Multilevel Latent Class Analysis Research Articles

Obsessive–compulsive disorder: subclassification based on co-morbidity

Obsessive-compulsive disorder (OCD) is probably an etiologically heterogeneous condition. Many patients manifest other psychiatric syndromes. This study investigated the relationship between OCD and co-morbid conditions to identify subtypes. Seven hundred and six individuals with OCD were assessed in the OCD Collaborative Genetics Study (OCGS). Multi-level latent class analysis was conducted based on the presence of eight co-morbid psychiatric conditions [generalized anxiety disorder (GAD), major depression, panic disorder (PD), separation anxiety disorder (SAD), tics, mania, somatization disorders (Som) and grooming disorders (GrD)]. The relationship of the derived classes to specific clinical characteristics was investigated. Two and three classes of OCD syndromes emerge from the analyses. The two-class solution describes lesser and greater co-morbidity classes and the more descriptive three-class solution is characterized by: (1) an OCD simplex class, in which major depressive disorder (MDD) is the most frequent additional disorder; (2) an OCD co-morbid tic-related class, in which tics are prominent and affective syndromes are considerably rarer; and (3) an OCD co-morbid affective-related class in which PD and affective syndromes are highly represented. The OCD co-morbid tic-related class is predominantly male and characterized by high conscientiousness. The OCD co-morbid affective-related class is predominantly female, has a young age at onset, obsessive-compulsive personality disorder (OCPD) features, high scores on the 'taboo' factor of OCD symptoms, and low conscientiousness. OCD can be classified into three classes based on co-morbidity. Membership within a class is differentially associated with other clinical characteristics. These classes, if replicated, should have important implications for research and clinical endeavors.

Heavy Alcohol use in the “Fighting Back” Survey Sample: Separating Individual and Community Level Influences using Multilevel Latent Class Analysis

In this article, multilevel latent class analysis is used to examine the structure of heavy alcohol use. A model with three latent classes (types) of people fits the data well: those who seldom suffer major consequences from heavy drinking, those who typically suffer only a small number of major consequences, and those who suffer serious consequences in a large number of areas of their lives. Individuals in the first class tend to be older, female, with domestic partners, more highly educated, employed, and either Catholic, Muslim, or Baptist.

Country and consumer segmentation: multi-level latent class analysis of financial product ownership

The financial services sector has internationalized over the last few decades. Important differences and similarities in financial behavior can be anticipated between both consumers within a particular country and those living in different countries. For companies in this market, the appropriate choice between strategic options and the resulting international performance may critically depend on the cross-national market structure of the various financial products. Insight into country segments and international consumer segments based on domain-specific behavioral variables will therefore be of key strategic importance. We present a multi-level latent class framework for obtaining simultaneously such country and consumer segments. In an empirical study, we apply this methodology and several alternative modeling approaches to data on ownership of eight financial products. Information is available for 15 European countries, with a sample size of about 1000 consumers per country. We find that both country segments and consumer segments are highly interpretable. Also, consumer segmentation is related to demographic variables such as age and income. Our conclusions feature implications, both academic and managerial, and directions for future research.

Country and Consumer Segmentation: Multi-Level Latent Class Analysis of Financial Product Ownership

The financial services sector has internationalized over the last few decades. Important differences and similarities in financial behavior can be anticipated between both consumers within a particular country and those living in different countries. For companies in this market, the appropriate choice between strategic options and the resulting international performance may critically depend on the cross-national demand structure for the various financial products. Insight into country segments and international consumer segments based on domain-specific behavioral variables will, therefore, be of key strategic importance. We present a multi-level latent class framework for obtaining simultaneously such country and consumer segments. In an empirical study, we apply this methodology to data on ownership of eight financial products. Information is available for fifteen European countries, with a sample size of about 1000 consumers per country. We find that both country segments and consumer segments are highly interpretable. Furthermore, consumer segmentation is related to demographic variables, such as age and income. Our conclusions feature implications, both academic and managerial, and directions for future research.