View source: R/multipleanovas.R
| MultipleANOVAs | R Documentation |
MultipleANOVAsComputes multiple ANOVAs.
MultipleANOVAs(
dependents,
independent,
subset = NULL,
weights = NULL,
compare = "To mean",
correction = "Table FDR",
robust.se = FALSE,
alternative = "Two-sided",
missing = "Exclude cases with missing data",
show.labels = FALSE,
seed = 1223,
p.cutoff = 0.05,
data = NULL,
...
)
dependents |
The outcome variables. |
independent |
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 |
compare |
One of |
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). |
alternative |
The alternative hypothesis: "Two sided", "Greater", or "Less". The main application of this is when Compare us set 'To first' (e.g., if testing a new product, where the purpose is to work out of the new product is superior to an existing product, "Greater" would be chosen). |
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 t-distribution. |
p.cutoff |
The alpha level to be used in testing. |
data |
An optional |
... |
Other parameters to be passed to |
Conducts multiple OneWayANOVAs, 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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