পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| বহুস্তরীয় রাশ মডেল× | বহুস্তরীয় পরিমাপের সমতা (Multilevel Measurement Invariance)× | |
|---|---|---|
| ক্ষেত্র | মনোমিতি | মনোমিতি |
| পরিবার | Latent structure | Latent structure |
| উদ্ভবের বছর≠ | 1997 | 2000s |
| প্রবর্তক≠ | Adams, Wilson & Wu | Muthén, Asparouhov, and colleagues |
| ধরন≠ | Hierarchical item response model | Measurement model evaluation |
| মৌলিক উৎস≠ | Adams, 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 ↗ |
| অপর নাম | hierarchical Rasch model, random-effects Rasch model, multilevel IRT Rasch, MRCML model | MLMI, multilevel factorial invariance, cross-level measurement invariance, multilevel CFA invariance |
| সম্পর্কিত≠ | 5 | 3 |
| সারসংক্ষেপ≠ | The 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. |
| ScholarGateডেটাসেট ↗ |
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