পদ্ধতির তুলনা করুন

	লজিস্টিক রিগ্রেশন	কাঠামোগত সমীকরণ মডেলিং
ক্ষেত্র	গবেষণা পরিসংখ্যান	গবেষণা পরিসংখ্যান
পরিবার	Process / pipeline	Process / pipeline
উদ্ভবের বছর	1958	1921
প্রবর্তক	David Roxbee Cox	Sewall Wright
ধরন	Method	Method
মৌলিক উৎস	Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242.	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.
অপর নাম	logit model, binomial logistic regression, LR	SEM, path analysis, latent variable modeling, causal modeling
সম্পর্কিত	3	3
সারসংক্ষেপ	Logistic regression is a statistical method for modeling the probability of a binary outcome (disease present/absent, success/failure) as a function of continuous and categorical predictors. Developed by David Roxbee Cox (1958), it solves the problem of predicting categorical outcomes by applying a logistic transformation to constrain predictions to the [0,1] probability interval, enabling accurate risk stratification, diagnostic prediction, and causal inference in epidemiology, medicine, and social science.	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.