CARL returns the test statistic and p-value for the aligned RL test
with empirically fitted degrees of freedom.
CARL(
y,
treatment,
block1,
block2,
n_components = 0,
n_permutations = 0,
treatment_scores = NULL,
sig_digits = 4,
verbose = FALSE
)The CARL test statistic adjusted for ties together with the
associated p-value using a chi-squared distribution with t+1 degrees of
freedom.
a numeric vector for the response variable.
a vector giving the treatment type for the corresponding
elements of y.
a vector giving the first blocking variable for the
corresponding elements of y.
a vector giving the second blocking variable for the
corresponding elements of y.
the number of polynomial components you wish to test. The maximum number of components is the number of treatments less one. If the number of components requested is less than t-2, a remainder component is created.
the number of permutations you wish to run.
the scores to be applied to the treatment groups. If not declared these will be set automatically and should be checked.
the number of significant digits the output should show.
flag for turning on the status bar for permutation tests.
This test is applicable to Latin square designs and is recommended over the RL and ARL test. The test uses t+1 as the degrees of freedom of the chi-squared null distribution and results in appropriate test sizes as well as good power.
Rayner, J.C.W and Livingston, G. C. (2022). An Introduction to Cochran-Mantel-Haenszel Testing and Nonparametric ANOVA. Wiley.
ARL() PARL()
attach(peanuts)
CARL(y = yield, treatment = treatment, block1 = row, block2 = col)
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