Mixture Latent Markov Modeling: Identifying and Predicting Unobserved Heterogeneity in Longitudinal Qualitative Status change

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 app...

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Main Authors:	WANG, Mo, CHAN, David
格式:	text
語言:	English
出版:	Institutional Knowledge at Singapore Management University 2011
主題:	mixture latent Markov modeling latent transition analysis longitudinal analysis qualitative status change Industrial and Organizational Psychology Quantitative Psychology
在線閱讀:	https://ink.library.smu.edu.sg/soss_research/982 https://ink.library.smu.edu.sg/context/soss_research/article/2238/viewcontent/MixtureLatentMarkovModel_2011.pdf
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spelling	sg-smu-ink.soss_research-22382018-03-26T05:26:16Z Mixture Latent Markov Modeling: Identifying and Predicting Unobserved Heterogeneity in Longitudinal Qualitative Status change WANG, Mo CHAN, David 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. 2011-07-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/soss_research/982 info:doi/10.1177/1094428109357107 https://ink.library.smu.edu.sg/context/soss_research/article/2238/viewcontent/MixtureLatentMarkovModel_2011.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School of Social Sciences eng Institutional Knowledge at Singapore Management University mixture latent Markov modeling latent transition analysis longitudinal analysis qualitative status change Industrial and Organizational Psychology Quantitative Psychology
institution	Singapore Management University
building	SMU Libraries
continent	Asia
country	Singapore Singapore
content_provider	SMU Libraries
collection	InK@SMU
language	English
topic	mixture latent Markov modeling latent transition analysis longitudinal analysis qualitative status change Industrial and Organizational Psychology Quantitative Psychology
spellingShingle	mixture latent Markov modeling latent transition analysis longitudinal analysis qualitative status change Industrial and Organizational Psychology Quantitative Psychology WANG, Mo CHAN, David Mixture Latent Markov Modeling: Identifying and Predicting Unobserved Heterogeneity in Longitudinal Qualitative Status change
description	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.
format	text
author	WANG, Mo CHAN, David
author_facet	WANG, Mo CHAN, David
author_sort	WANG, Mo
title	Mixture Latent Markov Modeling: Identifying and Predicting Unobserved Heterogeneity in Longitudinal Qualitative Status change
title_short	Mixture Latent Markov Modeling: Identifying and Predicting Unobserved Heterogeneity in Longitudinal Qualitative Status change
title_full	Mixture Latent Markov Modeling: Identifying and Predicting Unobserved Heterogeneity in Longitudinal Qualitative Status change
title_fullStr	Mixture Latent Markov Modeling: Identifying and Predicting Unobserved Heterogeneity in Longitudinal Qualitative Status change
title_full_unstemmed	Mixture Latent Markov Modeling: Identifying and Predicting Unobserved Heterogeneity in Longitudinal Qualitative Status change
title_sort	mixture latent markov modeling: identifying and predicting unobserved heterogeneity in longitudinal qualitative status change
publisher	Institutional Knowledge at Singapore Management University
publishDate	2011
url	https://ink.library.smu.edu.sg/soss_research/982 https://ink.library.smu.edu.sg/context/soss_research/article/2238/viewcontent/MixtureLatentMarkovModel_2011.pdf
_version_	1770571045789499392

Mixture Latent Markov Modeling: Identifying and Predicting Unobserved Heterogeneity in Longitudinal Qualitative Status change

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