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Autor:
Hochweber, Jan; Hartig, Johannes:

Titel:
Analyzing organizational growth in repeated cross-sectional designs using multilevel structural equation modeling

Quelle:
In: Methodology, 13 (2017) 3 , 83-97

URL des Volltextes:
http://www.dipfdocs.de/volltexte/2018/15867/pdf/med_13_3_Hochweber_A.pdf

URN:
urn:nbn:de:0111-pedocs-158678

Sprache:
Englisch

Dokumenttyp:
3a. Beiträge in begutachteten Zeitschriften; Aufsatz (keine besondere Kategorie)

Schlagwörter:
Methodologie, Organisation, Wachstum, Längsschnittuntersuchung, Daten, Datenanalyse, Strukturgleichungsmodell, Mehrebenenanalyse, Latente Wachstumskurvenmodelle, PISA (Programme for International Student Assessment), Simulation, Statistische Methode


Abstract(englisch):
In repeated cross-sections of organizations, different individuals are sampled from the same set of organizations at each time point of measurement. As a result, common longitudinal data analysis methods (e.g., latent growth curve models) cannot be applied in the usual way. In this contribution, a multilevel structural equation modeling approach to analyze data from repeated cross-sections is presented. Results from a simulation study are reported which aimed at obtaining guidelines on appropriate sample sizes. We focused on a situation where linear growth occurs at the organizational level, and organizational growth is predicted by a single organizational level variable. The power to identify an effect of this organizational level variable was moderately to strongly positively related to number of measurement occasions, number of groups, group size, intraclass correlation, effect size, and growth curve reliability. The Type I error rate was close to the nominal alpha level under all conditions. (DIPF/Orig.)


DIPF-Abteilung:
Bildungsqualität und Evaluation

Notizen:

last modified Nov 11, 2016