Objective Bayesian Inference for a Generalized Marginal Random Effects Model
نویسندگان
چکیده
منابع مشابه
Bayesian Inference for Spatial Beta Generalized Linear Mixed Models
In some applications, the response variable assumes values in the unit interval. The standard linear regression model is not appropriate for modelling this type of data because the normality assumption is not met. Alternatively, the beta regression model has been introduced to analyze such observations. A beta distribution represents a flexible density family on (0, 1) interval that covers symm...
متن کاملA Bayesian Nominal Regression Model with Random Effects for Analysing Tehran Labor Force Survey Data
Large survey data are often accompanied by sampling weights that reflect the inequality probabilities for selecting samples in complex sampling. Sampling weights act as an expansion factor that, by scaling the subjects, turns the sample into a representative of the community. The quasi-maximum likelihood method is one of the approaches for considering sampling weights in the frequentist framewo...
متن کاملPrior-free Inference for Objective Bayesian Analysis and Model Selection
A new approach to Bayesian inference, named the prior-free inference, is introduced for developing objective Bayesian analysis based on information-theoretic approach. This new approach is essentially a Bayesian method but it does not depend on a prior distribution for unknown parameters. Thus, this approach not only has the advantages of the Bayesian approach but also can avoid the difficulty,...
متن کاملBayesian Inference for Finite Mixtures of Generalized Linear Models with Random Effects
We present an hierarchical Bayes approach to modeling parameter heterogeneity in generalized linear models. The model assumes that there are relevant subpopulations and that within each subpopulation the individual-level regression coefficients have a multivariate normal distribution. However, class membership is not known a priori, so the heterogeneity in the regression coefficients becomes a ...
متن کاملApproximate Bayesian inference for random effects meta-analysis.
Whilst meta-analysis is becoming a more commonplace statistical technique, Bayesian inference in meta-analysis requires complex computational techniques to be routinely applied. We consider simple approximations for the first and second moments of the parameters of a Bayesian random effects model for meta-analysis. These computationally inexpensive methods are based on simple analytical formula...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Bayesian Analysis
سال: 2016
ISSN: 1936-0975
DOI: 10.1214/14-ba933