Cargando…
Quantifying the Impact of Unobserved Heterogeneity on Inference from the Logistic Model
While consequences of unobserved heterogeneity such as biased estimates of binary response regression models are generally known; quantifying these and awareness of situations with more serious impact on inference is however, remarkably lacking. This study examines the effect of unobserved heterogen...
Autor principal: | Ayis, Salma |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2009
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4453966/ https://www.ncbi.nlm.nih.gov/pubmed/26085712 http://dx.doi.org/10.1080/03610920802491782 |
Ejemplares similares
-
Toddlers infer unobserved causes for spontaneous events
por: Muentener, Paul, et al.
Publicado: (2014) -
Inferring collective dynamical states from widely unobserved systems
por: Wilting, Jens, et al.
Publicado: (2018) -
Ensemble inference of unobserved infections in networks using partial observations
por: Zhang, Renquan, et al.
Publicado: (2023) -
Beyond logistic regression: structural equations modelling for binary variables and its application to investigating unobserved confounders
por: Kupek, Emil
Publicado: (2006) -
The Control Outcome Calibration Approach for Causal Inference With Unobserved Confounding
por: Tchetgen Tchetgen, Eric
Publicado: (2014)