Model-based clustering methods for continuous data are well established and commonly used in a wide range of applications. However, model-based clustering methods for categorical data are less standard. Latent class analysis is a commonly used method for model-based clustering of binary data and/or categorical data, but due to an assumed local independence structure there may not be a correspon...

background: metabolic syndrome (mets), a combination of coronary heart disease and diabetes mellitus risk factor, refer to one of the most challenging public health issues in worldwide. the aim of this study was to identify the subgroups of participants in a study on the basis of mets components.   methods: the cross-sectional study took place in the districts related to tehran university of me...

This article discusses a modelling framework that links two well-known statistical methods: structural equation modelling (SEM) and latent class or finite mixture modelling. This hybrid approach was proposed independently by Arminger and Stein [1], Dolan and Van der Maas [4], and Jedidi, Jagpal and DeSarbo [5]. Here, we refer to this approach as mixture SEM or latent class SEM. There are two di...

  Background: Metabolic syndrome (MetS), a combination of coronary heart disease and diabetes mellitus risk factor, refer to one of the most challenging public health issues in worldwide. The aim of this study was to identify the subgroups of participants in a study on the basis of MetS components.   Methods: The cross-sectional study took place in the districts related to Teh...

Motorcycle crashes constitute a significant proportion of traffic accidents all over the world. The aim of this paper was to examine the motorcycle crash patterns and rider fault status across the provinces of Iran. For this purpose, 6638 motorcycle crashes occurred in Iran through 2009-2012 were used as the analysis data and a two-step clustering approach was adopted as the analysis framework....

Background: Cardio-metabolic syndrome indicates the clustering of several risk factors. The aims of this study were to identify the subgroups of the Iranian children and adolescents on the basis of the components of the cardio-metabolic syndrome and assess the role of demographic characteristics, socioeconomic status and life style related behaviors on the membership of participants in each lat...

The latent class model or multivariate multinomial mixture is a powerful model for clustering discrete data. This model is expected to be useful to represent non-homogeneous populations. It uses a conditional independence assumption given the latent class to which a statistical unit is belonging. However, it leads to a criterion that proves difficult to optimise by the standard approach based o...

This paper is concerned with model-based clustering of discrete data. Latent class models (LCMs) are usually used for the task. An LCM consists of a latent variable and a number of attributes. It makes the overly restrictive assumption that the attributes are mutually independent given the latent variable. We propose a novel method to relax the assumption. The key idea is to partition the attri...