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dc.contributor.authorde Haan-Rietdijk, S
dc.contributor.authorKuppens, P
dc.contributor.authorBergeman, CS
dc.contributor.authorSheeber, LB
dc.contributor.authorAllen, NB
dc.contributor.authorHamaker, EL
dc.date.accessioned2020-12-18T03:20:57Z
dc.date.available2020-12-18T03:20:57Z
dc.date.issued2017-11
dc.identifier.citationde Haan-Rietdijk, S., Kuppens, P., Bergeman, C. S., Sheeber, L. B., Allen, N. B. & Hamaker, E. L. (2017). On the Use of Mixed Markov Models for Intensive Longitudinal Data.. Multivariate Behav Res, 52 (6), pp.747-767. https://doi.org/10.1080/00273171.2017.1370364.
dc.identifier.issn0027-3171
dc.identifier.urihttp://hdl.handle.net/11343/255731
dc.description.abstractMarkov modeling presents an attractive analytical framework for researchers who are interested in state-switching processes occurring within a person, dyad, family, group, or other system over time. Markov modeling is flexible and can be used with various types of data to study observed or latent state-switching processes, and can include subject-specific random effects to account for heterogeneity. We focus on the application of mixed Markov models to intensive longitudinal data sets in psychology, which are becoming ever more common and provide a rich description of each subject's process. We examine how specifications of a Markov model change when continuous random effect distributions are included, and how mixed Markov models can be used in the intensive longitudinal research context. Advantages of Bayesian estimation are discussed and the approach is illustrated by two empirical applications.
dc.languageeng
dc.publisherInforma UK Limited
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0
dc.titleOn the Use of Mixed Markov Models for Intensive Longitudinal Data.
dc.typeJournal Article
dc.identifier.doi10.1080/00273171.2017.1370364
melbourne.affiliation.departmentMelbourne School of Psychological Sciences
melbourne.source.titleMultivariate Behavioral Research
melbourne.source.volume52
melbourne.source.issue6
melbourne.source.pages747-767
dc.rights.licenseCC BY-NC-ND
melbourne.elementsid1300409
melbourne.openaccess.pmchttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC5698102
melbourne.contributor.authorAllen, Nicholas
dc.identifier.eissn1532-7906
melbourne.accessrightsOpen Access


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