Usage
run_model(outcome, block1, ..., dataset, type = "gaussian", assumptions.check = T, outliers.check = "significant", transform.outcome = F)
Arguments
outcome
The dependent variable of the hierarchical model
block1
A character vector, with names of variables. The first block of
independent variables.
...
A character vector, with names of variables. Subsequent blocks of
independent variables.
dataset
A data frame containing variables refered to in
formulas, passed to data argument of lm
type
Family argument to pass to glm. Specify "binomial" for
binary logistic regression models.
assumptions.check
Boolean, if TRUE, then assumption checks are run and
output is produced. If FALSE, only model summary and coefficient tables are
produced.
outliers.check
Determines how many observations to display for
outliers check. Default is significant observations. "All" shows all
residual and Cook's D values.
transform.outcome
A boolean. If TRUE, a variable transformation of the
outcome is substituted in the final model if outcome is non-normal. NOT
IMPLEMENTED YET.