EconPapers    
Economics at your fingertips  
 

Hierarchical Generalized Linear Models and Frailty Models with Bayesian Nonparametric Mixing

Stephen G. Walker and Bani K. Mallick

Journal of the Royal Statistical Society Series B, 1997, vol. 59, issue 4, 845-860

Abstract: This paper proposes Bayesian nonparametric mixing for some well‐known and popular models. The distribution of the observations is assumed to contain an unknown mixed effects term which includes a fixed effects term, a function of the observed covariates, and an additive or multiplicative random effects term. Typically these random effects are assumed to be independent of the observed covariates and independent and identically distributed from a distribution from some known parametric family. This assumption may be suspect if either there is interaction between observed covariates and unobserved covariates or the fixed effects predictor of observed covariates is misspecified. Another cause for concern might be simply that the covariates affect more than just the location of the mixed effects distribution. As a consequence the distribution of the random effects could be highly irregular in modality and skewness leaving parametric families unable to model the distribution adequately. This paper therefore proposes a Bayesian nonparametric prior for the random effects to capture possible deviances in modality and skewness and to explore the observed covariates’ effect on the distribution of the mixed effects.

Date: 1997
References: Add references at CitEc
Citations: View citations in EconPapers (18)

Downloads: (external link)
https://doi.org/10.1111/1467-9868.00101

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssb:v:59:y:1997:i:4:p:845-860

Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-9868

Access Statistics for this article

Journal of the Royal Statistical Society Series B is currently edited by P. Fryzlewicz and I. Van Keilegom

More articles in Journal of the Royal Statistical Society Series B from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().

 
Page updated 2025-03-19
Handle: RePEc:bla:jorssb:v:59:y:1997:i:4:p:845-860