| RS.trend.test {CorrBin} | R Documentation |
Rao-Scott trend test
Description
RS.trend.test implements the Rao-Scott adjusted Cochran-Armitage test
for linear increasing trend with correlated data.
Usage
RS.trend.test(cbdata)
Arguments
cbdata |
a |
Details
The test is based on calculating a design effect for each cluster by dividing the observed variability by the one expected under independence. The number of responses and the cluster size are then divided by the design effect, and a Cochran-Armitage type test statistic is computed based on these adjusted values.
The implementation aims for testing for increasing trend, and a one-sided p-value is reported. The test statistic is asymptotically normally distributed, and a two-sided p-value can be easily computed if needed.
Value
A list with components
statistic |
numeric, the value of the test statistic |
p.val |
numeric, asymptotic one-sided p-value of the test |
Author(s)
Aniko Szabo, aszabo@mcw.edu
References
Rao, J. N. K. & Scott, A. J. A (1992) Simple Method for the Analysis of Clustered Data Biometrics, 48, 577-586.
See Also
SO.trend.test, GEE.trend.test for
alternative tests; CBData for constructing a CBData object.
Examples
data(shelltox)
RS.trend.test(shelltox)