dc.contributor.author
Hagel, Minne Luise
dc.contributor.author
Trutzenberg, Friedemann
dc.contributor.author
Eid, Michael
dc.date.accessioned
2024-05-13T14:57:00Z
dc.date.available
2024-05-13T14:57:00Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/43513
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-43229
dc.description.abstract
As the robust maximum likelihood 𝜒2 goodness-of-fit test had been found to yield inflated type-I error rates for certain two-level confirmatory factor analysis (CFA) models, a new correction for the test was implemented in Mplus version 8.7. In this simulation study, we inspected whether the corrected test statistics follow the expected 𝜒2 distributions when applying more complex two-level models for multitrait-multimethod data with varying sample sizes and correlations within trait factors. Investigating rejection rates and probability-probability plots, we found that the new correction markedly and sufficiently reduced previously inflated rejection rates in conditions with within-trait correlations equal to 1, 100 between-level units, and 10 or 20 within-level units. In other conditions, rejection rates were hardly affected or not sufficiently reduced by the new correction. While in most conditions, 2 within-level units did not suffice, 5 within-level units and 250 between-level units were enough to yield correct rejection rates given within-trait correlations did not exceed 0.80. Correlations above 0.80 required larger sample sizes. In planning studies with multilevel CFA models, researchers should be aware that sample size requirements for likelihood-based model fit evaluations can depend on several different factors and might consider conducting Monte Carlo simulations tailored to their specific modeling conditions.
en
dc.format.extent
30 Seiten
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
dc.subject
robust chi-square
en
dc.subject
multilevel modeling
en
dc.subject
multitrait-multimethod analysis
en
dc.subject
Monte Carlo simulation
en
dc.subject.ddc
100 Philosophie und Psychologie::150 Psychologie::150 Psychologie
dc.title
Applying the Robust Chi-Square Goodness-of-Fit Test to Multilevel Multitrait-Multimethod Models: A Monte Carlo Simulation Study on Statistical Performance
dc.type
Wissenschaftlicher Artikel
dc.identifier.sepid
98987
dcterms.bibliographicCitation.doi
10.3390/psycholint6020029
dcterms.bibliographicCitation.journaltitle
Psychology International
dcterms.bibliographicCitation.number
2
dcterms.bibliographicCitation.originalpublishername
MDPI
dcterms.bibliographicCitation.pagestart
462
dcterms.bibliographicCitation.pageend
491
dcterms.bibliographicCitation.volume
6
dcterms.bibliographicCitation.url
https://doi.org/10.3390/psycholint6020029
refubium.affiliation
Erziehungswissenschaft und Psychologie
refubium.note.author
Die Publikation wurde aus Open Access Publikationsgeldern der Freien Universität Berlin gefördert.
de
refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.isPartOf.eissn
2813-9844