Mixture multigroup structural equation modeling: A novel method for comparing structural relations across many groups.

Behavioral scientists often examine the relations between two or more latent variables (e.g., how emotions relate to life satisfaction), and structural equation modeling (SEM) is the state-of-the-art for doing so.

An empirically based typology of temporary alcohol abstinence challenge participants using latent class analysis.

Introduction: Identifying subgroups of Temporary (alcohol) Abstinence Challenge (TAC) participants may offer opportunities to enhance intervention effectiveness. However, knowledge about such subgroups is missing. This study aimed to (i) describe a TAC population; (ii) identify subgroups of participants based on determinants of changes in drinking behaviour; and (iii) characterise subgroups in terms of sociodemographic and other characteristics.

Causal Latent Class Analysis with Distal Outcomes: A Modified Three-Step Method Using Inverse Propensity Weighting.

Bias-adjusted three-step latent class (LC) analysis is a popular technique for estimating the relationship between LC membership and distal outcomes. Since it is impossible to randomize LC membership, causal inference techniques are needed to estimate causal effects leveraging observational data. This paper proposes two novel strategies that make use of propensity scores to estimate the causal effect of LC membership on a distal outcome variable.

Transgressive incidents targeted on staff in forensic psychiatric healthcare: a latent class analysis.

Transgressive incidents directed at staff by forensic patients occur frequently, leading to detrimental psychological and physical harm, underscoring urgency of preventive measures. These incidents, emerging within therapeutic relationships, involve complex interactions between patient and staff behavior. This study aims to identify clusters of transgressive incidents based on incident characteristics such as impact, severity, (presumed) cause, type of aggression, and consequences, using latent class analysis (LCA).