Cumulative Counts with Thresholds

Usage

s_count_cumulative(
  x,
  thresholds,
  lower_tail = TRUE,
  include_eq = TRUE,
  .N_col,
  ...
)

a_count_cumulative(
  x,
  thresholds,
  lower_tail = TRUE,
  include_eq = TRUE,
  .N_col,
  ...
)

count_cumulative(
  lyt,
  vars,
  var_labels = vars,
  show_labels = "visible",
  ...,
  table_names = vars,
  .stats = NULL,
  .formats = NULL,
  .labels = NULL,
  .indent_mods = NULL
)

Arguments

x

(numeric)
vector of numbers we want to analyze.

thresholds

(numeric)
vector of cutoff value for the counts.

lower_tail

(logical)
whether to count lower tail, default is TRUE.

include_eq

(logical)
whether to include value equal to the threshold in count, default is TRUE.

.N_col

(count)
denominator for fraction calculation.

...

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.

var_labels

(character)
character for label.

show_labels

(string)
label visibility: one of "default", "visible" and "hidden".

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.

.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_count_cumulative() returns a named list of count_fractions: a list with each thresholds value as a component, each component containing a vector for the count and fraction.

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

• count_cumulative() 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_count_cumulative() to the table layout.

Functions

• s_count_cumulative(): Statistics function that produces a named list given a numeric vector of thresholds.

• a_count_cumulative(): Formatted analysis function which is used as afun in count_cumulative().

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

See also

Examples

# Internal function - s_count_cumulative
if (FALSE) {
set.seed(1, kind = "Mersenne-Twister")
x <- c(sample(1:10, 10), NA)
.N_col <- length(x)
s_count_cumulative(x, thresholds = c(0, 5, 11), .N_col = .N_col)
s_count_cumulative(x, thresholds = c(0, 5, 11), include_eq = FALSE, na.rm = FALSE, .N_col = .N_col)
}

# Internal function - a_count_cumulative
if (FALSE) {
# Use the Formatted Analysis function for `analyze()`. We need to ungroup `count_fraction` first
# so that the `rtables` formatting function `format_count_fraction()` can be applied correctly.
afun <- make_afun(a_count_cumulative, .ungroup_stats = "count_fraction")
afun(x, thresholds = c(0, 5, 11), .N_col = .N_col)
}

basic_table() %>%
  split_cols_by("ARM") %>%
  add_colcounts() %>%
  count_cumulative(
    vars = "AGE",
    thresholds = c(40, 60)
  ) %>%
  build_table(tern_ex_adsl)
#>           A: Drug X    B: Placebo   C: Combination
#>             (N=69)       (N=73)         (N=58)    
#> ——————————————————————————————————————————————————
#> AGE                                               
#>   <= 40   52 (75.4%)   58 (79.5%)     41 (70.7%)  
#>   <= 60   69 (100%)    73 (100%)      58 (100%)