The analyze function count_cumulative() creates a layout element to calculate cumulative counts of values in a
numeric variable that are less than, less or equal to, greater than, or greater or equal to user-specified
threshold values.
This function analyzes numeric variable vars against the threshold values supplied to the thresholds
argument as a numeric vector. Whether counts should include the threshold values, and whether to count
values lower or higher than the threshold values can be set via the include_eq and lower_tail
parameters, respectively.
count_cumulative(
lyt,
vars,
thresholds,
lower_tail = TRUE,
include_eq = TRUE,
var_labels = vars,
show_labels = "visible",
na_str = default_na_str(),
nested = TRUE,
table_names = vars,
...,
na_rm = TRUE,
.stats = c("count_fraction"),
.stat_names = NULL,
.formats = NULL,
.labels = NULL,
.indent_mods = NULL
)s_count_cumulative(
x,
thresholds,
lower_tail = TRUE,
include_eq = TRUE,
denom = c("N_col", "n", "N_row"),
.N_col,
.N_row,
na_rm = TRUE,
...
)
a_count_cumulative(
x,
...,
.stats = NULL,
.stat_names = NULL,
.formats = NULL,
.labels = NULL,
.indent_mods = NULL
)
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.
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().
(PreDataTableLayouts)
layout that analyses will be added to.
(character)
variable names for the primary analysis variable to be iterated over.
(numeric)
vector of cutoff values for the counts.
(flag)
whether to count lower tail, default is TRUE.
(flag)
whether to include value equal to the threshold in
count, default is TRUE.
(character)
variable labels.
(string)
label visibility: one of "default", "visible" and "hidden".
(string)
string used to replace all NA or empty values in the output.
(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.
(character)
this can be customized in the case that the same vars are analyzed multiple
times, to avoid warnings from rtables.
additional arguments for the lower level functions.
(flag)
whether NA values should be removed from x prior to analysis.
(character)
statistics to select for the table.
Options are: 'count_fraction'
(character)
names of the statistics that are passed directly to name single statistics
(.stats). This option is visible when producing rtables::as_result_df() with make_ard = TRUE.
(named character or list)
formats for the statistics. See Details in analyze_vars for more
information on the "auto" setting.
(named character)
labels for the statistics (without indent).
(named integer)
indent modifiers for the labels. Defaults to 0, which corresponds to the
unmodified default behavior. Can be negative.
(numeric)
vector of numbers we want to analyze.
(string)
choice of denominator for proportion. Options are:
n: number of values in this row and column intersection.
N_row: total number of values in this row across columns.
N_col: total number of values in this column across rows.
(integer(1))
column-wise N (column count) for the full column being analyzed that is typically
passed by rtables.
(integer(1))
row-wise N (row group count) for the group of observations being analyzed
(i.e. with no column-based subsetting) that is typically passed by rtables.
count_cumulative(): Layout-creating function which can take statistics function arguments
and additional format arguments. This function is a wrapper for rtables::analyze().
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().
Relevant helper function h_count_cumulative(), and descriptive function d_count_cumulative().
basic_table() %>%
split_cols_by("ARM") %>%
add_colcounts() %>%
count_cumulative(
vars = "AGE",
thresholds = c(40, 60)
) %>%
build_table(tern_ex_adsl)
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