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Permutation Inference via MSPE Ratio for SCM

Source: R/scm.R
mspe_ratio_pval.Rd

Computes the Abadie et al. (2010) / Abadie (2021) permutation p-value. For each control unit, a leave-one-out synthetic control is fitted.

Usage

mspe_ratio_pval(
  fit,
  mspe_threshold = 0,
  max_iter = 100L,
  tol = 1e-04,
  use_covariates = FALSE,
  alternative = c("two.sided", "greater", "less")
)

Arguments

fit

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

mspe_threshold

Minimum pre-treatment MSPE for including a control unit in the two-sided test. Ignored for one-sided tests. Default: 0 (no filtering).

max_iter

Passed to scm_placebo_cpp(). Default 100L.

tol

Passed to scm_placebo_cpp(). Default 1e-4.

use_covariates

If TRUE and the fit used predictor covariates, applies the same covariate spec to each placebo unit (R-level loop). Default FALSE (faster C++ outcomes-only placebos).

alternative

Direction of the alternative hypothesis: "two.sided" (default) uses the MSPE ratio statistic; "greater" tests whether the treatment increased the outcome; "less" tests whether the treatment decreased the outcome. One-sided tests use the signed ATT as the test statistic.

Value

A list with:

  • p_value: Permutation p-value between 0 and 1

  • mspe_ratio_treated: MSPE_post / MSPE_pre for the treated unit (two.sided only)

  • mspe_ratios_all: Named numeric vector (treated first, then controls); two.sided only

  • placebo_effects: Named N_co-vector of placebo ATT estimates

  • treated_effect: ATT estimate for the treated unit

  • n_placebo_used: Number of control units used

Details

When alternative = "two.sided" (default), the test statistic is the post/pre MSPE ratio, following Abadie et al. (2010). When alternative = "greater" or "less", the test statistic is the signed average post-treatment gap (ATT), giving a one-sided permutation test as recommended by Abadie (2021) S.3.5 for improved power when the direction of the treatment effect is known.