Have you run document() on new functions ?)

[munoztd0]

@gmbecker added quartile col str

dat <- create_colspan_var(
   data.frame(
     TRT01A = factor(rep(c("Placebo", "Active 1"), each = 20)),
     BW = c(rnorm(20, 70, 10), rnorm(20, 75, 10))
   ),
   non_active_grp = "Placebo",
   non_active_grp_span_lbl = "Control",
   active_grp_span_lbl = "Active Treatment",
   colspan_var = "colspan_trt",
   trt_var = "TRT01A"
 )
 colspan_trt_map <- create_colspan_map(
   dat,
   non_active_grp = "Placebo",
   non_active_grp_span_lbl = "Control",
   active_grp_span_lbl = "Active Treatment",
   colspan_var = "colspan_trt",
   trt_var = "TRT01A"
 )

 lyt <- basic_table() |>
   quartile_col_struct(
     var = "BW",
     colspan_trt_map = colspan_trt_map,
     span_lbl = "Body Weight (kg) Quartiles"
   ) |>
   analyze("BW", afun = function(x, ...) length(x))

 build_table(lyt, dat)

looks like :

 
                   Active Treatment                                    Control                   
                       Active 1                                        Placebo                   
                        (N=20)                                          (N=20)                   
              Body Weight (kg) Quartiles                      Body Weight (kg) Quartiles         
     58 to <68   68 to <76   76 to <80   80 to 102   47 to <62   62 to <69   69 to <74   74 to 95
—————————————————————————————————————————————————————————————————————————————————————————————————
BW       5           5           5           5           5           5           5          5    

[munoztd0]

@gmbecker quartile col str now looks like these from @jkovach2 comments

dat <- data.frame(
  TRT01A = factor(rep(c("Placebo", "Active 1"), each = 10)),
  WGTGR1 = factor(
    rep(c("47 to <62", "62 to <69", "69 to <74", "74 to 95", "47 to <62"), 4),
    levels = c("47 to <62", "62 to <69", "69 to <74", "74 to 95")
  )
)
dat <- create_colspan_var(
  dat,
  non_active_grp = "Placebo",
  non_active_grp_span_lbl = "Control",
  active_grp_span_lbl = "Active Treatment",
  colspan_var = "colspan_trt",
  trt_var = "TRT01A"
)
colspan_trt_map <- create_colspan_map(
  dat,
  non_active_grp = "Placebo",
  non_active_grp_span_lbl = "Control",
  active_grp_span_lbl = "Active Treatment",
  colspan_var = "colspan_trt",
  trt_var = "TRT01A"
)

lyt <- basic_table() |>
  quartile_col_struct(
    grp_var = "WGTGR1",
    colspan_trt_map = colspan_trt_map,
    span_lbl = "Body Weight (kg) Quartiles"
  ) |>
  analyze("BW", afun = function(x, ...) length(x))

build_table(lyt, dat)

looks like :

           		 Active Treatment                                  Control                   
                           Active 1                                       Placebo                   
                            (N=10)                                         (N=10)                   
                  Body Weight (kg) Quartiles                     Body Weight (kg) Quartiles         
         47 to <62   62 to <69   69 to <74   74 to 95   47 to <62   62 to <69   69 to <74   74 to 95
————————————————————————————————————————————————————————————————————————————————————————————————————
BW       4           2           2          2           4           2           2          2