Non‐linear structural equation models with correlated continuous and discrete data |
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| Authors: | Professor Sik‐Yum Lee Xin‐Yuan Song Jing‐Heng Cai Wing‐Yee So Ching‐Wang Ma Chung‐Ngor Juliana Chan |
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| Affiliation: | 1. Department of Statistics, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong;2. Department of Medicine and Therapeutics, The Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong |
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| Abstract: | Structural equation models (SEMs) have been widely applied to examine interrelationships among latent and observed variables in social and psychological research. Motivated by the fact that correlated discrete variables are frequently encountered in practical applications, a non‐linear SEM that accommodates covariates, and mixed continuous, ordered, and unordered categorical variables is proposed. Maximum likelihood methods for estimation and model comparison are discussed. One real‐life data set about cardiovascular disease is used to illustrate the methodologies. |
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