विधियों की तुलना करें

	मिश्रित प्रभाव मॉडल	सामान्यीकृत रेखीय मॉडल (GLM)
क्षेत्र	सांख्यिकी	सांख्यिकी
परिवार	Regression model	Regression model
उद्भव वर्ष	1982	1972
प्रवर्तक	Laird & Ware	John A. Nelder & Robert W. M. Wedderburn
प्रकार	Mixed effects regression	Regression framework
मौलिक स्रोत	Laird, N. M., & Ware, J. H. (1982). Random-effects models for longitudinal data. Biometrics, 38(4), 963–974.	Nelder, J. A., & Wedderburn, R. W. M. (1972). Generalized linear models. Journal of the Royal Statistical Society: Series A (General), 135(3), 370–384.
उपनाम	LME, LMM, mixed model, random effects model	GLM, generalized regression, exponential family regression, link-function model
संबंधित	4	6
सारांश	A mixed effects model (or linear mixed model) extends ordinary regression by including both fixed effects — population-level parameters shared by all observations — and random effects that capture subject-, group-, or cluster-level variability. It is the standard tool for repeated-measures, longitudinal, and multilevel data where observations within the same unit are correlated.	The Generalized Linear Model is a unified regression framework that extends ordinary linear regression to outcomes from the exponential family — including binary, count, proportion, and continuous positive outcomes. A link function connects the linear predictor to the mean of the response, enabling principled modelling beyond the Gaussian case.