Extracts the meta information on all the models contained in a fixest_multi estimation.
Arguments
- x
A
fixest_multiobject, obtained from afixestestimation leading to multiple results.- simplify
Logical, default is
FALSE. The default behavior is to display all the meta information, even if they are identical across models. By usingsimplify = TRUE, only the information with some variation is kept.
Value
It returns a data.frame whose first column (named id) is the index of the models and
the other columns contain the information specific to each model (e.g. which sample,
which RHS, which dependent variable, etc).
Examples
# a multiple estimation
base = setNames(iris, c("y", "x1", "x2", "x3", "species"))
est = feols(y ~ csw(x.[, 1:3]), base, fsplit = ~species)
# All the meta information
models(est)
#> id sample.var sample rhs
#> 1 1 species Full sample x1
#> 2 2 species Full sample x1 + x2
#> 3 3 species Full sample x1 + x2 + x3
#> 4 4 species setosa x1
#> 5 5 species setosa x1 + x2
#> 6 6 species setosa x1 + x2 + x3
#> 7 7 species versicolor x1
#> 8 8 species versicolor x1 + x2
#> 9 9 species versicolor x1 + x2 + x3
#> 10 10 species virginica x1
#> 11 11 species virginica x1 + x2
#> 12 12 species virginica x1 + x2 + x3
# Illustration: Why use simplify
est_sub = est[sample = 2]
models(est_sub)
#> id sample.var sample rhs
#> 4 1 species setosa x1
#> 5 2 species setosa x1 + x2
#> 6 3 species setosa x1 + x2 + x3
models(est_sub, simplify = TRUE)
#> id rhs
#> 4 1 x1
#> 5 2 x1 + x2
#> 6 3 x1 + x2 + x3