OneWayMANOVA | R Documentation |
OneWayMANOVA
Computes a one-way analysis of variance with post hoc tests.
OneWayMANOVA(
outcomes,
predictor,
subset = NULL,
weights = NULL,
robust.se = FALSE,
missing = "Exclude cases with missing data",
show.labels = FALSE,
seed = 1223,
p.cutoff = 0.05,
binary = FALSE,
pillai = FALSE,
fdr = TRUE,
return.all = FALSE,
...
)
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 t-distribution. |
p.cutoff |
The alpha level to be used in testing. |
binary |
Automatically converts non-ordered factors to dummy-coded (binary indicator) variables. |
pillai |
If |
fdr |
If |
return.all |
If |
... |
Other parameters to be passed to |
By default, the overall p-value is computed as the smallest p-value in any cell following application of the
False Discovery Rate correction to the p-values. If thefdr
is set to FALSE
, the correction is not applied, which means
that the overall p-value is the smallest of the uncorrected p-values, and, additionally, the p-values for each row
are from the OneWayANOVA F-tests.
Tests are two-sided, 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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