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Effect heterogeneity and variable selection for standardizing causal effects to a target population

  • Anders HuitfeldtEmail author
  • Sonja A. Swanson
  • Mats J. Stensrud
  • Etsuji Suzuki
METHODS

Abstract

The participants in randomized trials and other studies used for causal inference are often not representative of the populations seen by clinical decision-makers. To account for differences between populations, researchers may consider standardizing results to a target population. We discuss several different types of homogeneity conditions that are relevant for standardization: Homogeneity of effect measures, homogeneity of counterfactual outcome state transition parameters, and homogeneity of counterfactual distributions. Each of these conditions can be used to show that a particular standardization procedure will result in an unbiased estimate of the effect in the target population, given assumptions about the relevant scientific context. We compare and contrast the homogeneity conditions, in particular their implications for selection of covariates for standardization and their implications for how to compute the standardized causal effect in the target population. While some of the recently developed counterfactual approaches to generalizability rely upon homogeneity conditions that avoid many of the problems associated with traditional approaches, they often require adjustment for a large (and possibly unfeasible) set of covariates.

Keywords

Methodology Effect heterogeneity Generalizability External validity Standardization Effect measures 

Notes

Acknowledgements

The authors are grateful to Dr. Issa Dahabreh and two anonymous reviewers for suggestions that greatly improved the manuscript. Any remaining errors are our own.

Funding

The authors received no specific funding for this work. Dr. Stensrud is supported by the Research Council of Norway, Grant NFR239956/F20 - Analyzing clinical health registries: Improved software and mathematics of identifiability. Dr. Swanson is supported by NWO/ZonMw Veni Grant (91617066). Dr. Suzuki is supported by Japan Society for the Promotion of Science (KAKENHI Grant Numbers JP17K17898, JP15K08776, and JP18K10104) and The Okayama Medical Foundation. Dr. Huitfeldt was supported by the Effective Altruism Hotel Blackpool during revision of the manuscript.

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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Norwegian Institute of Public HealthOsloNorway
  2. 2.PharmacoEpidemiology and Drug Safety Research Group, Department of Pharmacy, and PharmaTox Strategic Initiative, Faculty of Mathematics and Natural SciencesUniversity of OsloOsloNorway
  3. 3.Department of EpidemiologyErasmus MCRotterdamNetherlands
  4. 4.Department of EpidemiologyHarvard T.H. Chan School of Public HealthBostonUSA
  5. 5.Department of BiostatisticsUniversity of OsloOsloNorway
  6. 6.Department of Epidemiology, Graduate School of Medicine, Dentistry and Pharmaceutical SciencesOkayama UniversityOkayamaJapan

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