Counterfactual prediction is not only for causal inference
Clinical researchers generate and analyze health data for three classes of tasks: description, prediction, and counterfactual prediction [1]. Description uses data to provide a quantitative summary of certain features of the world. Prediction uses data to map some features of the world (the inputs)...
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| Veröffentlicht in: | European journal of epidemiology 2020-07, Vol.35 (7), p.615-617 |
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| container_title | European journal of epidemiology |
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| creator | Dickerman, Barbra A. Hernán, Miguel A. |
| description | Clinical researchers generate and analyze health data for three classes of tasks: description, prediction, and counterfactual prediction [1]. Description uses data to provide a quantitative summary of certain features of the world. Prediction uses data to map some features of the world (the inputs) to other features of the world (the outputs). Counterfactual prediction uses data to predict certain features of the world if the world had been different. |
| doi_str_mv | 10.1007/s10654-020-00659-8 |
| format | Article |
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| ispartof | European journal of epidemiology, 2020-07, Vol.35 (7), p.615-617 |
| issn | 0393-2990 1573-7284 |
| language | eng |
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| source | Jstor Complete Legacy; MEDLINE; Springer Nature - Complete Springer Journals |
| subjects | Algorithms Cardiology Causality Clinical Decision Rules Clinical medicine Clinical trials Commentary Confounding Factors, Epidemiologic Decision Making Epidemiologic Research Design Epidemiology Humans Infectious Diseases Medicine Medicine & Public Health Models, Statistical Oncology Predictions Public Health Statistical inference Validity |
| title | Counterfactual prediction is not only for causal inference |
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