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Layering tfrmts

Source: vignettes/layer.Rmd
layer.Rmd

A core design element of tfrmt is to offer the ability to layer tfrmts together. This ability provides an opportunity to build template table formats that can be shared, improved, and reused across multiple projects. tfrmt provides a few tfrmt templates to facilitate the creation of basic tfrmts, but they require customization. This can be done through layering.

To layer tfrmts, you can pipe or use the layer_tfrmt() function. Piping is the preferred method for readability.

When a tfrmt gets layered, the values in the first tfrmt are coalesced with values in the second tfrmt. If the second tfrmt has any of the same parameters specified as the first tfrmt, the values from the second tfrmt are prioritized. The exception to this rule is the “body_plan”, which will stack the plans together. To change this behavior see the layer_tfrmt() documentation.

Example

Here is an example of layering through piping. We create a template from tfrmt_sigdig() and pipe it into a separate tfrmt.

We provide tfrmt_sigdig() with a data.frame detailing the groups and the significant digits the values are to be rounded to and it creates a tfrmt with a body_plan that supports this.

The second tfrmt defines the table specific information, including title, specific columns to use for row labels and output columns, as well as the col_plan.

The output tfrmt generates a table with the subset data_labs.


data_labs_subset <- data_labs %>% 
  filter(
    group2 %in% c("ALANINE AMINOTRANSFERASE" ,"ALBUMIN" ,"ALKALINE PHOSPHATASE","ASPARTATE AMINOTRANSFERASE", "BASOPHILS"),
    rowlbl %in% c("Bsln", "End[1]")
  )

data_input <- tribble(
  ~group1,   ~group2, ~sigdig,
  "CHEMISTRY",   ".default", 3,
  "CHEMISTRY",   "ALBUMIN",  1,
  "CHEMISTRY",   "CALCIUM",   1,
  ".default",    ".default",  2
  )


labs_tfrmt_template <- tfrmt_sigdig(
  sigdig_df = data_input,
  group = vars(group1, group2),
  label = rowlbl,
  param_defaults = param_set("[{n}]" = NA)
  ) 

labs_tfrmt <- labs_tfrmt_template %>%
  tfrmt(
    column = vars(col1, col2),
    param = param,
    value = value,
    sorting_cols = vars(ord1, ord2, ord3),
    row_grp_plan = row_grp_plan(
      label_loc = element_row_grp_loc(location = "indent")
    ),
    col_plan = col_plan(
      group1, group2,
      rowlbl,
      "Residuals" = res,
      "Change From Baseline" = cbl,
      n,
      -starts_with("ord")
      )
  )

labs_tfrmt %>% 
  print_to_gt(data_labs_subset) %>% 
  tab_options(
    container.width = 1000
  )
Placebo
Xanomeline High Dose
Xanomeline Low Dose
Residuals Change From Baseline n Residuals Change From Baseline n Residuals Change From Baseline n
CHEMISTRY








  ALANINE AMINOTRANSFERASE








    Bsln 17.5698 (9.21577) [86] 19.2024 (10.04781) [84] 17.9634 (8.71984) [82]
    End[1] 18.1190 (16.73781) 0.4167 (15.39614) [84] 19.4750 (7.43916) 0.0750 (8.07524) [80] 18.2561 (8.26387) 0.2625 (7.24742) [82]
  ALBUMIN








    Bsln 39.84 (2.807) [86] 40.29 (2.839) [84] 39.77 (2.564) [82]
    End[1] 39.63 (3.321) -0.23 (2.690) [84] 39.81 (2.481) -0.55 (2.638) [80] 39.23 (2.970) -0.54 (2.643) [82]
  ALKALINE PHOSPHATASE








    Bsln 77.6977 (58.10600) [86] 71.0482 (38.84802) [83] 73.3333 (20.72016) [81]
    End[1] 84.6429 (84.85858) 7.0714 (49.36678) [84] 70.2500 (37.90845) -1.6000 (12.00169) [80] 71.6341 (23.80295) -1.0759 (13.08725) [82]
  ASPARTATE AMINOTRANSFERASE








