Related Experiment Video
Updated: Jun 22, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
Published on: July 3, 2020
Bayesian semiparametric analysis of structural equation models with mixed continuous and unordered categorical
Xin-Yuan Song1, Ye-Mao Xia, Sik-Yum Lee
1Department of Statistics, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong. xysong@sta.cuhk.edu.hk
Abstract:
Recently, structural equation models (SEMs) have been applied for analyzing interrelationships among observed and latent variables in biological and medical research. Latent variables in these models are typically assumed to have a normal distribution. This article considers a Bayesian semparametric SEM with covariates, and mixed continuous and unordered categorical variables, in which the explanatory latent variables in the structural equation are modeled via an appropriate truncated Dirichlet process with a stick-breaking procedure. Results obtained from a simulation study and an analysis of a real medical data set are presented to illustrate the methodology.
Related Concept Videos
Mechanistic Models: Compartment Models in Individual and Population Analysis
Friedman Two-way Analysis of Variance by Ranks
Parametric Survival Analysis: Weibull and Exponential Methods
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
Censoring Survival Data
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Assumptions of Survival Analysis
