Latent Class Analysis for Models with Error of Measurement Using Log-Linear Models and An Application to Women’s Liberation Data
Volume 9, Issue 1 (2011), pp. 43–54
Pub. online: 4 August 2022
Type: Research Article
Open Access
Open Access
Published
4 August 2022
4 August 2022
Abstract
Abstract: This article deals with the latent class analysis of models with
error of measurement. If the latent variable is ordinal and manifest variables
are nominal, an approach to handle the restrictions is given for latent class
analysis of the models with error of measurement using log linear models. By
this way, we include ordinal nature of the latent variable into the analysis.
Therefore, overall uncertainty is decreased, and our inferences become more
precise. The new approach is applied to a women’s liberation data set.