pseudostudy1

<p>Example data set in a two-way layout without
effects (in terms of disribution) by factors "treatment" and "age".
In constrast to the 'pseudostudy2' data set the number of factorial
levels is low while the number of observations per factor level combination is
large.</p>

datasets

Analysis of multivariate data with two-way completely randomized
factorial design. The analysis is based on fully nonparametric, rank-based
methods and uses test statistics based on the Dempster's ANOVA, Wilk's Lambda,
Lawley-Hotelling and Bartlett-Nanda-Pillai criteria. The multivariate
response is allowed to be ordinal, quantitative, binary or a mixture of the
different variable types. The package offers two functions performing the
analysis, one for small and the other for large sample sizes. The underlying methodology
is largely described in Bathke and Harrar (2016) <doi:10.1007/978-3-319-39065-9_7> and in
Munzel and Brunner (2000) <doi:10.1016/S0378-3758(99)00212-8> and in
Kiefel and Bathke (2022) <doi:10.1515/stat-2022-0112>.

Maximilian Kiefel

nparMD

Nonparametric Analysis of Multivariate Data in Factorial Designs

pseudostudy1 function

<p>pseudostudy consists of 56 cases (rows) and 5 variables where
'treatment'('age') is considered to be the explanatory factor 'A'('B') and
the variables resp1, resp2. resp3 form the response vector.</p>

pseudostudy1: pseudostudy dataset 1

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Examples