เปรียบเทียบวิธี
ดูวิธีที่เลือกเทียบกันแบบเคียงข้าง แถวที่ต่างกันจะถูกเน้นไว้
| การวิจัยเชิงทดสอบโมเดล× | การวิจัยเชิงยืนยัน× | |
|---|---|---|
| สาขาวิชา | การออกแบบการวิจัย | การออกแบบการวิจัย |
| ตระกูล | Process / pipeline | Process / pipeline |
| ปีกำเนิด≠ | 1970s (Joreskog 1969–1973); widely adopted in social sciences by the 1980s–1990s | 1934 (Popper); widely adopted in social sciences from 1960s onward |
| ผู้ริเริ่ม≠ | Karl G. Joreskog (SEM/LISREL framework); formalized through structural equation modeling tradition | Karl Popper (falsificationism); formalized in behavioral sciences by Paul Meehl and others |
| ประเภท≠ | Confirmatory quantitative research design | Quantitative research design |
| แหล่งต้นตำรับ≠ | Kline, R. B. (2015). Principles and Practice of Structural Equation Modeling (4th ed.). Guilford Press. ISBN: 978-1462523344 | Popper, K. R. (1959). The Logic of Scientific Discovery. Hutchinson. ISBN: 978-0415278447 |
| ชื่อเรียกอื่น | model-based research, structural model testing, theory-testing research, MTR | hypothesis-testing research, deductive research, theory-testing research, confirmatory study |
| ที่เกี่ยวข้อง≠ | 5 | 4 |
| สรุป≠ | 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. | Confirmatory research is a deductive quantitative design in which the researcher specifies hypotheses derived from existing theory before data collection, then tests whether the data support or refute those hypotheses. Unlike exploratory approaches that generate ideas from data, confirmatory research begins with an established theoretical framework, pre-registers predictions, and applies statistical tests to evaluate those predictions against empirical evidence. It is the backbone of hypothesis-driven social, behavioral, and health science inquiry. |
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