blavaan: Bayesian structural equation models via parameter expansion

E. Merkle, Y. Rosseel
{"title":"blavaan: Bayesian structural equation models via parameter expansion","authors":"E. Merkle, Y. Rosseel","doi":"10.18637/jss.v085.i04","DOIUrl":null,"url":null,"abstract":"This article describes blavaan, an R package for estimating Bayesian structural equation models (SEMs) via JAGS and for summarizing the results. It also describes a novel parameter expansion approach for estimating specific types of models with residual covariances, which facilitates estimation of these models in JAGS. The methodology and software are intended to provide users with a general means of estimating Bayesian SEMs, both classical and novel, in a straightforward fashion. Users can estimate Bayesian versions of classical SEMs with lavaan syntax, they can obtain state-of-the-art Bayesian fit measures associated with the models, and they can export JAGS code to modify the SEMs as desired. These features and more are illustrated by example, and the parameter expansion approach is explained in detail.","PeriodicalId":8446,"journal":{"name":"arXiv: Computation","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2015-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"215","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv: Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18637/jss.v085.i04","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 215

Abstract

This article describes blavaan, an R package for estimating Bayesian structural equation models (SEMs) via JAGS and for summarizing the results. It also describes a novel parameter expansion approach for estimating specific types of models with residual covariances, which facilitates estimation of these models in JAGS. The methodology and software are intended to provide users with a general means of estimating Bayesian SEMs, both classical and novel, in a straightforward fashion. Users can estimate Bayesian versions of classical SEMs with lavaan syntax, they can obtain state-of-the-art Bayesian fit measures associated with the models, and they can export JAGS code to modify the SEMs as desired. These features and more are illustrated by example, and the parameter expansion approach is explained in detail.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
blavaan:通过参数展开的贝叶斯结构方程模型
本文介绍了blavaan,这是一个R包,用于通过JAGS估计贝叶斯结构方程模型(sem)并总结结果。本文还描述了一种新的参数展开方法,用于估计具有残差协方差的特定类型的模型,这有助于在JAGS中对这些模型进行估计。该方法和软件旨在以简单的方式为用户提供估计贝叶斯sem的一般方法,包括经典的和新颖的。用户可以使用lavaan语法估计经典sem的贝叶斯版本,他们可以获得与模型相关的最先进的贝叶斯拟合度量,并且可以导出JAGS代码以根据需要修改sem。通过实例说明了这些特点,并详细说明了参数展开方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Double Happiness: Enhancing the Coupled Gains of L-lag Coupling via Control Variates. SCOREDRIVENMODELS.JL: A JULIA PACKAGE FOR GENERALIZED AUTOREGRESSIVE SCORE MODELS Simple conditions for convergence of sequential Monte Carlo genealogies with applications Increasing the efficiency of Sequential Monte Carlo samplers through the use of approximately optimal L-kernels Particle Methods for Stochastic Differential Equation Mixed Effects Models
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1