Description Usage Arguments Details
View source: R/multiplemeans.R
Compares means of multiple outcomes on a categorical predictor.
1 2 3 4 5 
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 
correction 
The multiple comparison adjustment method: 
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. 
title 
The title to appear in the output. 
subtitle 
The footer to appear in the output. 
footer 
The footer to appear in the output. 
... 
Other parameters to be passed to 
Computes multiple ANOVAs.
Conducts multiple OneWayANOVA
s, and puts them in a list. If correction
is
"Table FDR"
, the false discovery rate correction is applied across the entire table. All
other corrections are performed within rows. Additional detail about the other parameters can be found in OneWayANOVA
.
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