Pseudo-random Number Generator Influences on Average Treatment Effect Estimates Obtained with Machine Learning
Our findings add another dimension of concern regarding the potential for "p-hacking," and further warrant the need to move away from simplistic evidentiary thresholds in empirical research. When empirical results depend on pseudo-random number generator seed values, caution is warranted in interpreting these results.
Authors
- Lisa M. Bodnar (ORCID: https://orcid.org/0000-0001-9427-5467)
- Ya‐Hui Yu (ORCID: https://orcid.org/0000-0002-9104-8899)
- Ashley Isaac Naimi (ORCID: https://orcid.org/0000-0002-1510-8175)
Institutions
- Emory University (US)
- Georgia Department of Public Health (US)
Publication Details
- Journal
- Epidemiology
- Published
- 2024-08-16
- DOI
- https://doi.org/10.1097/ede.0000000000001785
- Citations
- 7
- Primary Topic
- Pregnancy and preeclampsia studies
- Type
- article
- Field-Weighted Citation Impact
- 4.08
Funders
- National Institutes of Health