Description Usage Arguments Details
Computes a oneway analysis of variance with post hoc tests.
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outcomes 
The outcome variables. 
predictor 
The factor representing the groups. 
subset 
An optional vector specifying a subset of observations to be
used in the fitting process, or, the name of a variable in 
weights 
An optional vector of sampling weights, or, the name or, the
name of a variable in 
robust.se 
Computes standard errors that are robust to violations of the assumption of constant variance. This parameter is ignored if weights are applied (as weights already employ a sandwich estimator). 
missing 
How missing data is to be treated in the ANOVA. Options:

show.labels 
Shows the variable labels, as opposed to the labels, in the outputs, where a variables label is an attribute (e.g., attr(foo, "label")). 
seed 
The random number seed used when evaluating the multivariate tdistribution. 
p.cutoff 
The alpha level to be used in testing. 
binary 
Automatically converts nonordered factors to dummycoded (binary indicator) variables. 
pillai 
If 
fdr 
If 
return.all 
If 
... 
Other parameters to be passed to 
By default, the overall pvalue is computed as the smallest pvalue in any cell following application of the
False Discovery Rate correction to the pvalues. If thefdr
is set to FALSE
, the correction is not applied, which means
that the overall pvalue is the smallest of the uncorrected pvalues, and, additionally, the pvalues for each row
are from the OneWayANOVA Ftests.
Tests are twosided, comparing to the Grand Mean (i.e., "To mean" in OneWayANOVA).
Additional detail about the other parameters can be found in OneWayANOVA
.
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