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Daudzlīmeņu konverģentā validitāte×Testēšana uz mērījumu ekvivalenci×
NozarePsihometrijaPsihometrija
SaimeLatent structureLatent structure
Izcelsmes gads20052000
AutorsDyer, Hanges & Hall; Chen, Bliese & MathieuVandenberg & Lance
TipsMeasurement validity evaluationMulti-group confirmatory factor analysis procedure
PirmavotsDyer, N. G., Hanges, P. J. & Hall, R. J. (2005). Applying multilevel confirmatory factor analysis techniques to the study of leadership. Leadership Quarterly, 16(1), 149–167. DOI ↗Vandenberg, R. J., & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature. Organizational Research Methods, 3(1), 4–70. DOI ↗
Citi nosaukumicross-level convergent validity, multilevel measurement validity, between-level convergent validityFactorial Invariance, Measurement Equivalence, Configural-Metric-Scalar Testing, Ölçüm Değişmezliği
Saistītās43
KopsavilkumsMultilevel convergent validity evaluates whether items or scales intended to measure the same construct show coherent, strong associations at each level of a nested data structure — within individuals, within groups, and between groups. It extends classical convergent validity from single-level measurement models into the multilevel confirmatory factor analysis (ML-CFA) framework.Measurement invariance testing is a sequence of nested confirmatory factor analysis (CFA) models that examines whether a psychological scale measures the same latent construct in the same way across distinct groups or time points. Systematized and popularized by Vandenberg and Lance (2000), the procedure tests a hierarchy of constraints — from identical factor patterns to identical item intercepts — so that researchers can justify meaningful group comparisons on latent means.
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ScholarGateSalīdzināt metodes: Multilevel Convergent Validity · Measurement Invariance. Izgūts 2026-06-19 no https://scholargate.app/lv/compare