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Related Experiment Videos

The compliance score as a regressor in randomized trials.

Marshall M Joffe1, Thomas R Ten Have, Colleen Brensinger

  • 1Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, 602 Blockley Hall, 423 Guardian Dr, Philadelphia, PA 19104-6021, USA. mjoffe@cceb.upenn.edu

Biostatistics (Oxford, England)
|August 20, 2003
PubMed
Summary

The compliance score in randomized trials measures randomization's effect on treatment. Using an identity link function allows valid inference on treatment effects, even with noncompliance, unlike nonlinear links.

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Area of Science:

  • Biostatistics
  • Clinical Trials Methodology
  • Epidemiology

Background:

  • Compliance score is a group-level pretreatment variable in randomized trials.
  • Individual-level compliance measures can lead to misleading inferences.
  • Understanding compliance is crucial for accurate treatment effect estimation.

Purpose of the Study:

  • To evaluate the role of the compliance score in randomized trials.
  • To determine how link functions affect the interpretation of compliance score models.
  • To assess the validity of inference under different compliance scenarios.

Main Methods:

  • Utilized the compliance score as a group-level pretreatment variable.
  • Analyzed models incorporating the compliance score as a regressor of interest.

Related Experiment Videos

  • Examined the impact of identity and nonlinear link functions on inference.
  • Applied methods to data from two distinct randomized trials.

    • Main Results:

    • The compliance score effectively measures randomization's impact on treatment received.
    • Identity link functions permit valid inference on treatment effects, even with nonrandom noncompliance.
    • Nonlinear link functions complicate the interpretation and validity of inference regarding treatment effects.
    • Illustrative data from two randomized trials support these findings.

    Conclusions:

    • The compliance score is a valuable tool for assessing treatment effects in randomized trials.
    • Identity link functions are recommended for robust inference in the presence of noncompliance.
    • Careful consideration of link functions is essential when using compliance scores in statistical models.