Visualize changes in point estimate and s.e. when dropping observations

Make a faceted line graph describing the percentage variation of the point estimate and s.e. of interest as a function of the proportion of observations dropped.

Usage

idid_viz_drop_change(
  reg,
  var_interest,
  threshold_change = 0.05,
  search_step = 0.05,
  search_start = search_step,
  search_end = 1 - search_step,
  color = "#300D49",
  ...
)

Arguments

reg

A regression object.

var_interest

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

threshold_change

A double (between 0 and 1). The change threshold in estimate and s.e. when dropping observations.

search_step

A double (between 0 and 1). The additional proportion of observations to drop in each iteration of the loop.

search_start

A numeric (between 0 and 1). Proportion of observation to drop in the first step of the loop in idid_contrib_threshold.

search_end

A numeric (between 0 and 1). Proportion of observation to drop in the last step of the loop in idid_contrib_threshold.

color

A string. Color of the graph.

...

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

Value

A ggplot2 object.

The name of the facet variable is measure.

Examples

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

idid_viz_drop_change(reg_ex, "median", search_end = 0.6)