Summarize the Change from Baseline or Absolute Baseline Values

The primary analysis variable .var indicates the numerical change from baseline results, and additional required secondary analysis variables are value and baseline_flag. Depending on the baseline flag, either the absolute baseline values (at baseline) or the change from baseline values (post-baseline) are then summarized.

Usage

s_change_from_baseline(df, .var, variables, na.rm = TRUE, ...)

a_change_from_baseline(df, .var, variables, na.rm = TRUE, ...)

summarize_change(
  lyt,
  vars,
  na_str = NA_character_,
  nested = TRUE,
  ...,
  table_names = vars,
  .stats = c("n", "mean_sd", "median", "range"),
  .formats = NULL,
  .labels = NULL,
  .indent_mods = NULL
)

Arguments

df

(data.frame)
data set containing all analysis variables.

.var

(string)
single variable name that is passed by rtables when requested by a statistics function.

variables

(named list of string)
list of additional analysis variables.

na.rm

(flag)
whether NA values should be removed from x prior to analysis.

...

additional arguments for the lower level functions.

lyt

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

vars

(character)
variable names for the primary analysis variable to be iterated over.

na_str

(string)
string used to replace all NA or empty values in the output.

nested

(flag)
whether this layout instruction should be applied within the existing layout structure if possible (TRUE, the default) or as a new top-level element (FALSE). Ignored if it would nest a split. underneath analyses, which is not allowed.

table_names

(character)
this can be customized in case that the same vars are analyzed multiple times, to avoid warnings from rtables.

.stats

(character)
statistics to select for the table.

.formats

(named character or list)
formats for the statistics. See Details in analyze_vars for more information on the "auto" setting.

.labels

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

.indent_mods

(named integer)
indent modifiers for the labels. Defaults to 0, which corresponds to the unmodified default behavior. Can be negative.

Value

• s_change_from_baseline() returns the same values returned by s_summary.numeric().

• a_change_from_baseline() returns the corresponding list with formatted rtables::CellValue().

• summarize_change() returns a layout object suitable for passing to further layouting functions, or to rtables::build_table(). Adding this function to an rtable layout will add formatted rows containing the statistics from s_change_from_baseline() to the table layout.

Functions

• s_change_from_baseline(): Statistics function that summarizes baseline or post-baseline visits.

• a_change_from_baseline(): Formatted analysis function which is used as afun in summarize_change().

• summarize_change(): Layout-creating function which can take statistics function arguments and additional format arguments. This function is a wrapper for rtables::analyze().

Note

The data in df must be either all be from baseline or post-baseline visits. Otherwise an error will be thrown.

To be used after a split on visits in the layout, such that each data subset only contains either baseline or post-baseline data.

Examples

df <- data.frame(
  chg = c(1, 2, 3),
  is_bl = c(TRUE, TRUE, TRUE),
  val = c(4, 5, 6)
)

# `summarize_change()`

## Fabricated dataset.
library(dplyr)

dta_test <- data.frame(
  USUBJID = rep(1:6, each = 3),
  AVISIT = rep(paste0("V", 1:3), 6),
  ARM = rep(LETTERS[1:3], rep(6, 3)),
  AVAL = c(9:1, rep(NA, 9))
) %>%
  mutate(ABLFLL = AVISIT == "V1") %>%
  group_by(USUBJID) %>%
  mutate(
    BLVAL = AVAL[ABLFLL],
    CHG = AVAL - BLVAL
  ) %>%
  ungroup()

results <- basic_table() %>%
  split_cols_by("ARM") %>%
  split_rows_by("AVISIT") %>%
  summarize_change("CHG", variables = list(value = "AVAL", baseline_flag = "ABLFLL")) %>%
  build_table(dta_test)
# \donttest{
Viewer(results)
# }