विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| दीर्घकालिक पुष्टिकारी कारक विश्लेषण (Longitudinal Confirmatory Factor Analysis)× | Structural Equation Modeling× | |
|---|---|---|
| क्षेत्र≠ | मनोमिति | अनुसंधान सांख्यिकी |
| परिवार≠ | Latent structure | Process / pipeline |
| उद्भव वर्ष≠ | 1970s–1990s | 1921 |
| प्रवर्तक≠ | Karl Jöreskog (CFA framework); longitudinal extension by Wheaton, Muthén, and Alwin in the 1970s–1990s | Sewall Wright |
| प्रकार≠ | Longitudinal latent variable / measurement model | Method |
| मौलिक स्रोत≠ | Widaman, K. F. & Reise, S. P. (1997). Exploring the measurement invariance of psychological instruments: Applications in the substance use domain. In K. J. Bryant, M. Windle & S. G. West (Eds.), The science of prevention: Methodological advances from alcohol and substance abuse research (pp. 281–324). American Psychological Association. link ↗ | Jöreskog, K. G., & Sörbom, D. (1973). LISREL: A general computer program for estimating a linear structural equation system. Research Bulletin 73-5. University of Stockholm. link ↗ |
| उपनाम | longitudinal CFA, repeated-measures CFA, longitudinal measurement model, panel CFA | SEM, path analysis, latent variable modeling, causal modeling |
| संबंधित≠ | 6 | 3 |
| सारांश≠ | Longitudinal confirmatory factor analysis (longitudinal CFA) applies a theoretically specified measurement model to data collected at two or more time points. Its primary purpose is to verify that a scale measures the same latent construct in the same way over time — a prerequisite for drawing valid conclusions about change from repeated-measures data. | Structural equation modeling (SEM) is a comprehensive statistical framework combining path analysis (Sewall Wright, 1921) and confirmatory factor analysis to test complex causal models linking observed and latent variables. Formalized by Jöreskog (1973) with LISREL software, SEM enables simultaneous estimation of measurement relationships (how variables measure latent constructs) and structural relationships (how constructs influence outcomes), making it powerful for theory testing in psychology, epidemiology, organizational research, and health sciences where complex mediation, moderation, and latent processes require integrated analysis. |
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