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Causal inference with observational data: the need for triangulation of evidence
The goal of much observational research is to identify risk factors that have a causal effect on health and social outcomes. However, observational data are subject to biases from confounding, selection and measurement, which can result in an underestimate or overestimate of the effect of interest....
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| Publicado no: | Psychol Med |
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| Main Authors: | , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Cambridge University Press
2021
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8020490/ https://ncbi.nlm.nih.gov/pubmed/33682654 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1017/S0033291720005127 |
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