Loading…
The authors respond to "structural equation models and epidemiologic analysis"
Arlinghaus et al comment on Dr. VanderWeele's insightful commentary on their article on the use of structural equation modeling (SEM) as a tool for epidemiologic analysis. While they agree that it is important to weigh the benefits of SEM against the limitations posed by broad assumptions, ther...
Saved in:
Published in: | American journal of epidemiology 2012-10, Vol.176 (7), p.613-614 |
---|---|
Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | Arlinghaus et al comment on Dr. VanderWeele's insightful commentary on their article on the use of structural equation modeling (SEM) as a tool for epidemiologic analysis. While they agree that it is important to weigh the benefits of SEM against the limitations posed by broad assumptions, there is general consensus that an underlying theory about mechanisms is required, and ideally a model should be specified before the data are collected. VanderWeele states that oftentimes models are constructed on the basis of what researchers feel are important pathways and recommends including more pathways rather than fewer, leading to conservative control for confounding fit. While they acknowledge the need to control for confounding, commonly several models are in fact tested concurrently using SEM to critically evaluate the alternative models and to avoid the pitfall of simply confirming the researcher's preferred model. |
---|---|
ISSN: | 0002-9262 1476-6256 |
DOI: | 10.1093/aje/kws218 |