Description Usage Arguments Details Value References See Also Examples
Multiresponse permutation procedures (MRPP) are used for univariate and multivariate analyses of grouped data in a completely randomized oneway design. MRPP are used for comparing equality of treatment groups analogous to oneway analysis of variance (or ttest) for univariate data, or multivariate analysis of variance (Hotelling's T^2) for multivariate data.
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variables 
the names of response variables to be used in the analysis. If more than one is used these are specified using the form 
group 
the name of the grouping variable to be used in the analysis. 
data 
the 
expon 
allows selection of alternative exponents in distance calculations. Default uses 1 corresponding to Euclidean distance. Use of 2 is squared Euclidean distance, corresponding to many conventional parametric tests on means. 
c.form 
has four options that control how the groups are weighted:

hotelling 
a 
commens 
a 
interv 
allows an analysis to be conducted on univariate circular data such as time or compass orientation.
This analysis recognizes that there are no endpoints to the measurement scale. 
number.perms 
if specified a Monte Carlo resampling procedure with 
exact 
a 
has.excess 
a 
excess.value 
the value of the excess group, if not specified it is assumed that the largest grouping value indicates the excess group. 
max.dist 
specifying a numeric value causes the MRPP analysis to replace interobject distances 
save.test 
a 
The default Euclidean distance function in MRPP provides an omnibus test of distributional equivalence among groups or a test for common medians if the assumption of equal dispersions is applicable. Options allow MRPP to perform permutation (randomization) versions of ttests, oneway analysis of variance, KruskalWallis tests (for ranked data), MannWhitney Wilcoxon tests (for ranked data), and oneway multivariate analysis of variance. Options in MRPP also allow you to truncate distances to evaluate multiple clumping of data, establish an excess group, and select arc distances to compare circular distributions of grouped data. Multivariate data are commensurated (standardized) to a common scale but an option allows you to turn off commensuration. Commensuration can be done by using average Euclidean distance (default) or the variance/covariance matrix for the dependent variables. Multivariate medians and distance quantiles (MEDQ) are provided as estimates to be used in describing distributional changes detected by MRPP analyses.
mrpp
returns an object of either class MRPPObj
or EMRPPObj
.
The functions summary
as well as print
can be used to obtain a summary of the test.
Generic accessor functions pvalue
and ResampVals
(for MRPPObj
) can be used to obtain the pvalue and Monte Carlo resampled test statistic values respectively.
Mielke, P.W., Jr., and K.J. Berry. 2001. Permutation methods: A distance function approach. SpringerVerlag.
pvalue
, and ResampVals
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