View source: R/aaa-generics1.R
mc.test.chisq.CMData | R Documentation |
mc.test.chisq
tests whether the assumption of marginal compatibility is
violated in the data.
## S3 method for class 'CMData'
mc.test.chisq(object, ...)
## S3 method for class 'CBData'
mc.test.chisq(object, ...)
mc.test.chisq(object, ...)
object |
a |
... |
other potential arguments; not currently used |
The assumption of marginal compatibility (AKA reproducibility or interpretability) implies that
the marginal probability of response does not depend on clustersize.
Stefanescu and Turnbull (2003), and Pang and Kuk (2007) developed a
Cochran-Armitage type test for trend in the marginal probability of success
as a function of the clustersize. mc.test.chisq
implements a
generalization of that test extending it to multiple treatment groups.
A list with the following components:
overall.chi |
the test statistic; sum of the statistics for each group |
overall.p |
p-value of the test |
individual |
a list of the results of the test applied to each group separately:
|
Aniko Szabo
Stefanescu, C. & Turnbull, B. W. (2003) Likelihood inference for exchangeable binary data with varying cluster sizes. Biometrics, 59, 18-24
Pang, Z. & Kuk, A. (2007) Test of marginal compatibility and smoothing methods for exchangeable binary data with unequal cluster sizes. Biometrics, 63, 218-227
mc.est
for estimating the distribution under marginal
compatibility.
data(dehp)
mc.test.chisq(dehp)
data(shelltox)
mc.test.chisq(shelltox)
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