Compute the between-group variances in weights

Identify variables along which groups may contribute heterogeneously to identification.

Usage

idid_grouping_var(reg, var_interest, grouping_vars, ...)

Arguments

reg

A regression object.

var_interest

A string. The name of the main variable of interest.

grouping_vars

A string vector of variable names or "everything". The set of variables to group weights by. If "everything" passed, group by each of the variables in the data set successively.

...

Additional elements to pass to the regression function when partialling out controls.

Value

A dataframe with 2 columns:

• grouping_var the names of grouping var

• between_var the between-group variation in weights

Details

Identify variables for which grouping by this variable yields the most heterogeneous between-groups differences in weights (i.e. the largest between-groups variance).

Examples

reg_ex <- ggplot2::txhousing |>
  lm(formula = log(sales) ~ median + listings + city + as.factor(date))

idid_grouping_var(reg_ex, "median", grouping_vars = c("city", "year", "month"))
#>   grouping_var  between_var
#> 2         year 0.0014294311
#> 1         city 0.0003418194
#> 3        month 0.0001321872

#We can now then explore the weights along the dimension with the largest
#variance: year
idid_viz_weights(reg_ex, "median", year)