The next generation of regression standardization with the R package stdReg2
Regression standardization is a useful tool for performing causal inference in epidemiology. We have updated the R package stdReg to stdReg2 to be more user-friendly, flexible, and to include two new functionalities, a generalized linear model-based double-robust method and regression standardization for the restricted mean survival. The old package stdReg will continue to function, but new users may find the upgraded version easier to use. We highlight the improvements and implementation in this article. Keywords: average treatment effect, causal inference, regression standardization, statistical software.
Authors
- Erin E. Gabriel (ORCID: https://orcid.org/0000-0002-0504-8404)
- Arvid Sjölander (ORCID: https://orcid.org/0000-0001-5226-6685)
- Michael Charles Sachs (ORCID: https://orcid.org/0000-0002-1279-8676)
- Adam Brand (ORCID: https://orcid.org/0000-0003-1300-5292)
- Johan Sebastian Ohlendorff
Institutions
- University of Copenhagen (DK)
- Karolinska Institutet (SE)
- Emmes (United States) (US)
Publication Details
- Journal
- Annals of Epidemiology
- Published
- 2025-04-09
- DOI
- https://doi.org/10.1016/j.annepidem.2025.04.002
- Primary Topic
- Advanced Causal Inference Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Danmarks Grundforskningsfond
- Novo Nordisk
- Novo Nordisk Fonden