विधियों की तुलना करें

	प्रच्छन्न वृद्धि वक्र मॉडल (LGC)	मिश्रित प्रभाव मॉडल
क्षेत्र	सांख्यिकी	सांख्यिकी
परिवार	Latent structure	Regression model
उद्भव वर्ष	1990	1982
प्रवर्तक	Meredith & Tisak	Laird & Ware
प्रकार	Latent variable / longitudinal growth model	Mixed effects regression
मौलिक स्रोत	Meredith, W. & Tisak, J. (1990). Latent Curve Analysis. Psychometrika, 55(1), 107–122.	Laird, N. M., & Ware, J. H. (1982). Random-effects models for longitudinal data. Biometrics, 38(4), 963–974.
उपनाम	latent growth model, LGC, growth curve model, Gizil Büyüme Eğrisi Modeli	LME, LMM, mixed model, random effects model
संबंधित	5	4
सारांश	The latent growth curve model is a structural equation modelling approach introduced by Meredith and Tisak (1990) for analysing change over time. It treats each individual's starting point (intercept) and rate of change (slope) as latent variables, simultaneously estimating the average trajectory across the sample and the extent to which individuals differ in their own trajectories.	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.