View source: R/summarize_colvars.R
summarize_colvars | R Documentation |
The analyze function summarize_colvars()
uses the statistics function s_summary()
to analyze variables that are
arranged in columns. The variables to analyze should be specified in the table layout via column splits (see
rtables::split_cols_by()
and rtables::split_cols_by_multivar()
) prior to using summarize_colvars()
.
The function is a minimal wrapper for rtables::analyze_colvars()
, a function typically used to apply different
analysis methods in rows for each column variable. To use the analysis methods as column labels, please refer to
the analyze_vars_in_cols()
function.
summarize_colvars(
lyt,
...,
na_str = default_na_str(),
.stats = c("n", "mean_sd", "median", "range", "count_fraction"),
.formats = NULL,
.labels = NULL,
.indent_mods = NULL
)
lyt |
( |
... |
arguments passed to |
na_str |
( |
.stats |
( |
.formats |
(named |
.labels |
(named |
.indent_mods |
(named |
A layout object suitable for passing to further layouting functions, or to rtables::build_table()
.
Adding this function to an rtable
layout will summarize the given variables, arrange the output
in columns, and add it to the table layout.
rtables::split_cols_by_multivar()
and analyze_colvars_functions
.
dta_test <- data.frame(
USUBJID = rep(1:6, each = 3),
PARAMCD = rep("lab", 6 * 3),
AVISIT = rep(paste0("V", 1:3), 6),
ARM = rep(LETTERS[1:3], rep(6, 3)),
AVAL = c(9:1, rep(NA, 9)),
CHG = c(1:9, rep(NA, 9))
)
## Default output within a `rtables` pipeline.
basic_table() %>%
split_cols_by("ARM") %>%
split_rows_by("AVISIT") %>%
split_cols_by_multivar(vars = c("AVAL", "CHG")) %>%
summarize_colvars() %>%
build_table(dta_test)
## Selection of statistics, formats and labels also work.
basic_table() %>%
split_cols_by("ARM") %>%
split_rows_by("AVISIT") %>%
split_cols_by_multivar(vars = c("AVAL", "CHG")) %>%
summarize_colvars(
.stats = c("n", "mean_sd"),
.formats = c("mean_sd" = "xx.x, xx.x"),
.labels = c(n = "n", mean_sd = "Mean, SD")
) %>%
build_table(dta_test)
## Use arguments interpreted by `s_summary`.
basic_table() %>%
split_cols_by("ARM") %>%
split_rows_by("AVISIT") %>%
split_cols_by_multivar(vars = c("AVAL", "CHG")) %>%
summarize_colvars(na.rm = FALSE) %>%
build_table(dta_test)
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