Längsschnittdaten und Mehrebenenanalyse

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In the present article a few basic multilevel models for longitudinal data are introduced and applied to the Household Income and Labor Dynamics in Australia Survey 10 (HILDA) for demonstrational purposes. The covered models are adaptions of the random-intercept-only model, the random-intercept models and the random- intercept random-slope model with and without level-1 and level-2 predictors to longitudinal data. The modeling of contextual effects is covered. One particularity in longitudinal data is the fact that persons (level-2) may be regarded as the context of the time-varying observations on level-1. To incorporate the macro-level of sociology, it is necessary to expand the model to a third level. A model with three levels is introduced and in addition a simple growth curve model and a multivariate multilevel model are presented.

Translated title of the contributionLongitudinal Data and Multilevel Analysis
Original languageGerman
JournalKölner Zeitschrift für Soziologie und Sozialpsychologie
Issue number1
Pages (from-to)189-218
Number of pages30
Publication statusPublished - 09.2014
Externally publishedYes

    Research areas

  • Sociology - Contextual effects, Longitudinal data analysis, Multilevel modeling, Panel data