Cargando…
Treatment effects beyond the mean using distributional regression: Methods and guidance
This paper introduces distributional regression also known as generalized additive models for location, scale and shape (GAMLSS) as a modeling framework for analyzing treatment effects beyond the mean. In contrast to mean regression models, GAMLSS relate each distributional parameter to covariates....
Autores principales: | Hohberg, Maike, Pütz, Peter, Kneib, Thomas |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7021287/ https://www.ncbi.nlm.nih.gov/pubmed/32058999 http://dx.doi.org/10.1371/journal.pone.0226514 |
Ejemplares similares
-
Regression: models, methods and applications
por: Fahrmeir, Ludwig, et al.
Publicado: (2013) -
Is age at menopause decreasing? – The consequences of not completing the generational cohort
por: Martins, Rui, et al.
Publicado: (2022) -
Statistical Modelling and Regression Structures
por: Kneib, Thomas, et al.
Publicado: (2010) -
Bayesian Gaussian distributional regression models for more efficient norm estimation
por: Voncken, Lieke, et al.
Publicado: (2020) -
Thinking beyond the mean: a practical guide for using quantile regression methods for health services research
por: Lê Cook, Benjamin, et al.
Publicado: (2013)