Assertion: regression's variable | /r/HasProperty | included
Facets:
Source sentences:
text: Bidirectional elimination is a combination of the first two methods that tests which variables should be included or excluded.
text: When the extra variable is included, the data always have the option of giving it an estimated coefficient of zero, leaving the predicted values and the R2 unchanged.
text: In this case, it often doesn't make sense to include only a few levels of the covariate; the group lasso can ensure that all the variables encoding the categorical covariate are either included or excluded from the model together.
text: · Only the meaningful variables should be included.
text: Bidirectional elimination, a combination of the above, testing at each step for variables to be included or excluded.
text: Is the model significantly improved when these variables are included?