Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Анализ дифференциального функционирования элементов (DIF)× | Моделирование структурными уравнениями (SEM)× | |
|---|---|---|
| Область≠ | Психометрия | Статистика |
| Семейство | Latent structure | Latent structure |
| Год появления≠ | 1988 | 1970 |
| Автор метода≠ | Paul W. Holland & Dorothy T. Thayer (Mantel-Haenszel approach, 1988) | Karl Jöreskog (LISREL framework, 1970s) |
| Тип≠ | Item-level fairness / measurement equivalence analysis | Latent variable / causal modeling |
| Основополагающий источник≠ | Holland, P. W. & Thayer, D. T. (1988). Differential Item Performance and the Mantel-Haenszel Procedure. ETS Research Report Series. link ↗ | Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage Learning. ISBN: 978-1473756540 |
| Другие названия≠ | Madde Yanlılık Analizi (DIF — Differential Item Functioning), item bias analysis, Mantel-Haenszel DIF, Lord chi-square DIF | Yapısal Eşitlik Modellemesi (SEM), structural equation modelling, covariance structure analysis, latent variable modeling |
| Связанные≠ | 4 | 5 |
| Сводка≠ | Differential Item Functioning analysis examines whether examinees from different groups — such as gender, ethnicity, or language background — who have the same underlying ability respond differently to a test item. First formalised by Holland and Thayer in 1988 via the Mantel-Haenszel procedure, it is the principal tool in modern test development for detecting and removing item bias. | Structural equation modeling is a multivariate statistical framework that simultaneously estimates a measurement model — relating observed indicators to latent constructs — and a structural model specifying directional or reciprocal relationships among those constructs. Rooted in the LISREL tradition developed by Karl Jöreskog in the 1970s, SEM is the standard tool for testing complex theoretical models in the social, behavioural, and management sciences. |
| ScholarGateНабор данных ↗ |
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