Mediation with External Summary Statistic Information (MESSI) Article Swipe
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2306.17347
Environmental health studies are increasingly measuring endogenous omics data ($\boldsymbol{M}$) to study intermediary biological pathways by which an exogenous exposure ($\boldsymbol{A}$) affects a health outcome ($\boldsymbol{Y}$), given confounders ($\boldsymbol{C}$). Mediation analysis is frequently carried out to understand such mechanisms. If intermediary pathways are of interest, then there is likely literature establishing statistical and biological significance of the total effect, defined as the effect of $\boldsymbol{A}$ on $\boldsymbol{Y}$ given $\boldsymbol{C}$. For mediation models with continuous outcomes and mediators, we show that leveraging external summary-level information on the total effect improves estimation efficiency of the natural direct and indirect effects. Moreover, the efficiency gain depends on the asymptotic partial $R^2$ between the outcome ($\boldsymbol{Y}\mid\boldsymbol{M},\boldsymbol{A},\boldsymbol{C}$) and total effect ($\boldsymbol{Y}\mid\boldsymbol{A},\boldsymbol{C}$) models, with smaller (larger) values benefiting direct (indirect) effect estimation. We robustify our estimation procedure to incongenial external information by assuming the total effect follows a random distribution. This framework allows shrinkage towards the external information if the total effects in the internal and external populations agree. We illustrate our methodology using data from the Puerto Rico Testsite for Exploring Contamination Threats, where Cytochrome p450 metabolites are hypothesized to mediate the effect of phthalate exposure on gestational age at delivery. External information on the total effect comes from a recently published pooled analysis of 16 studies. The proposed framework blends mediation analysis with emerging data integration techniques.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2306.17347
- https://arxiv.org/pdf/2306.17347
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4383046438
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4383046438Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2306.17347Digital Object Identifier
- Title
-
Mediation with External Summary Statistic Information (MESSI)Work title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-06-28Full publication date if available
- Authors
-
Jonathan Boss, Wei Hao, Amber L. Cathey, Barrett M. Welch, Kelly K. Ferguson, John D. Meeker, Jian Kang, Bhramar MukherjeeList of authors in order
- Landing page
-
https://arxiv.org/abs/2306.17347Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2306.17347Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2306.17347Direct OA link when available
- Concepts
-
Mediation, Confounding, Physics, Combinatorics, Statistics, Mathematics, Political science, LawTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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