View source: R/multipleanovas.R
MultipleANOVAs | R Documentation |
MultipleANOVAs
Computes 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 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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