เปรียบเทียบวิธี

	แบบจำลองเส้นโค้งการเติบโตแบบแฝง (Latent Growth Curve Model - LGC)	Mixed Effects Model
สาขาวิชา	สถิติศาสตร์	สถิติศาสตร์
ตระกูล	Latent structure	Regression model
ปีกำเนิด	1990	1982
ผู้ริเริ่ม	Meredith & Tisak	Laird & Ware
ประเภท	Latent variable / longitudinal growth model	Mixed effects regression
แหล่งต้นตำรับ	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.
ชื่อเรียกอื่น	latent growth model, LGC, growth curve model, Gizil Büyüme Eğrisi Modeli	LME, LMM, mixed model, random effects model
ที่เกี่ยวข้อง	5	4
สรุป	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.