Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Дослідження тестування моделей× | Дослідження з перевіркою гіпотез× | |
|---|---|---|
| Галузь | Дизайн дослідження | Дизайн дослідження |
| Родина | Process / pipeline | Process / pipeline |
| Рік появи≠ | 1970s (Joreskog 1969–1973); widely adopted in social sciences by the 1980s–1990s | Early 20th century (Fisher 1925; Neyman–Pearson 1933) |
| Автор методу≠ | Karl G. Joreskog (SEM/LISREL framework); formalized through structural equation modeling tradition | Karl Pearson, Ronald A. Fisher, Jerzy Neyman, Egon Pearson |
| Тип≠ | Confirmatory quantitative research design | Quantitative confirmatory research design |
| Основоположне джерело≠ | Kline, R. B. (2015). Principles and Practice of Structural Equation Modeling (4th ed.). Guilford Press. ISBN: 978-1462523344 | Kerlinger, F. N., & Lee, H. B. (1986). Foundations of Behavioral Research (3rd ed.). Holt, Rinehart and Winston. ISBN: 978-0030417603 |
| Інші назви | model-based research, structural model testing, theory-testing research, MTR | hypothetico-deductive research, confirmatory quantitative research, null hypothesis significance testing, NHST design |
| Пов'язані≠ | 5 | 4 |
| Підсумок≠ | Model testing research is a confirmatory quantitative design in which the researcher specifies a theoretical model — depicting hypothesized relationships among constructs — and then tests how well that model fits empirical data. Drawing primarily on structural equation modeling (SEM) and confirmatory factor analysis (CFA), it evaluates whether the data-implied covariance structure is consistent with the theoretically derived one, yielding fit indices that indicate model-data correspondence. | Hypothesis testing research is a quantitative design in which the investigator derives one or more explicit, falsifiable propositions from theory, translates them into a null hypothesis (H0) and an alternative hypothesis (H1), collects empirical data, and then applies an inferential statistical test to decide whether the evidence is sufficient to reject H0. The approach is the dominant paradigm for confirmatory science across the social, behavioral, health, and natural sciences. |
| ScholarGateНабір даних ↗ |
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