Original Research ARTICLE
Evaluation of Analysis Approaches for Latent Class Analysis with Auxiliary Linear Growth Model
- 1Southern Methodist University, United States
- 2Anadolu University, Turkey
This study investigated the performance of three selected approaches to estimating a two-phase mixture model, where the first phase was a two-class latent class analysis model and the second phase was a linear growth model with four time points. The three evaluated methods were (a) one-step approach, (b) three-step approach, and (c) case-weight approach. As a result, some important results were demonstrated. First, the case-weight and three-step approaches demonstrated higher convergence rate than the one-step approach. Second, it was revealed that case-weight and three-step approaches generally did better in correct model selection than the one-step approach. Third, it was revealed that parameters were similarly recovered well by all three approaches for the larger class. However, parameter recovery for the smaller class differed between the three approaches. For example, the case-weight approach produced constantly lower empirical standard errors. However, the estimated standard errors were substantially underestimated by the case-weight and three-step approaches when class separation was low. Also, bias was substantially higher for the case-weight approach than the other two approaches.
Keywords: mixture model, latent class analysis, one-step approach, case-weight approach, Three-step approach
Received: 30 Mar 2017;
Accepted: 26 Jan 2018.
Edited by:Oi-Man Kwok, Texas A&M University College Station, United States
Reviewed by:Eun Sook Kim, University of South Florida, United States
Minjung Kim, The Ohio State University, United States
Copyright: © 2018 Kamata, Kara, Patarapichayatham and Lan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Dr. Akihito Kamata, Southern Methodist University, Dallas, 75275-0455, TX, United States, firstname.lastname@example.org