rbmi_ancova_single {junco} | R Documentation |
Implements an Analysis of Covariance (ANCOVA)
Description
Performance analysis of covariance. See rbmi_ancova()
for full details.
Usage
rbmi_ancova_single(
data,
outcome,
group,
covariates,
weights = c("counterfactual", "equal", "proportional_em", "proportional")
)
Arguments
data |
A |
outcome |
string, the name of the outcome variable in |
group |
string, the name of the group variable in |
covariates |
character vector containing the name of any additional covariates to be included in the model as well as any interaction terms. |
weights |
Character, either |
Details
-
group
must be a factor variable with only 2 levels. -
outcome
must be a continuous numeric variable.
Value
a list containing var
with variance estimates as well as
trt_*
and lsm_*
entries. See rbmi_ancova()
for full details.
See Also
Examples
iris2 <- iris[iris$Species %in% c("versicolor", "virginica"), ]
iris2$Species <- factor(iris2$Species)
rbmi_ancova_single(iris2, "Sepal.Length", "Species", c("Petal.Length * Petal.Width"))