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Using randomization tests to assess treatment effects in multiple-group interrupted time series analysis.

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  • 1Linden Consulting Group, LLC, San Francisco, California.

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Summary

Randomization tests offer a non-parametric alternative for interrupted time series analysis (ITSA), providing exact P values without strong assumptions. This method proved effective in evaluating California's Proposition 99, showing reduced cigarette sales.

Keywords:
balancebiascausal inferenceconfoundinginterrupted time series analysismatchingpermutation testsrandomization tests

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Area of Science:

  • Epidemiology
  • Biostatistics
  • Public Health Policy Evaluation

Background:

  • Interrupted time series analysis (ITSA) is a common method for evaluating interventions.
  • Parametric ITSA methods often rely on assumptions that may not hold, especially with small sample sizes.
  • Contrasting treated units with control groups enhances internal validity.

Purpose of the Study:

  • To introduce randomization tests as a non-parametric, distribution-free method for computing exact P values in multiple-group ITSA.
  • To evaluate the effectiveness of California's Proposition 99 in reducing cigarette sales using randomization tests and comparing them to a parametric approach.

Main Methods:

  • The study employed interrupted time series analysis (ITSA) to evaluate California's Proposition 99.
  • California (CA) was compared to Montana (MT) and Idaho (ID) as control states.
  • Randomization tests were used and their results contrasted with interrupted time series analysis regression (ITSAREG).

Main Results:

  • Both randomization tests and ITSAREG found Montana and Idaho to be comparable to California in the preintervention period.
  • Both methods indicated statistically significant lower cigarette sales in California during the postintervention period (P < 0.01).

Conclusions:

  • Randomization tests yielded P values comparable to ITSAREG, supporting the intervention's effect.
  • Randomization tests are a valuable, assumption-free complement or alternative to parametric methods in ITSA due to their flexibility.