Sara Wade

Reader in Statistics and Data Science


Curriculum vitae


[email protected]


School of Mathematics

University of Edinburgh

Room 5406
James Clerk Maxwell Building, Edinburgh, EH9 3FD



Mapping of machine learning approaches for description, prediction, and causal inference in the social and health sciences


Journal article


A.K. Leist, M. Klee, J.H. Kim, D.H Rehkopf, S.P.A Bordas, G. Muniz-Terrera, S. Wade
Science Advances, 2022


Paper
Cite

Cite

APA   Click to copy
Leist, A. K., Klee, M., Kim, J. H., Rehkopf, D. H., Bordas, S. P. A., Muniz-Terrera, G., & Wade, S. (2022). Mapping of machine learning approaches for description, prediction, and causal inference in the social and health sciences. Science Advances. https://doi.org/10.1126/sciadv.abk1942


Chicago/Turabian   Click to copy
Leist, A.K., M. Klee, J.H. Kim, D.H Rehkopf, S.P.A Bordas, G. Muniz-Terrera, and S. Wade. “Mapping of Machine Learning Approaches for Description, Prediction, and Causal Inference in the Social and Health Sciences.” Science Advances (2022).


MLA   Click to copy
Leist, A. K., et al. “Mapping of Machine Learning Approaches for Description, Prediction, and Causal Inference in the Social and Health Sciences.” Science Advances, 2022, doi:10.1126/sciadv.abk1942.


BibTeX   Click to copy

@article{leist2022a,
  title = {Mapping of machine learning approaches for description, prediction, and causal inference in the social and health sciences},
  year = {2022},
  journal = {Science Advances},
  doi = {10.1126/sciadv.abk1942},
  author = {Leist, A.K. and Klee, M. and Kim, J.H. and Rehkopf, D.H and Bordas, S.P.A and Muniz-Terrera, G. and Wade, S.}
}


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