ScholarGate
Asistent

Usporedite metode

Pregledajte odabrane metode jednu uz drugu; retci koji se razlikuju su istaknuti.

Višerazinski Raschov model×Višerazinska invarijancija mjerenja×
PodručjePsihometrijaPsihometrija
ObiteljLatent structureLatent structure
Godina nastanka19972000s
TvoracAdams, Wilson & WuMuthén, Asparouhov, and colleagues
VrstaHierarchical item response modelMeasurement model evaluation
Temeljni izvorAdams, R. J., Wilson, M. & Wu, M. (1997). Multilevel item response models: An approach to errors in variables regression. Journal of Educational and Behavioral Statistics, 22(1), 47–76. DOI ↗Muthén, B. O., & Asparouhov, T. (2009). Multilevel factor analysis of class and student achievement components. Journal of Educational and Behavioral Statistics, 34(2), 250–270. link ↗
Drugi nazivihierarchical Rasch model, random-effects Rasch model, multilevel IRT Rasch, MRCML modelMLMI, multilevel factorial invariance, cross-level measurement invariance, multilevel CFA invariance
Srodne53
SažetakThe multilevel Rasch model extends the standard Rasch model to data with a nested structure — for example, students within classrooms within schools — by embedding person ability parameters inside a hierarchical linear model. It yields item difficulty estimates on a logit scale while simultaneously partitioning person-ability variance across cluster levels and correcting standard errors for non-independence.Multilevel measurement invariance testing evaluates whether a latent construct is measured equivalently both within clusters (e.g., individuals within teams) and between clusters (e.g., team-level aggregates). It extends standard measurement invariance procedures to nested data structures commonly encountered in organisational, educational, and cross-cultural research.
ScholarGateSkup podataka
  1. v1
  2. 2 Izvori
  3. PUBLISHED
  1. v1
  2. 2 Izvori
  3. PUBLISHED

Idi na pretraživanje Preuzmi prezentaciju

ScholarGateUsporedite metode: Multilevel Rasch Model · Multilevel Measurement Invariance. Preuzeto 2026-06-19 s https://scholargate.app/hr/compare