ggstatsplot (version 0.0.6)

subtitle_contigency_tab: Making text subtitle for contingency analysis (Pearson's chi-square test for independence for between-subjects design or McNemar's test for within-subjects design)

Description

Making text subtitle for contingency analysis (Pearson's chi-square test for independence for between-subjects design or McNemar's test for within-subjects design)

Usage

subtitle_contigency_tab(data, main, condition, counts = NULL,
  nboot = 25, paired = FALSE, stat.title = NULL, conf.level = 0.95,
  conf.type = "norm", messages = TRUE, k = 3)

Arguments

data

The data as a data frame (matrix or tables will not be accepted).

main

The variable to use as the rows in the contingency table.

condition

The variable to use as the columns in the contingency table.

counts

A string naming a variable in data containing counts, or NULL if each row represents a single observation (Default).

nboot

Number of bootstrap samples for computing effect size (Default: 25).

paired

Logical indicating whether data came from a within-subjects design study (Default: FALSE). If TRUE, McNemar test subtitle will be returned. If FALSE, Pearson's chi-square test will be returned.

stat.title

Title for the effect being investigated with the chi-square test. The default is NULL, i.e. no title will be added to describe the effect being shown. An example of a stat.title argument will be something like "main x condition" or "interaction".

conf.level

Scalar between 0 and 1. If NULL, the defaults return 95 lower and upper confidence intervals (0.95).

conf.type

A vector of character strings representing the type of intervals required. The value should be any subset of the values "norm", "basic", "perc", "bca". For more, see ?boot::boot.ci.

messages

Decides whether messages references, notes, and warnings are to be displayed (Default: TRUE).

k

Number of digits after decimal point (should be an integer) (Default: k = 3).

See Also

ggpiestats

Examples

# NOT RUN {
# without counts data
subtitle_contigency_tab(
  data = mtcars,
  main = am,
  condition = cyl
)

# with counts data
# in case of no variation, NaN will be shown for results
library(jmv)

dat <- as.data.frame(HairEyeColor) %>%
  dplyr::filter(.data = ., Sex == "Male")

subtitle_contigency_tab(
  data = dat,
  main = Hair,
  condition = Sex,
  counts = Freq
)
# }