A Flexible Approach for Assessing Heterogeneity of Causal Treatment Effects on Patient Survival Using Large Datasets with Clustered Observations

Personalized medicine requires an understanding of treatment effect heterogeneity. Evolving toward causal evidence for scenarios not studied in randomized trials necessitates a methodology using real-world evidence. Herein, we demonstrate a methodology that generates causal effects, assesses the het...

Descripción completa

Detalles Bibliográficos
Autores principales: Hu, Liangyuan, Ji, Jiayi, Liu, Hao, Ennis, Ronald
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Brief Report
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9690785/
https://www.ncbi.nlm.nih.gov/pubmed/36429621
http://dx.doi.org/10.3390/ijerph192214903

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9690785/
https://www.ncbi.nlm.nih.gov/pubmed/36429621
http://dx.doi.org/10.3390/ijerph192214903

Ejemplares similares