Sensitivity analysis for several treatments at once

Runs regsen_breakdown() (or regsen_bounds()) once per candidate treatment and collects the breakdown points into one table. This is the applied question "which of my regressors would survive an unobservable, and which would not?", answered in a single call.

Usage

regsen_multi(
  formula,
  data,
  treatments,
  compare = NULL,
  fun = regsen_breakdown,
  ...
)

# S3 method for class 'regsensitivity_multi'
plot(x, base_size = 11, ...)

Arguments

formula

A model formula. Its right-hand side must contain every name in treatments. Which term appears first does not matter here, since each treatment is promoted in turn.

data

A data frame.

treatments

Character vector of variables to treat as the treatment in turn.

compare

Passed to the underlying analysis. A variable currently acting as the treatment is removed from compare for that row, since a variable cannot calibrate against itself.

fun

The analysis to run: regsen_breakdown() (default) or regsen_bounds().

...

Passed to fun, e.g. cbar, analysis, beta.

x

A regsensitivity_multi object.

base_size

Base font size, passed to theme_regsen().

Value

A data.frame of class regsensitivity_multi, one row per treatment, with columns treatment, estimate (the medium-regression coefficient), breakdown, and n. Rows where the analysis failed carry NA and an error column explaining why, rather than aborting the whole sweep.

Details

Each treatment is analysed in the same model: the variable of interest moves to the front of the formula and every other right-hand-side term stays a control, including the other candidate treatments. That is deliberate – dropping the others would change the specification and the breakdown points would no longer be comparable across rows.

Examples

# \donttest{
data(bfg2020)
w1 <- c("log_area_2010", "lat", "lon")
regsen_multi(
    avgrep2000to2016 ~ tye_tfe890_500kNI_100_l6 + log_area_2010 + lat + lon,
    data = bfg2020,
    treatments = c("tye_tfe890_500kNI_100_l6", "lat"),
    compare = w1, cbar = 1
)
#> 
#> Sensitivity across treatments
#> ------------------------------------------------------------
#>                 treatment estimate breakdown     n
#>  tye_tfe890_500kNI_100_l6    1.385    0.3749  2036
#>                       lat  -0.3266    0.9425  2036
# }