Multilevel models with multivariate mixed response types

doi:10.1177/1471082x0800900301

Multilevel models with multivariate mixed response types

2009-10-21

0

PRE

AI

DOI：10.1177/1471082x0800900301

原文链接

原文求助

摘要

En 中文

We build upon the existing literature to formulate a class of models for multivariate mixtures of Gaussian, ordered or unordered categorical responses and continuous distributions that are not Gaussian, each of which can be defined at any level of a multilevel data hierarchy. We describe a Markov chain Monte Carlo algorithm for fitting such models. We show how this unifies a number of disparate problems, including partially observed data and missing data in generalized linear modelling. The two-level model is considered in detail with worked examples of applications to a prediction problem and to multiple imputation for missing data. We conclude with a discussion outlining possible extensions and connections in the literature. Software for estimating the models is freely available.

Multilevel models with multivariate mixed response types

摘要

AI总结

期刊

机构

引用论文