I'm doing a difference-in-differences (DiD) on a small sample (N=6, T=24) and I'm therefore interested in running permutation tests as several simulation studies recommend this (e.g. Rokicki et al. 2018).
However, I seem to run into some complications using Stata's -permute- and the user-written -ritest-. The documentation on the commands does not describe the warning messages(may be that it's clear but I'm just missing out as I'm new to permutation).
Specifically, when using the following DiD-model wit -ritest-, where intervention is binary treatment variable and post_17Q1 is binary post-variable,
Code:
ritest intervention _b[1.intervention#1.post_17Q1], reps(50) strata(region) /// cluster(intervention): xtreg suicideRate i.intervention##i.post_17Q1, fe cluster(region)
Code:
Warning: some strata contain no variation in intervention
Code:
Warning: 100% of the resampled realizations for _pm_1 are exactly identical to original value
Code:
permute intervention _b[1.intervention#1.post_17Q1], /// reps(50): xtreg suicideRate i.intervention##i.post_17Q1, fe cluster(region)
Code:
Monte Carlo permutation results Number of obs = 144 command: xtreg suicideRate i.intervention##i.post_17Q1, fe cluster(region) _pm_1: _b[1.intervention#1.post_17Q1] permute var: intervention ------------------------------------------------------------------------------ T | T(obs) c n p=c/n SE(p) [95% Conf. Interval] -------------+---------------------------------------------------------------- _pm_1 | -.8296676 0 0 . . . . ------------------------------------------------------------------------------ Note: Confidence interval is with respect to p=c/n. Note: c = #{|T| >= |T(obs)|} Note: Missing values observed in permutation replicates.
References:
Rokicki et al. 2018. Inference with Difference-in-Differences With a Small Number of Groups: A Review, Simulation Study, and Empirical Application Using SHARE Data.
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