cochran_qtest: Cochran's Q Test

In kassambara/rstatix: Pipe-Friendly Framework for Basic Statistical Tests

Cochran's Q Test

Description

Performs the Cochran's Q test for unreplicated randomized block design experiments with a binary response variable and paired data. This test is analogue to the friedman.test() with 0,1 coded response. It's an extension of the McNemar Chi-squared test for comparing more than two paired proportions.

Usage

cochran_qtest(data, formula)

Arguments

data	a data frame containing the variables in the formula.
formula	a formula of the form a ~ b | c, where a is the outcome variable name; b is the within-subjects factor variables; and c (factor) is the column name containing individuals/subjects identifier. Should be unique per individual.

Examples

# Generate a demo data
mydata <- data.frame(
  outcome = c(0,1,1,0,0,1,0,1,1,1,1,1,0,0,1,1,0,1,0,1,1,0,0,1,0,1,1,0,0,1),
  treatment = gl(3,1,30,labels=LETTERS[1:3]),
  participant = gl(10,3,labels=letters[1:10])
)
mydata$outcome <- factor(
  mydata$outcome, levels = c(1, 0),
  labels = c("success", "failure")
  )
# Cross-tabulation
xtabs(~outcome + treatment, mydata)

# Compare the proportion of success between treatments
cochran_qtest(mydata, outcome ~ treatment|participant)

# pairwise comparisons between groups
pairwise_mcnemar_test(mydata, outcome ~ treatment|participant)

kassambara/rstatix documentation built on Feb. 6, 2023, 3:36 a.m.