Skip to contents

Non-parametric Inference for SI (Agarwal et al. 2025)

Source: R/si.R
si_inference.Rd

Estimates SE and confidence intervals for the ATT via non-parametric cluster bootstrap or jackknife over control units. Works for both sharp and staggered SI fits. For staggered fits, bootstrap resamples each cohort's control pool independently, and jackknife uses a per-cohort LOO with delta-method variance aggregation.

Usage

si_inference(
  fit,
  method = c("bootstrap", "jackknife", "jackknife_global"),
  n_boot = 499L,
  level = 0.95,
  alternative = c("two.sided", "greater", "less"),
  seed = NULL
)

Arguments

fit

A coresynth object from scm_fit() with method = "si".

method

"bootstrap" (default) or "jackknife".

n_boot

Number of bootstrap replications (default 499L; ignored for jackknife).

level

Confidence level (default 0.95).

alternative

"two.sided" (default), "greater", or "less".

seed

RNG seed for reproducibility (default NULL).

Value

A list of class coresynth_inference.