4.4 Article

How to perform three-step latent class analysis in the presence of measurement non-invariance or differential item functioning

Related references

Note: Only part of the references are listed.
Article Mathematics, Interdisciplinary Applications

Prediction from Latent Classes: A Demonstration of Different Approaches to Include Distal Outcomes in Mixture Models

Karen Nylund-Gibson et al.

STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL (2019)

Article Mathematics, Interdisciplinary Applications

The Detection and Modeling of Direct Effects in Latent Class Analysis

Jeroen H. M. Janssen et al.

STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL (2019)

Article Mathematics, Interdisciplinary Applications

Latent Class Trees with the Three-Step Approach

Mattis Van den Bergh et al.

STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL (2019)

Article Mathematics, Interdisciplinary Applications

Two-Step Estimation of Models Between Latent Classes and External Variables

Zsuzsa Bakk et al.

PSYCHOMETRIKA (2018)

Article Mathematics, Interdisciplinary Applications

Mostly Harmless Direct Effects: A Comparison of Different Latent Markov Modeling Approaches

Roberto Di Mari et al.

STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL (2018)

Article Psychology, Educational

Multidimensional Extension of Multiple Indicators Multiple Causes Models to Detect DIF

Soo Lee et al.

EDUCATIONAL AND PSYCHOLOGICAL MEASUREMENT (2017)

Article Mathematics, Interdisciplinary Applications

A Comparison of Three-Step Approaches for Auxiliary Variables in Latent Class and Latent Profile Analysis

Zachary K. Collier et al.

STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL (2017)

Article Mathematics, Interdisciplinary Applications

On the Application of the Three-Step Approach to Growth Mixture Models

Thierno M. O. Diallo et al.

STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL (2017)

Article Mathematics, Interdisciplinary Applications

Measurement Invariance and Differential Item Functioning in Latent Class Analysis With Stepwise Multiple Indicator Multiple Cause Modeling

Katherine E. Masyn

STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL (2017)

Article Mathematics, Interdisciplinary Applications

Robustness of Stepwise Latent Class Modeling With Continuous Distal Outcomes

Zsuzsa Bakk et al.

STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL (2016)

Article Mathematics, Interdisciplinary Applications

Modeling Predictors of Latent Classes in Regression Mixture Models

Minjung Kim et al.

STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL (2016)

Article Mathematics, Interdisciplinary Applications

Covariates and Mixture Modeling: Results of a Simulation Study Exploring the Impact of Misspecified Effects on Class Enumeration

Karen Nylund-Gibson et al.

STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL (2016)

Article Mathematics, Interdisciplinary Applications

Bias-Adjusted Three-Step Latent Markov Modeling With Covariates

Roberto Di Mari et al.

STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL (2016)

Article Mathematics, Interdisciplinary Applications

Auxiliary Variables in Mixture Modeling: Three-Step Approaches Using Mplus

Tihomir Asparouhov et al.

STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL (2014)

Article Social Sciences, Mathematical Methods

Chi-Square Difference Tests for Detecting Differential Functioning in a Multidimensional IRT Model: A Monte Carlo Study

Youngsuk Suh et al.

APPLIED PSYCHOLOGICAL MEASUREMENT (2014)

Article Statistics & Probability

A Monte Carlo evaluation of three methods to detect local dependence in binary data latent class models

Daniel L. Oberski et al.

ADVANCES IN DATA ANALYSIS AND CLASSIFICATION (2013)

Article Political Science

Latent Class Modeling with Covariates: Two Improved Three-Step Approaches

Jeroen K. Vermunt

POLITICAL ANALYSIS (2010)

Article Mathematics, Interdisciplinary Applications

Evaluation of MIMIC-Model Methods for DIF Testing With Comparison to Two-Group Analysis

Carol M. Woods

MULTIVARIATE BEHAVIORAL RESEARCH (2009)