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How to achieve model-robust inference in stepped wedge trials with model-based methods?

Bingkai Wang1, Xueqi Wang2,3, Fan Li2,4

  • 1Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI 48109, United States.

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|November 5, 2024
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Summary

Model-based analysis of stepped wedge designs can provide consistent estimation of treatment effects, even with a misspecified working model. Correctly specifying the treatment effect structure is key for accurate results in stepped wedge cluster randomized trials.

Keywords:
causal inferencecluster randomized trialcovariate adjustmentestimandsmodel misspecificationtime-varying treatment effect

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Area of Science:

  • Biostatistics
  • Epidemiology
  • Clinical Trials

Background:

  • Stepped wedge designs are increasingly used in cluster randomized trials.
  • Model-based analysis is standard for evaluating treatment effects in these designs.
  • Properties of these analyses under model misspecification are not well understood.

Purpose of the Study:

  • To investigate the conditions under which model-based methods for stepped wedge designs provide consistent estimation of marginal treatment effects.
  • To determine the impact of working model misspecification on the validity of these analyses.
  • To identify requirements for robust inference.

Main Methods:

  • Focus on linear mixed models and generalized estimating equations with various working correlation structures.
  • Theoretical analysis of consistency for nonparametric marginal treatment effect estimands.
  • Use of sandwich variance estimators and g-computation for robust inference.

Main Results:

  • Consistency for nonparametric estimands generally requires a correctly specified treatment effect structure.
  • Other aspects of the working model (covariates, random effects, error distribution) can be misspecified.
  • Sandwich variance estimators provide valid inference; g-computation is needed for non-identity link functions or ratio estimands.

Conclusions:

  • Model-based analysis of stepped wedge designs can be robust to certain types of model misspecification.
  • Correct specification of the treatment effect is crucial for valid estimation.
  • The findings offer guidance for analyzing stepped wedge trials and ensuring reliable treatment effect estimation.