Embracing Uncertainty: The Value of Partial Identification in Public Health and Clinical Research
| Autor: | Daniel L. Millimet, Charles F. Manski, John Mullahy, Atheendar S. Venkataramani |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Identification methods
medicine.medical_specialty Epidemiology Management science Public health 010102 general mathematics Uncertainty Public Health Environmental and Occupational Health 01 natural sciences 03 medical and health sciences Identification (information) 0302 clinical medicine Empirical research Clinical research medicine Humans Public Health 030212 general & internal medicine 0101 mathematics Psychology Value (mathematics) Preventive healthcare |
| Zdroj: | American Journal of Preventive Medicine. 61:e103-e108 |
| ISSN: | 0749-3797 |
| DOI: | 10.1016/j.amepre.2021.01.041 |
| Popis: | Introduction This paper describes the methodology of partial identification and its applicability to empirical research in preventive medicine and public health. Methods The authors summarize findings from the methodologic literature on partial identification. The analysis was conducted in 2020–2021. Results The applicability of partial identification methods is demonstrated using 3 empirical examples drawn from published literature. Conclusions Partial identification methods are likely to be of considerable interest to clinicians and others engaged in preventive medicine and public health research. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect