MODELLING CORRELATION MATRICES IN MULTIVARIATE DATA, WITH APPLICATION TO RECIPROCITY AND COMPLEMENTARITY OF CHILD-PARENT EXCHANGES OF SUPPORT

• 成果类型: Article
• 署名作者: Zhang, Siliang; Kuha, Jouni; Steele, Fiona
• 署名单位: East China Normal University; University of London; London School Economics & Political Science
• 刊物名称: ANNALS OF APPLIED STATISTICS
• ISSN/ISSBN: 1932-6157
• DOI: 10.1214/24-AOAS1921
• 发表日期: 2024
• 页码: 3024-3049
• 关键词: intergenerational exchange; efficient estimation; Covariance matrices; longitudinal data; adult children; discrepancies; likelihood; selection; transfers; patterns

摘要

We define a model for the joint distribution of multiple continuous latent variables, which includes a model for how their correlations depend on explanatory variables. This is motivated by and applied to social scientific research questions in the analysis of intergenerational help and support within families, where the correlations describe reciprocity of help between generations and complementarity of different kinds of help. We propose an MCMC procedure for estimating the model which maintains the positive definiteness of the implied correlation matrices and describe theoretical results which justify this approach and facilitate efficient implementation of it. The model is applied to data from the UK Household Longitudinal Study to analyse exchanges of practical and financial support between adult individuals and their noncoresident parents.