sta_chisq: Pearson's or McNemar's Chi-squared Test for Count Data

In j3ypi/inductive: A pipe-friendly and consistent framework for frequentist statistics in R

Description

Performs chi-squared contingency table tests and goodness-of-fit tests.

Usage

sta_chisq(
  x = NULL,
  y = NULL,
  paired = FALSE,
  obj = TRUE,
  correct = TRUE,
  p = rep(1/length(x), length(x)),
  rescale.p = FALSE,
  simulate.p.value = FALSE,
  B = 2000
)

Arguments

x	a numeric vector or matrix. x and y can also both be factors.
y	a numeric vector; ignored if x is a matrix. If x is a factor, y should be a factor of the same length.
paired	a logical variable indicating whether to treat the two variances as being equal.
obj	a logical whether the test object of stats::chisq.test() or stats::mcnemar.test should be returned.
correct	a logical indicating whether to apply continuity correction when computing the test statistic for 2 by 2 tables: one half is subtracted from all |O - E| differences; however, the correction will not be bigger than the differences themselves. No correction is done if simulate.p.value = TRUE.
p	a vector of probabilities of the same length of x. An error is given if any entry of p is negative.
rescale.p	a logical scalar; if TRUE then p is rescaled (if necessary) to sum to 1. If rescale.p is FALSE, and p does not sum to 1, an error is given.
simulate.p.value	a logical indicating whether to compute p-values by Monte Carlo simulation.
B	an integer specifying the number of replicates used in the Monte Carlo test.

Examples

## Not run: 
library(magrittr)
data(big_five, package = "inductive")

kont <- table(big_five$Geschlecht, big_five$Extraversion > 4)

sta_chisq(kont)

kont %>% 
  sta_chisq(paired = TRUE)


## End(Not run)

j3ypi/inductive documentation built on Feb. 7, 2020, 12:37 p.m.