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Exploring sources of construct-relevant multidimensionality in psychiatric measurement. A tutorial […]
Morin, Alexandre J. S.; Arens, A. Katrin; Tran, Antoine; Caci, Hervé
Zeitschriftenbeitrag
| In: International Journal of Methods in Psychiatric Research | 2016
36964 Endnote
Autor*innen:
Morin, Alexandre J. S.; Arens, A. Katrin; Tran, Antoine; Caci, Hervé
Titel:
Exploring sources of construct-relevant multidimensionality in psychiatric measurement. A tutorial and illustration using the Composite Scale of Morningness
In:
International Journal of Methods in Psychiatric Research, 25 (2016) 4, S. 277-288
DOI:
10.1002/mpr.1485
URN:
urn:nbn:de:0111-dipfdocs-201733
URL:
http://www.dipfdocs.de/volltexte/2020/20173/pdf/IJMPR_2016_4_Morin_et_al_Exploring_sources_of_construct-relevant_multidimensionality_A.pdf
Dokumenttyp:
3a. Beiträge in begutachteten Zeitschriften; Aufsatz (keine besondere Kategorie)
Sprache:
Englisch
Schlagwörter:
Alter; Biorhythmus; Einflussfaktor; Erhebungsinstrument; Erwachsener; Faktorenanalyse; Geschlecht; Indikator; Messung; Methode; Psychiatrie; Psychometrie; Strukturgleichungsmodell
Abstract:
This paper illustrates a psychometric approach of broad relevance to psychiatric research instruments. Many instruments include indicators related to more than one source of true-score variance due to the: (1) assessment of conceptually adjacent constructs; (2) the presence of a global construct underlying answers to items designed to assess multiple dimensions. Exploratory structural equation modelling (ESEM) is naturally suited to the investigation of the first source, whereas bifactor models are particularly suited to the investigation of the second source. When both sources are present, bifactor-ESEM becomes the model of choice. To illustrate this framework, we use the responses of 1159 adults [655 female, 504 male, mean age (Mage) = 41.84] who completed the French Version of the Composite Scale of Morningness (CSM). We investigate the factor structure of the CSM, test the relations between CSM factors and body mass index, and verify the measurement invariance of the model across gender and age groups. (DIPF/Orig.)
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