cic() gains a discrete argument (default FALSE). When discrete = TRUE,
the discrete CIC estimator of Theorem 4.1 of Athey and Imbens (2006) is used
instead of the continuous estimator (Theorem 3.1). The discrete variant
correctly handles outcomes with mass points (e.g., integer-valued durations)
by integrating the counterfactual over the corresponding quantile band rather
than applying a point mapping. Analytic standard errors are suppressed with an
informative message when discrete = TRUE, as Theorem 5.1 assumes a
continuous distribution; bootstrap inference is recommended instead.
print.cic() now displays which estimator was used
(continuous (Theorem 3.1) or discrete (Theorem 4.1)).
ecdf_eval_left(), integral_quantile(),
and compute_cic_cf() to support the discrete CIC estimator.Any scripts or data that you put into this service are public.
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