Summarize cumulative counts of a (numeric
) vector that is less than, less or equal to,
greater than, or greater or equal to user-specific thresholds.
Usage
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,
.stats = NULL,
.formats = NULL,
.labels = NULL,
.indent_mods = NULL
)
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,
...
)
Arguments
- lyt
(
layout
)
input layout where analyses will be added to.- vars
(
character
)
variable names for the primary analysis variable to be iterated over.- thresholds
(
numeric
)
vector of cutoff value for the counts.- lower_tail
(
logical
)
whether to count lower tail, default isTRUE
.- include_eq
(
logical
)
whether to include value equal to thethreshold
in count, default isTRUE
.- var_labels
(
character
)
character for label.- show_labels
(
string
)
label visibility: one of "default", "visible" and "hidden".- na_str
(
string
)
string used to replace allNA
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.- ...
additional arguments for the lower level functions.
- table_names
(
character
)
this can be customized in case that the samevars
are analyzed multiple times, to avoid warnings fromrtables
.- .stats
(
character
)
statistics to select for the table. Runget_stats("count_cumulative")
to see available statistics for this function.- .formats
(named
character
orlist
)
formats for the statistics. See Details inanalyze_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.- x
(
numeric
)
vector of numbers we want to analyze.- .N_col
(
integer
)
column-wise N (column count) for the full column being analyzed that is typically passed byrtables
.
Value
count_cumulative()
returns a layout object suitable for passing to further layouting functions, or tortables::build_table()
. Adding this function to anrtable
layout will add formatted rows containing the statistics froms_count_cumulative()
to the table layout.
s_count_cumulative()
returns a named list ofcount_fraction
s: a list with eachthresholds
value as a component, each component containing a vector for the count and fraction.
a_count_cumulative()
returns the corresponding list with formattedrtables::CellValue()
.
Functions
count_cumulative()
: Layout-creating function which can take statistics function arguments and additional format arguments. This function is a wrapper forrtables::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 asafun
incount_cumulative()
.
See also
Relevant helper function h_count_cumulative()
, and descriptive function d_count_cumulative()
.
Examples
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%)