Assessing causal treatment effect estimation when using large observational datasets

Assessing causal treatment effect estimation when using large observational datasets

Abstract Background Recently, there has been a heightened interest in developing and evaluating different methods for analysing observational data. This has been driven by the increased availability of large data resources such as Electronic Health Record (EHR) data alongside known limitations and c...

ver descrição completa

Detalhes bibliográficos
Main Authors: E. R. John, K. R. Abrams, C. E. Brightling, N. A. Sheehan
Formato: Artigo
Idioma:English
Publicado em: BMC 2019-11-01
Colecção:BMC Medical Research Methodology
Assuntos:
Observational data
Causal effect
Instrumental variable
Propensity scores
Unmeasured confounding
Acesso em linha:http://link.springer.com/article/10.1186/s12874-019-0858-x

Internet

http://link.springer.com/article/10.1186/s12874-019-0858-x

Registos relacionados