Usage
s_test_proportion_diff(
df,
.var,
.ref_group,
.in_ref_col,
variables = list(strata = NULL),
method = c("chisq", "schouten", "fisher", "cmh")
)
a_test_proportion_diff(
df,
.var,
.ref_group,
.in_ref_col,
variables = list(strata = NULL),
method = c("chisq", "schouten", "fisher", "cmh")
)
test_proportion_diff(
lyt,
vars,
...,
var_labels = vars,
show_labels = "hidden",
table_names = vars,
.stats = NULL,
.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 byrtableswhen requested by a statistics function.- .ref_group
(
data.frameorvector)
the data corresponding to the reference group.- .in_ref_col
(
logical)TRUEwhen working with the reference level,FALSEotherwise.- variables
(named
listofstring)
list of additional analysis variables.- method
(
string)
one ofchisq,cmh,fisher, orschouten; specifies the test used to calculate the p-value.- lyt
(
layout)
input layout where analyses will be added to.- vars
(
character)
variable names for the primary analysis variable to be iterated over.- ...
other arguments are passed to
s_test_proportion_diff().- 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 samevarsare analyzed multiple times, to avoid warnings fromrtables.- .stats
(
character)
statistics to select for the table.- .formats
(named
characterorlist)
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.- tbl
(
matrix)
matrix with two groups in rows and the binary response (TRUE/FALSE) in columns.
Value
s_test_proportion_diff()returns a namedlistwith a single itempvalwith an attributelabeldescribing the method used. The p-value tests the null hypothesis that proportions in two groups are the same.
a_test_proportion_diff()returns the corresponding list with formattedrtables::CellValue().
test_proportion_diff()returns a layout object suitable for passing to further layouting functions, or tortables::build_table(). Adding this function to anrtablelayout will add formatted rows containing the statistics froms_test_proportion_diff()to the table layout.
Functions
s_test_proportion_diff(): Statistics function which tests the difference between two proportions.a_test_proportion_diff(): Formatted analysis function which is used asafunintest_proportion_diff().test_proportion_diff(): Layout-creating function which can take statistics function arguments and additional format arguments. This function is a wrapper forrtables::analyze().
Examples
dta <- data.frame(
rsp = sample(c(TRUE, FALSE), 100, TRUE),
grp = factor(rep(c("A", "B"), each = 50)),
strat = factor(rep(c("V", "W", "X", "Y", "Z"), each = 20))
)
# With `rtables` pipelines.
l <- basic_table() %>%
split_cols_by(var = "grp", ref_group = "B") %>%
test_proportion_diff(
vars = "rsp",
method = "cmh", variables = list(strata = "strat")
)
build_table(l, df = dta)
#> B A
#> —————————————————————————————————————————————————————
#> p-value (Cochran-Mantel-Haenszel Test) 1.0000