explainedVariance {MEAL} | R Documentation |
Using a data.frame as input, calculates the R2 between a dependent variable and some independent variables. Base adjusting by covariates can also be used.
explainedVariance(data, num_mainvar = 1, num_covariates = 0, variable_label = NULL)
data |
Data.frame containing the dependent variable in the first column. |
num_mainvar |
Numerical with the number of variables that should be grouped. They should be at the beggining. |
num_covariates |
Numerical with the number of variables that should be considered as covariates. Covariates variables must be at the end. |
variable_label |
Character with the name of the main variable in the results. |
explainedVariance
computes R2 via linear models. The first column
is considered to be the dependent variable. Therefore, a lineal model will be
constructed for each of the remaining variables. In case that covariates
were included, they will be included in all the models and, in addition, a model
containing only the covariates will be returned.
Some variables can be grouped in the models to assess their effect together.
Numeric vector with the R2 explained by each of the variables.
data(mtcars) R2 <- explainedVariance(mtcars) R2