    Bsln 23.2442 (7.50206) [86] 23.1071 (6.61145) [84] 23.4390 (8.23737) [82]
    End[1] 25.1310 (21.32524) 1.8214 (19.03463) [84] 22.7000 (6.13023) -0.4000 (6.35968) [80] 23.2073 (8.20981) -0.3000 (8.05896) [82]
HEMATOLOGY








  BASOPHILS








    Bsln 0.054 (0.0364) [85] 0.052 (0.0204) [81] 0.054 (0.0308) [81]
    End[1] 0.048 (0.0258) -0.007 (0.0288) [84] 0.051 (0.0244) -0.001 (0.0207) [81] 0.049 (0.0269) -0.006 (0.0293) [82]

Conflicting Layers

As two tfrmt are layered, there may come a case where the groups value is not the same across the body plan. Additionally, data may be provided in a slightly different group names than was expected. Addressing this without having to re-write the entire body_plan is able to be done with the update_group() function.

Similar to the rename() function, here we provide the new group name and which old group name needs to be updated. The function maps across the entire tfrmt and updates all references of the old group name to the new one.

For example, this is useful when a template tfrmt needs references updated. This could happen when the input data set has a slightly different naming convention than expected.


## provided data had different column names for groups
alternate_data_labs_subset <- data_labs_subset %>% 
  rename(
    `Lab Type` = group1,
    `Lab Test` = group2,
  )

labs_tfrmt %>% 
  update_group(
    `Lab Type` = group1,
    `Lab Test` = group2,
  ) %>% 
  tfrmt(
    col_plan = col_plan(
      `Lab Type`, `Lab Test`,
      rowlbl,
      "Residuals" = res,
      "Change From Baseline" = cbl,
      n,
      -starts_with("ord")
      )
  ) %>% 
  print_to_gt(alternate_data_labs_subset) %>% 
  tab_options(
    container.width = 1000
  )
Placebo
Xanomeline High Dose
Xanomeline Low Dose
Residuals Change From Baseline n Residuals Change From Baseline n Residuals Change From Baseline n
CHEMISTRY








  ALANINE AMINOTRANSFERASE








    Bsln 17.5698 (9.21577) [86] 19.2024 (10.04781) [84] 17.9634 (8.71984) [82]
    End[1] 18.1190 (16.73781) 0.4167 (15.39614) [84] 19.4750 (7.43916) 0.0750 (8.07524) [80] 18.2561 (8.26387) 0.2625 (7.24742) [82]
  ALBUMIN








    Bsln 39.84 (2.807) [86] 40.29 (2.839) [84] 39.77 (2.564) [82]
    End[1] 39.63 (3.321) -0.23 (2.690) [84] 39.81 (2.481) -0.55 (2.638) [80] 39.23 (2.970) -0.54 (2.643) [82]
  ALKALINE PHOSPHATASE








    Bsln 77.6977 (58.10600) [86] 71.0482 (38.84802) [83] 73.3333 (20.72016) [81]
    End[1] 84.6429 (84.85858) 7.0714 (49.36678) [84] 70.2500 (37.90845) -1.6000 (12.00169) [80] 71.6341 (23.80295) -1.0759 (13.08725) [82]
  ASPARTATE AMINOTRANSFERASE








    Bsln 23.2442 (7.50206) [86] 23.1071 (6.61145) [84] 23.4390 (8.23737) [82]
    End[1] 25.1310 (21.32524) 1.8214 (19.03463) [84] 22.7000 (6.13023) -0.4000 (6.35968) [80] 23.2073 (8.20981) -0.3000 (8.05896) [82]
HEMATOLOGY








  BASOPHILS








    Bsln 0.054 (0.0364) [85] 0.052 (0.0204) [81] 0.054 (0.0308) [81]
    End[1] 0.048 (0.0258) -0.007 (0.0288) [84] 0.051 (0.0244) -0.001 (0.0207) [81] 0.049 (0.0269) -0.006 (0.0293) [82]