পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| বহুমাত্রিক মডেল পরীক্ষণ গবেষণা× | কাঠামোগত সমীকরণ মডেলিং× | |
|---|---|---|
| ক্ষেত্র≠ | গবেষণা নকশা | গবেষণা পরিসংখ্যান |
| পরিবার | Process / pipeline | Process / pipeline |
| উদ্ভবের বছর≠ | 1970s–1980s (multivariate model testing as a distinct approach) | 1921 |
| প্রবর্তক≠ | Karl Jöreskog (SEM/LISREL framework); Barbara Tabachnick & Linda Fidell (multivariate methods synthesis) | Sewall Wright |
| ধরন≠ | Quantitative confirmatory research design | Method |
| মৌলিক উৎস≠ | Tabachnick, B. G., & Fidell, L. S. (2019). Using Multivariate Statistics (7th ed.). Pearson. ISBN: 978-0134790541 | 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 ↗ |
| অপর নাম | multivariate model testing, multivariate structural testing, multivariate confirmatory modeling, MVMT research | SEM, path analysis, latent variable modeling, causal modeling |
| সম্পর্কিত≠ | 5 | 3 |
| সারসংক্ষেপ≠ | Multivariate model testing research is a confirmatory quantitative design in which a theoretically derived model involving multiple variables and their interrelationships is formally tested against empirical data. Rather than exploring patterns inductively, the researcher specifies a model a priori — capturing hypothesized directional paths, latent constructs, or covariance structures — and then evaluates how well this model reproduces the observed data using techniques such as structural equation modeling, confirmatory factor analysis, or multivariate path analysis. | 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. |
| ScholarGateডেটাসেট ↗ |
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