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Blocking for Sequential Political Experiments.

Ryan T Moore1, Sally A Moore

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Political Analysis : an Annual Publication of the Methodology Section of the American Political Science Association
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Summary
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Sequential randomization methods using continuous covariates improve covariate balance in experiments where subjects enter over time. These novel approaches outperform complete randomization in simulations and real-world clinical trials.

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Area of Science:

  • Experimental Design
  • Statistical Methods
  • Political Science

Background:

  • Traditional experiments randomize all units simultaneously.
  • Sequential experiments often use complete randomization for trickling subjects.
  • Rich background data is frequently underutilized in sequential trials.

Purpose of the Study:

  • Develop sequential treatment assignment methods using continuous covariates.
  • Improve covariate balance in sequential experimental designs.
  • Compare novel methods against complete randomization.

Main Methods:

  • Sequential assignment based on continuous covariates.
  • Building on biased coin and minimization procedures.
  • Simulation studies and real-world clinical trial deployment.

Main Results:

  • Novel methods demonstrated superior covariate balance compared to complete randomization in simulations.
  • Successful deployment in a clinical trial highlighted practical advantages.
  • Evaluated performance in larger sequential political trials.

Conclusions:

  • Sequential blocking methods offer significant advantages for experiments with trickling subjects.
  • These methods enhance covariate balance and experimental efficiency.
  • Applicable across various fields including clinical and political science research.