Factor Analysis with Categorical Indicators: A Comparison Between Traditional and Latent Class Approaches

132 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Latent Class Analysis (2021, background): “The key assumption made for any latent variable model is that the latent variable or variables explain all associations between the indicators, as implied by the assumption of local independence (Vermunt & Magidson, 2004b).”
The effect of exposure to bullying on turnover intentions: the role of perceived psychological contract violation and benevolent behaviour (2017, background): “As a result, the standard error may not be trustworthy (Vermunt & Magidson, 2005).”
Technical Guide for Latent GOLD 5.1: Basic, Advanced, and Syntax 1 (2016, background): “Thus, rather than working with a single nominal latent variable, here we work with one or more dichotomous or ordered polytomous latent variables (Magidson and Vermunt, 2001; Vermunt and Magidson, 2005a).”
Measuring bullying at work with the short-negative acts questionnaire: identification of targets and criterion validity (2019, background): “Vermunt and Magidson (2005) proposed the use of Latent Class Cluster (LCC) and Latent Class Factor (LCF) analysis for such data.”