simulate_data {pensynth}

Simulate synthetic control data

Description

This function simulates a basic form of synthetic control data, mainly for testing purposes. This

Usage

simulate_data(
  N_donor = 50,
  N_covar = 5,
  N_pre = 12,
  N_post = 6,
  N_nonzero = 4,
  treatment_effect = 1,
  sd_resid_X1 = 0.1,
  sd_resid_Z1 = 0.1,
  sd_resid_Y1 = 0.1
)

Arguments

N_donor

number of donors

N_covar

number of covariates

N_pre

number of pre-intervention timepoints

N_post

number of post-intervention timepoints

N_nonzero

number of true nonzero weights

treatment_effect

the size of the true treatment effect

sd_resid_X1

the residual standard deviation of X1

sd_resid_Z1

the residual standard deviation of Z1

sd_resid_Y1

the residual standard deviation of Y1

Details

Note that treatment effect can be a single number, but it may also be a vector of length N_post, indicating the effect size at each post-intervention measurement occasion.

Value

A list with the following elements

• w the true unit weights

• X0 the donor unit covariates

• X1 the treated unit covariates

• Z0 the donor unit pre-intervention outcomes

• Z1 the treated unit pre-intervention outcomes

• Y0 the donor unit post-intervention outcomes

• Y1 the treated unit post-intervention outcomes

See Also

pensynth(), cv_pensynth(), placebo_test()

Examples

# simulate data with an effect of 0.8 SD
dat <- simulate_data(treatment_effect = 0.8)

plot(
  NA,
  ylim = c(-3, 3),
  xlim = c(1, 18),
  main = "Simulated data",
  ylab = "Outcome value"
)
for (n in 1:ncol(dat$Z0))
  lines(1:18, c(dat$Z0[, n], dat$Y0[, n]), col = "grey")
lines(1:18, c(dat$Z1, dat$Y1))
lines(1:18, rbind(dat$Z0, dat$Y0) %*% dat$w, lty = 2)
abline(v = length(dat$Z1) + 0.5, lty = 3)
legend(
  x = "bottomleft",
  legend = c(
    "Donor units",
    "Treated unit",
    "True synth. control",
    "Intervention time"
  ),
  lty = c(1, 1, 2, 3),
  col = c("grey", "black", "black", "black")
)