方法对比
并排查看您选择的方法;存在差异的行会高亮显示。
| 模型检验研究× | 因果比较研究× | |
|---|---|---|
| 领域 | 研究设计 | 研究设计 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1970s (Joreskog 1969–1973); widely adopted in social sciences by the 1980s–1990s | 1964 |
| 提出者≠ | Karl G. Joreskog (SEM/LISREL framework); formalized through structural equation modeling tradition | Fred N. Kerlinger |
| 类型≠ | Confirmatory quantitative research design | Non-experimental quantitative research design |
| 开创性文献≠ | Kline, R. B. (2015). Principles and Practice of Structural Equation Modeling (4th ed.). Guilford Press. ISBN: 978-1462523344 | Kerlinger, F. N. (1964). Foundations of Behavioral Research. Holt, Rinehart and Winston. link ↗ |
| 别名 | model-based research, structural model testing, theory-testing research, MTR | ex post facto research, causal-comparative design, retrospective causal study, CCR |
| 相关≠ | 5 | 3 |
| 摘要≠ | 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. | Causal-comparative research is a non-experimental quantitative design in which the researcher compares two or more groups that already differ on an independent variable — one that was not manipulated — to investigate possible causes or consequences of that difference. Because group membership is pre-existing rather than randomly assigned, the design can suggest causal relationships but cannot establish them with the certainty of a true experiment. It is widely used in education, psychology, and social sciences when experimental manipulation is impractical or unethical. |
| ScholarGate数据集 ↗ |
|
|