Latent Markov factor analysis: A mixture modeling approach for evaluating within- and between-person measurement model differences in intensive longitudinal data

L.V.D.E. Vogelsmeier

Latent Markov factor analysis: A mixture modeling approach for evaluating within- and between-person measurement model differences in intensive longitudinal data

L.V.D.E. Vogelsmeier^*

^*Corresponding author for this work

Methodology and Statistics

Research output: Thesis › Doctoral Thesis

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Original language	English
Qualification	Doctor of Philosophy
Supervisors/Advisors	Vermunt, Jeroen, Promotor De Roover, Kim, Promotor Ceulemans, Eva, Promotor, External person Hamaker, E. L., Member PhD commission, External person Wicherts, Jelte, Member PhD commission Bakk, Z., Member PhD commission
Award date	14 Jan 2022
Place of Publication	s.l.
Publisher	Ridderprint
Print ISBNs	978-94-6416-941-6
Publication status	Published - 14 Jan 2022

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Vogelsmeier Latent 14-01-2021Final published version, 4.32 MB

Cite this

@phdthesis{91f039178a3f4d11a14bb4e14e2a0777,

title = "Latent Markov factor analysis: A mixture modeling approach for evaluating within- and between-person measurement model differences in intensive longitudinal data",

author = "L.V.D.E. Vogelsmeier",

year = "2022",

month = jan,

day = "14",

language = "English",

isbn = "978-94-6416-941-6",

publisher = "Ridderprint",

}