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Mixed Markov Latent Class Models

Authors: Frank van de Pol; Rolf Langeheine;

Mixed Markov Latent Class Models

Abstract

The process of change in a discrete characteristic is seldom the same for every respondent in a panel survey. Mixed Markov latent class models describe cross-tables of consecutive measurements in terms of several Markov chains. Each of these chains may be a stayer chain or some kind of mover chain. Markov chains may or may not be latent; i.e., they may or may not be unreliably measured. In this paper, we extend the mixed Markov latent class model to several subpopulations. We give formulas for estimation under equality restrictions when some parameters are fixed, and we give estimation priorities for several types of restrictions. Equality restrictions on parameters across subpopulations can be tested by means of a likelihood ratio test. To illustrate, we reanalyze a data set from Wiggins (1973).

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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
79
Top 10%
Top 10%
Average
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