Literature DB >> 30834430

Using Bounds to Compare the Strength of Exchangeability Assumptions for Internal and External Validity.

Alexander Breskin1, Daniel Westreich1, Stephen R Cole1, Jessie K Edwards1.   

Abstract

In the absence of strong assumptions (e.g., exchangeability), only bounds for causal effects can be identified. Here we describe bounds for the risk difference for an effect of a binary exposure on a binary outcome in 4 common study settings: observational studies and randomized studies, each with and without simple random selection from the target population. Through these scenarios, we introduce randomizations for selection and treatment, and the widths of the bounds are narrowed from 2 (the width of the range of the risk difference) to 0 (point identification). We then assess the strength of the assumptions of exchangeability for internal and external validity by comparing their contributions to the widths of the bounds in the setting of an observational study without random selection from the target population. We find that when less than two-thirds of the target population is selected into the study, the assumption of exchangeability for external validity of the risk difference is stronger than that for internal validity. The relative strength of these assumptions should be considered when designing, analyzing, and interpreting observational studies and will aid in determining the best methods for estimating the causal effects of interest.
© The Author(s) 2019. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  causal inference; external validity; internal validity; partial identification

Mesh:

Year:  2019        PMID: 30834430      PMCID: PMC6601532          DOI: 10.1093/aje/kwz060

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


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