plac.dist: Plot the distribution of placebo samples for synthetic...

In bcastanho/SCtools: Extensions for Synthetic Controls Analysis

Plot the distribution of placebo samples for synthetic control analysis with multiple treated units.

Description

Takes the output object of multiple.synth creates a distribution of placebo average treatment effects, to test the significance of the observed ATE. Does so by sampling k placebos (where k = the number of treated units) nboots times, and calculating the average treatment effect of the k placebos each time.

Usage

plac.dist(multiple.synth, nboots = 500)

plac_dist(multiple.synth, nboots = 500)

Arguments

multiple.synth

multiple.synth

An object returned by the function multiple.synth

nboots

Number of bootstrapped samples of placebos to take. Default is 500. It should be higher for more reliable inference.

Value

p

The plot.

att.t

The observed average treatment effect.

df

Dataframe where each row is the ATT for one bootstrapped placebo sample, used to build the distribution plot.

p.value

Proportion of bootstrapped placebo samples ATTs which are more extreme than the observed average treatment effect. Equivalent to a p-value in a two-tailed test.

Examples

## Not run: 
## Using the toy data from Synth:
library(Synth)
data(synth.data)
set.seed(42)
## Run the function similar to the dataprep() setup:
multi <- multiple.synth(foo = synth.data,
                       predictors = c("X1", "X2", "X3"),
                       predictors.op = "mean",
                       dependent = "Y",
                       unit.variable = "unit.num",
                       time.variable = "year",
                       treatment.time = 1990,
                       special.predictors = list(
                         list("Y", 1991, "mean"),
                         list("Y", 1985, "mean"),
                         list("Y", 1980, "mean")
                       ),
                       treated.units = c(2,7),
                       control.units = c(29, 13, 17, 32),
                       time.predictors.prior = c(1984:1989),
                       time.optimize.ssr = c(1984:1990),
                       unit.names.variable = "name",
                       time.plot = 1984:1996, gen.placebos = TRUE, Sigf.ipop = 2,
                       strategy = 'multicore' )

## Plot with the average path of the treated units and the average of their
## respective synthetic controls:

multi$p

## Bootstrap the placebo units to get a distribution of placebo average
## treatment effects, and plot the distribution with a vertical line 
## indicating the actual ATT:

att.test <- plac.dist(multi)
att.test$p

## End(Not run)

bcastanho/SCtools documentation built on June 4, 2023, 6:28 a.m.