| plot.assumptions_cmpoutput {micompr} | R Documentation |
Plot p-values for testing the assumptions of the parametric tests used in output comparison
Description
Plot method for objects of class assumptions_cmpoutput
containing p-values produced by testing the assumptions of the
parametric tests used for comparing an output.
Usage
## S3 method for class 'assumptions_cmpoutput'
plot(x, ...)
Arguments
x |
Objects of class |
... |
Extra options passed to |
Details
Several bar plots are presented, showing the p-values yielded by the
Shapiro-Wilk (shapiro.test) and Royston tests
(mvn) for univariate and multivariate normality,
respectively, and for the Bartlett (bartlett.test) and
Box's M (boxM) for testing homogeneity of variances
and of covariance matrices, respectively. The following bar plots are shown:
One bar plot for the p-values of the Bartlett test, one bar (p-value) per individual principal component.
-
s bar plots for p-values of the Shapiro-Wilk test, where s is the number of groups being compared. Individual bars in each plot are associated with a principal component.
-
t bar plot for the p-values of the Royston test with s bars each, where t is the number of unique MANOVA tests performed (one per requested explained variances) and s is the number of groups being compared. These plots will not show if there is only one principal component being considered.
One plot for the p-values of the Box's M test, one bar (p-value) per unique MANOVA tests performed (one per requested explained variances).
Value
None.
Examples
# Create a cmpoutput object from the provided datasets
cmp <- cmpoutput("All", 0.9, pphpc_ok$data[["All"]], pphpc_ok$obs_lvls)
# Display a bar plot with the p-values of the assumptions for the parametric
# tests performed in cmp
plot(assumptions(cmp))