Publication Type
Journal Article
Version
acceptedVersion
Publication Date
7-2011
Abstract
There are many areas of organizational research where we may be concerned with subgroup differences in status change profiles. The purpose of this article is to illustrate, using a real data set on retirees' postretirement employment statuses (PES), how mixture latent Markov modeling may be applied to substantive research in organizational settings to identify population subgroups with varying status change profiles and examine their correlates, by modeling unobserved heterogeneity in longitudinal qualitative changes. Steps in the modeling process are highlighted and limitations, cautions, recommendations, and extensions of the technique are discussed.
Keywords
mixture latent Markov modeling, latent transition analysis, longitudinal analysis, qualitative status change
Discipline
Industrial and Organizational Psychology | Quantitative Psychology
Research Areas
Psychology
Publication
Organizational Research Methods
Volume
14
Issue
3
First Page
411
Last Page
431
ISSN
1094-4281
Identifier
10.1177/1094428109357107
Publisher
SAGE
Citation
WANG, Mo, & CHAN, David.(2011). Mixture Latent Markov Modeling: Identifying and Predicting Unobserved Heterogeneity in Longitudinal Qualitative Status change. Organizational Research Methods, 14(3), 411-431.
Available at: https://ink.library.smu.edu.sg/soss_research/982
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1177/1094428109357107