Difference Test for Two Proportions

Various tests were implemented to test the difference between two proportions.

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,
  na_str = NA_character_,
  nested = TRUE,
  ...,
  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 by rtables when requested by a statistics function.

.ref_group

(data.frame or vector)
the data corresponding to the reference group.

.in_ref_col

(logical)
TRUE when working with the reference level, FALSE otherwise.

variables

(named list of string)
list of additional analysis variables.

method

(string)
one of chisq, cmh, fisher, or schouten; 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.

na_str

(string)
string used to replace all NA 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.

...

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 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. See Details in analyze_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.

Value

• s_test_proportion_diff() returns a named list with a single item pval with an attribute label describing 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 formatted rtables::CellValue().

• test_proportion_diff() 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_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 as afun in test_proportion_diff().

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

See also

h_prop_diff_test

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