Sampling for computational efficiency when conducting analyses in big data.

Rudolph JE, Zhou Y, Yenokyan K, Xu X, Wentz E, Calkins KL, Joshu CE, Lau B

DOI: 10.1093/aje/kwaf268
Published: 2026 Mar 17
Container: American journal of epidemiology
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1093/aje/kwaf268,
  title = {Sampling for computational efficiency when conducting analyses in big data.},
  author = {Rudolph JE and Zhou Y and Yenokyan K and Xu X and Wentz E and Calkins KL and Joshu CE and Lau B},
  year = {2026},
  journal = {American journal of epidemiology},
  doi = {10.1093/aje/kwaf268},
  url = {https://doi.org/10.1093/aje/kwaf268}
}

RIS

TY  - JOUR
TI  - Sampling for computational efficiency when conducting analyses in big data.
AU  - Rudolph JE
AU  - Zhou Y
AU  - Yenokyan K
AU  - Xu X
AU  - Wentz E
AU  - Calkins KL
AU  - Joshu CE
AU  - Lau B
PY  - 2026
JO  - American journal of epidemiology
DO  - 10.1093/aje/kwaf268
UR  - https://doi.org/10.1093/aje/kwaf268
ER  -

APA

JE, R., Y, Z., K, Y., X, X., E, W., KL, C., CE, J., & B, L. (2026). Sampling for computational efficiency when conducting analyses in big data.. American journal of epidemiology. https://doi.org/10.1093/aje/kwaf268

Source records

pubmed · retrieved 2026-09-25T02:41:47.373Z