Data · collection · 2015
Causal Models for Mediation Analysis: An Introduction to Structural Mean Models
Listed in DataCite
Mediation analyses are critical to understanding why behavioral interventions work.
Description
To yield a causal interpretation, common mediation approaches must make an assumption of “sequential ignorability.” The current article describes an alternative approach to causal mediation called structural mean models (SMMs). A specific SMM called a rank-preserving model (RPM) is introduced in the context of an applied example.
Particular attention is given to the assumptions of both approaches to mediation. Applying both mediation approaches to the college student drinking data yield notable differences in the magnitude of effects. Simulated examples reveal instances in which the traditional approach can yield strongly biased results, whereas the RPM approach remains unbiased in these cases.
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At the same time, the RPM approach has its own assumptions that must be met for correct inference, such as the existence of a covariate that strongly moderates the effect of the intervention on the mediator and no unmeasured confounders that also serve as a moderator of the effect of the intervention or the mediator on the outcome. The RPM approach to mediation offers an alternative way to perform mediation analysis when there may be unmeasured confounders.
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Where it is published
- Repository landing page tandf.figshare.com/collections/Causal_Models_for_Mediation_Analysis_An_Introducti… ↗
landing page · from DataCite
- Repository landing page tandf.figshare.com/collections/Causal_Models_for_Mediation_Analysis_An_Introducti… ↗
landing page · from DataCite
- DOI doi.org/10.6084/m9.figshare.c.2087264 ↗
DOI / persistent id · from DataCite
- DOI doi.org/10.6084/m9.figshare.c.2087264.v1 ↗
DOI / persistent id · from DataCite
Documentation and papers
Catalogue records · 4
- DataCite API api.datacite.org/dois/10.6084/m9.figshare.c.2087264.v1 ↗
metadata API · from DataCite
- DataCite API api.datacite.org/dois/10.6084/m9.figshare.c.2087264 ↗
metadata API · from DataCite
- DataCite Commons commons.datacite.org/doi.org/10.6084/m9.figshare.c.2087264.v1 ↗
catalogue entry · from DataCite
- DataCite Commons commons.datacite.org/doi.org/10.6084/m9.figshare.c.2087264 ↗
catalogue entry · from DataCite
Topics
- Stated by source
- Mathematics · Mathematics
- From keywords
- Life Sciences · Life Sciences · Mathematics & Statistics · Mathematics & Statistics
Provenance · 2 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| DataCite | 10.6084/m9.figshare.c.2087264 | 14 d ago | JSON v1 |
| DataCite | 10.6084/m9.figshare.c.2087264.v1 | 14 d ago | JSON v1 |
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|---|---|---|---|
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| concepts[field].fos:mathematics | source · DataCite | connector:datacite@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · DataCite | vocabulary-mapper@1.0.0 | keywords['Biological Sciences'] |
| concepts[field].local:field:life-sciences | mapping · DataCite | vocabulary-mapper@1.0.0 | keywords['Biological Sciences'] |
| concepts[field].local:field:mathematics-statistics | mapping · DataCite | vocabulary-mapper@1.0.0 | keywords['Mathematics'] |
| concepts[field].local:field:mathematics-statistics | mapping · DataCite | vocabulary-mapper@1.0.0 | keywords['Mathematics'] |
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