Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Изследване чрез сравнително тестване на модели× | Изследване с проверка на хипотези× | |
|---|---|---|
| Област | Дизайн на изследването | Дизайн на изследването |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 1969–2000s | Early 20th century (Fisher 1925; Neyman–Pearson 1933) |
| Създател≠ | Rooted in structural equation modeling traditions; formalized through Jöreskog (1969) and extended by Vandenberg & Lance (2000) | Karl Pearson, Ronald A. Fisher, Jerzy Neyman, Egon Pearson |
| Тип≠ | Quantitative confirmatory-comparative research design | Quantitative confirmatory research design |
| Основополагащ източник≠ | 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 |
| Други названия | comparative model comparison, cross-group model testing, competing model comparison research, comparative structural model evaluation | hypothetico-deductive research, confirmatory quantitative research, null hypothesis significance testing, NHST design |
| Свързани | 4 | 4 |
| Резюме≠ | Comparative model testing research is a quantitative design in which two or more theoretically motivated models — or the same model evaluated across distinct groups or conditions — are systematically tested and compared using fit indices, likelihood-ratio tests, or information criteria. The goal is to determine which model better represents the data structure, or whether a model's parameter structure holds equally across comparison groups. | 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. |
| ScholarGateНабор от данни ↗ |
|
|