विधियों की तुलना करें

	पैनल सरल रैखिक प्रतिगमन	हायरार्किकल लीनियर मॉडल (HLM)
क्षेत्र	सांख्यिकी	सांख्यिकी
परिवार	Regression model	Regression model
उद्भव वर्ष	1986	1992
प्रवर्तक	Hsiao (1986); Baltagi (seminal textbook treatments)	Bryk & Raudenbush
प्रकार	Linear regression (panel data)	Multilevel linear regression
मौलिक स्रोत	Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586	Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods (2nd ed.). Sage Publications. ISBN: 978-0761919049
उपनाम	panel SLR, longitudinal simple regression, two-way panel simple regression, fixed-effects simple linear regression	HLM, multilevel linear model, nested data model, random coefficient model
संबंधित	5	4
सारांश	Panel simple linear regression models a continuous outcome as a linear function of a single predictor using data that track the same entities (individuals, firms, countries) across multiple time periods. It separates within-entity variation from between-entity variation, enabling control for unobserved time-invariant characteristics that would confound a plain cross-sectional regression.	The Hierarchical Linear Model (HLM) is a multilevel regression method designed for data in which lower-level units (e.g., students, patients) are nested within higher-level groups (e.g., schools, hospitals). It simultaneously models within-group relationships and between-group variation, producing unbiased estimates and correct standard errors that ordinary regression cannot provide for nested data.