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What random assignment does and does not do.

Merton S Krause1, Kenneth I Howard

  • 1Northwestern University, USA. msk514@northwestern.edu

Journal of Clinical Psychology
|June 17, 2003
PubMed
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Random assignment in clinical trials minimizes confounding from patient characteristics, but cannot fully eliminate it. Unmeasured variables and their interactions with treatments still pose risks to internal validity.

Area of Science:

  • Clinical Trials Methodology
  • Biostatistics
  • Epidemiology

Background:

  • Random assignment is a cornerstone of experimental design to minimize bias.
  • Confounding variables can impact the interpretation of treatment effects.
  • Unmeasured patient characteristics and their interactions pose challenges to internal validity.

Purpose of the Study:

  • To evaluate the extent to which random assignment mitigates confounding by unknown patient characteristics.
  • To explore the persistent threat of unmeasured variable interactions in randomized studies.

Main Methods:

  • Stochastic analysis of random assignment in experimental settings.
  • Theoretical consideration of confounding in the presence of unmeasured variables.

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Main Results:

  • Random assignment tends to minimize confounding with increasing sample size or replications.
  • Complete avoidance of confounding by unknown patient characteristics is unlikely.
  • Confounding by unmeasured Patient Variable x Treatment Variable interactions remains a significant concern.

Conclusions:

  • While random assignment reduces confounding, it does not eliminate it entirely.
  • Internal validity depends not only on the degree of confounding but also on the causal power of confounding variables.
  • Careful consideration of potential unmeasured confounders and interactions is crucial for robust clinical trial interpretation.