Evaluating the Role of High‐Dimensional Proxy Data in Confounding Adjustment in Multiple Sclerosis Research: A Case Study
Incorporating high-dimensional proxy information resulted in minor variations in effect estimates compared to traditional covariate adjustment. These findings suggest that the impact of residual confounding in the question under consideration may be modest. Further research should explore additional data dimensions and replicate these findings across different datasets.
Authors
- Helen Tremlett (ORCID: https://orcid.org/0000-0001-5804-2535)
- Huah Shin Ng (ORCID: https://orcid.org/0000-0001-8381-5253)
- Mohammad Ehsanul Karim (ORCID: https://orcid.org/0000-0002-0346-2871)
- Feng Zhu (ORCID: https://orcid.org/0000-0002-8468-183X)
- Hanna A. Frank (ORCID: https://orcid.org/0000-0002-3314-8154)
- Md. Belal Hossain (ORCID: https://orcid.org/0000-0003-4603-863X)
Institutions
- University of British Columbia (CA)
- Flinders University (AU)
- SA Health (AU)
- Centre for Advancing Health Outcomes (CA)
Publication Details
- Journal
- Pharmacoepidemiology and Drug Safety
- Published
- 2025-02-01
- DOI
- https://doi.org/10.1002/pds.70112
- Citations
- 3
- Primary Topic
- Multiple Sclerosis Research Studies
- Type
- article
- Field-Weighted Citation Impact
- 4.41
Funders
- Multiple Sclerosis Society of Canada
- Canadian Institutes of Health Research