Cargando…
Three handy tips and a practical guide to improve your propensity score models
Real-world data are increasingly available to investigate ‘real-world’ safety and efficacy. However, since treatment in observational studies is not randomly allocated, confounding by indication may occur, in which differences in patient characteristics may influence both treatment choices and treat...
Autores principales: | Bergstra, Sytske Anne, Sepriano, Alexandre, Ramiro, Sofia, Landewé, Robert |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6525599/ https://www.ncbi.nlm.nih.gov/pubmed/31168417 http://dx.doi.org/10.1136/rmdopen-2019-000953 |
Ejemplares similares
-
Comparative construct validity of three presenteeism instruments in workers with musculoskeletal complaints: a prospective cohort study
por: van der Burg, Lennart, et al.
Publicado: (2020) -
COVID-19-induced hyperinflammation, immunosuppression, recovery and survival: how causal inference may help draw robust conclusions
por: Landewé, Robert B M, et al.
Publicado: (2021) -
Analysing and reporting of observational data: a systematic review informing the EULAR points to consider when analysing and reporting comparative effectiveness research with observational data in rheumatology
por: Lauper, Kim, et al.
Publicado: (2021) -
Biological DMARDs and disease modification in axial spondyloarthritis: a review through the lens of causal inference
por: Sepriano, Alexandre, et al.
Publicado: (2021) -
Make: tips and tales from the workshop : a handy reference for Makers
por: Branwyn, Gareth, et al.
Publicado: (2018)