View source: R/cochran_qtest.R
cochran_qtest | R Documentation |
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.
cochran_qtest(data, formula)
data |
a data frame containing the variables in the formula. |
formula |
a formula of the form |
# 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)
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