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Does a 2-sample t-test for clustered data.
t.test.cluster(y, cluster, group, conf.int = 0.95)
# S3 method for t.test.cluster
print(x, digits, ...)
a matrix of statistics of class t.test.cluster
normally distributed response variable to test
cluster identifiers, e.g. subject ID
grouping variable with two values
confidence coefficient to use for confidence limits
an object created by t.test.cluster
number of significant digits to print
unused
Frank Harrell
Donner A, Birkett N, Buck C, Am J Epi 114:906-914, 1981.
Donner A, Klar N, J Clin Epi 49:435-439, 1996.
Hsieh FY, Stat in Med 8:1195-1201, 1988.
set.seed(1)
y <- rnorm(800)
group <- sample(1:2, 800, TRUE)
cluster <- sample(1:40, 800, TRUE)
table(cluster,group)
t.test(y ~ group) # R only
t.test.cluster(y, cluster, group)
# Note: negate estimates of differences from t.test to
# compare with t.test.cluster
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