A simulated dataset with a binary instrument, a binary treatment with
two-sided noncompliance, and continuous, positive, and binary outcome
variables, designed to exercise every model family supported by
drlate(). The complier average treatment effect (LATE) used in the
data-generating process is 0.5. The treatment is genuinely endogenous
(compliance type shifts the baseline outcome, so naive OLS is biased
upward) and the instrument is only conditionally valid (its propensity
depends on age and educ, so the raw Wald ratio is biased too).
Format
A data frame with 2,000 rows and 7 variables:
- lwage
continuous outcome
- kwage
positive outcome (for Poisson models),
exp(lwage / 2)- hijob
binary outcome (for logit models)
- nvstat
binary treatment
- rsncode
binary instrument
- age
continuous covariate
- educ
factor covariate with levels
hs,college,graduate