Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Умовний аналіз процесів (модерована медіація)× | Регресія звичайно найменших квадратів (ЗНК)× | |
|---|---|---|
| Галузь≠ | Причинно-наслідковий висновок | Економетрика |
| Родина | Regression model | Regression model |
| Рік появи≠ | 2018 | 2019 |
| Автор методу≠ | Andrew F. Hayes (PROCESS framework); Preacher, Rucker & Hayes (moderated mediation) | Wooldridge (textbook treatment); classical least squares |
| Тип≠ | Regression-based conditional process model | Linear regression |
| Основоположне джерело≠ | Hayes, A. F. (2018). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach (2nd ed.). The Guilford Press. ISBN: 978-1462534654 | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| Інші назви≠ | moderated mediation, moderated mediation analysis, PROCESS model, Hayes PROCESS conditional process model | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Пов'язані | 5 | 5 |
| Підсумок≠ | Conditional process analysis is Andrew F. Hayes's regression-based PROCESS framework (2018) that combines mediation and moderation in a single model, testing how an indirect effect changes across levels of a moderator. It quantifies conditional indirect and conditional direct effects and tests them with bootstrap confidence intervals. | Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE). |
| ScholarGateНабір даних ↗ |
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