Latent class analysis in PLS-SEM: A review and recommendations for future applications
With the increasing prominence of partial least squares structural equation modeling (PLS-
SEM) in business research, the use of latent class analyses for identifying and treating …
SEM) in business research, the use of latent class analyses for identifying and treating …
Measurement invariance in the social sciences: Historical development, methodological challenges, state of the art, and future perspectives
This review summarizes the current state of the art of statistical and (survey) methodological
research on measurement (non) invariance, which is considered a core challenge for the …
research on measurement (non) invariance, which is considered a core challenge for the …
Latent class analysis: a guide to best practice
Latent class analysis (LCA) is a statistical procedure used to identify qualitatively different
subgroups within populations who often share certain outward characteristics. The …
subgroups within populations who often share certain outward characteristics. The …
Ten frequently asked questions about latent class analysis.
Latent class analysis (LCA) is a statistical method used to identify unobserved subgroups in
a population with a chosen set of indicators. Given the increasing popularity of LCA, our aim …
a population with a chosen set of indicators. Given the increasing popularity of LCA, our aim …
[BOOK][B] Structural equation modeling: Applications using Mplus
J Wang, X Wang - 2019 - books.google.com
Presents a useful guide for applications of SEM whilst systematically demonstrating various
SEM models using Mplus Focusing on the conceptual and practical aspects of Structural …
SEM models using Mplus Focusing on the conceptual and practical aspects of Structural …
Auxiliary Variables in Mixture Modeling: Three-Step Approaches Using Mplus
This article discusses alternatives to single-step mixture modeling. A 3-step method for latent
class predictor variables is studied in several different settings, including latent class …
class predictor variables is studied in several different settings, including latent class …
Finding latent groups in observed data: A primer on latent profile analysis in Mplus for applied researchers
The present guide provides a practical guide to conducting latent profile analysis (LPA) in
the Mplus software system. This guide is intended for researchers familiar with some latent …
the Mplus software system. This guide is intended for researchers familiar with some latent …
[PDF][PDF] Auxiliary variables in mixture modeling: Using the BCH method in Mplus to estimate a distal outcome model and an arbitrary secondary model
In mixture modeling, indicator variables are used to identify an underlying latent categorical
variable. In many practical applications we are interested in using the latent categorical …
variable. In many practical applications we are interested in using the latent categorical …
[BOOK][B] An introduction to multilevel modeling techniques: MLM and SEM approaches
Multilevel modelling is a data analysis method that is frequently used to investigate
hierarchal data structures in educational, behavioural, health, and social sciences …
hierarchal data structures in educational, behavioural, health, and social sciences …
[BOOK][B] Longitudinal structural equation modeling: A comprehensive introduction
JT Newsom - 2023 - taylorfrancis.com
Longitudinal Structural Equation Modeling is a comprehensive resource that reviews
structural equation modeling (SEM) strategies for longitudinal data to help readers …
structural equation modeling (SEM) strategies for longitudinal data to help readers …