পদ্ধতির তুলনা করুন

	বহুমাত্রিক মডেল পরীক্ষণ গবেষণা	পাথ অ্যানালাইসিস (Path Analysis)
ক্ষেত্র	গবেষণা নকশা	পরিসংখ্যান
পরিবার	Process / pipeline	Latent structure
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	Causal / mediation model
মৌলিক উৎস	Tabachnick, B. G., & Fidell, L. S. (2019). Using Multivariate Statistics (7th ed.). Pearson. ISBN: 978-0134790541	Wright, S. (1921). Correlation and causation. Journal of Agricultural Research, 20(7), 557–585.
অপর নাম	multivariate model testing, multivariate structural testing, multivariate confirmatory modeling, MVMT research	PA, path coefficient analysis, observed-variable SEM, causal path modeling
সম্পর্কিত	5	5
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.	Path analysis tests a researcher-specified causal diagram among observed variables by decomposing their intercorrelations into direct effects, indirect (mediated) effects, and spurious associations. Developed by Sewall Wright in 1921, it is the observed-variable special case of structural equation modeling and remains a standard tool for theory-driven multivariate causal inference.