Cargando…
Regression Discontinuity for Causal Effect Estimation in Epidemiology
Regression discontinuity analyses can generate estimates of the causal effects of an exposure when a continuously measured variable is used to assign the exposure to individuals based on a threshold rule. Individuals just above the threshold are expected to be similar in their distribution of measur...
Autores principales: | Oldenburg, Catherine E., Moscoe, Ellen, Bärnighausen, Till |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4978750/ https://www.ncbi.nlm.nih.gov/pubmed/27547695 http://dx.doi.org/10.1007/s40471-016-0080-x |
Ejemplares similares
-
Regression Discontinuity Designs in Epidemiology: Causal Inference Without Randomized Trials
por: Bor, Jacob, et al.
Publicado: (2014) -
Trends in the Mechanistic and Dynamic Modeling of Infectious Diseases
por: Lessler, Justin, et al.
Publicado: (2016) -
The causal effect of retirement on stress in older adults in China: A regression discontinuity study
por: Chen, Simiao, et al.
Publicado: (2019) -
Antiretroviral Therapy and Mortality in Rural South Africa: A Comparison of Causal Modeling Approaches
por: Oldenburg, Catherine E, et al.
Publicado: (2018) -
Regression Discontinuity Designs in Health: A Systematic Review
por: Hilton Boon, Michele, et al.
Publicado: (2020)