Replication Data for: Scale length does matter: Recommendations for Measurement Invariance Testing with Categorical Factor Analysis and Item Response Theory Approaches

Dataset

DOI

These files contain the code and data used to evaluate the impact of MG-CCFA- and MG-IRT-based hypotheses and testing strategies on the power to detect violations of MI, for which we performed two simulation studies. In the first study, an invariance scenario was simulated where parameters were invariant between groups. The second study simulated a non-invariance scenario where model parameters varied between groups.

See the file Data Report - Replication Data for - Scale length does matter - Recommendations for Measurement Invariance Testing.pdf for, among other things, more information about the files and how they relate.

Identifier
DOI	https://doi.org/10.34894/K2ZKED
Related Identifier	https://doi.org/10.3758/s13428-021-01690-7
Metadata Access	https://dataverse.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.34894/K2ZKED

Provenance
Creator	D'Urso, Damiano ; Vermunt, Jeroen ; de Roover, Kim ; Tijmstra, Jesper
Publisher	DataverseNL
Contributor	D'Urso, Damiano; Vermunt, Jeroen; de Roover, Kim; DataverseNL
Publication Year	2022
Rights	CC-BY-4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by/4.0
OpenAccess	true
Contact	D'Urso, Damiano (Tilburg University); Vermunt, Jeroen (Tilburg University); de Roover, Kim (KU Leuven)

Representation
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Version	1.0
Discipline	Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Life Sciences; Psychology; Social Sciences; Social and Behavioural Sciences; Soil Sciences