Toward a Total Causal Error Framework: Extending Cornfield's Insights Across Causal Identification, Representation, and Measurement.

Eisenhauer EW, Han D, Edwards B, Brick JM

DOI: 10.1353/obs.00014
Published: 2026
Container: Observational studies
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1353/obs.00014,
  title = {Toward a Total Causal Error Framework: Extending Cornfield's Insights Across Causal Identification, Representation, and Measurement.},
  author = {Eisenhauer EW and Han D and Edwards B and Brick JM},
  year = {2026},
  journal = {Observational studies},
  doi = {10.1353/obs.00014},
  url = {https://doi.org/10.1353/obs.00014}
}

RIS

TY  - JOUR
TI  - Toward a Total Causal Error Framework: Extending Cornfield's Insights Across Causal Identification, Representation, and Measurement.
AU  - Eisenhauer EW
AU  - Han D
AU  - Edwards B
AU  - Brick JM
PY  - 2026
JO  - Observational studies
DO  - 10.1353/obs.00014
UR  - https://doi.org/10.1353/obs.00014
ER  -

APA

EW, E., D, H., B, E., & JM, B. (2026). Toward a Total Causal Error Framework: Extending Cornfield's Insights Across Causal Identification, Representation, and Measurement.. Observational studies. https://doi.org/10.1353/obs.00014

Source records

pubmed · retrieved 2026-09-25T00:49:01.260Z