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Factorial Designs, Model Selection, and (Incorrect) Inference in Randomized Experiments

Serie

  • CESifo Working Paper

Resumen

  • Factorial designs are widely used for studying multiple treatments in one experiment. While “long” model t-tests provide valid inferences, “short” model t-tests (ignoring interactions) yield higher power if interactions are zero, but incorrect inferences otherwise. Of 27 factorial experiments published in top-5 journals (2007–2017), 19 use the short model. After including all interactions, over half their results lose significance. Modest local power improvements over the long model are possible, but with lower power for most values of the interaction. If interactions are not of interest, leaving the interaction cells empty yields valid inferences and global power improvements.

fecha de publicación

  • 2020

Líneas de investigación

  • Cross-cut Designs
  • Factorial Designs
  • Field Experiments
  • Randomized Controlled Trial

Issue

  • 8137