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Sharpening bounds on principal effects with covariates.

Dustin M Long1, Michael G Hudgens

  • 1Department of Biostatistics, West Virginia University, Morgantown, West Virginia, 26506-9190, U.S.A.

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Adjusting for baseline covariates can sharpen bounds on treatment effects in randomized studies, reducing bias from post-randomization variables. This method significantly narrowed bounds in an HIV prevention study.

Keywords:
BoundsCausal effectsPartial identifiabilityPotential outcomesPrincipal strata

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Area of Science:

  • Biostatistics
  • Epidemiology
  • Clinical Trials

Background:

  • Selection bias in randomized studies can arise from post-randomization variables.
  • Principal strata offer a framework for estimating treatment effects, but principal effects are often unidentifiable.
  • Identifiable bounds on principal effects may be too wide to be informative.

Purpose of the Study:

  • To investigate methods for improving the precision of bounds on principal effects.
  • To assess the impact of adjusting for baseline covariates on the width of these bounds.
  • To provide conditions under which adjusted bounds are sharper than unadjusted bounds.

Main Methods:

  • Developed a method to adjust bounds on principal effects using a categorical baseline covariate.
  • Derived necessary and sufficient conditions for improved bound sharpness.
  • Applied the method to data from a mother-to-child HIV transmission prevention study.

Main Results:

  • Adjusted bounds are never wider than unadjusted bounds.
  • Demonstrated conditions for achieving sharper bounds.
  • In an HIV prevention study, adjusted bounds were 63% narrower than unadjusted bounds when using low birth weight as a covariate.

Conclusions:

  • Adjusting for baseline covariates is a valuable strategy to improve the informativeness of bounds on principal effects.
  • This approach can mitigate selection bias in the presence of unidentifiable principal effects.
  • The findings have implications for causal inference in clinical trials and observational studies.