ScholarGate
Assistent

Sammenlign metoder

Gjennomgå de valgte metodene side om side; rader som avviker, er uthevet.

Latent Growth Curve Model (LGC)×Mixed Effects Model×
FagfeltStatistikkStatistikk
FamilieLatent structureRegression model
Opprinnelsesår19901982
OpphavspersonMeredith & TisakLaird & Ware
TypeLatent variable / longitudinal growth modelMixed effects regression
Opprinnelig kildeMeredith, W. & Tisak, J. (1990). Latent Curve Analysis. Psychometrika, 55(1), 107–122. DOI ↗Laird, N. M., & Ware, J. H. (1982). Random-effects models for longitudinal data. Biometrics, 38(4), 963–974. DOI ↗
Aliaslatent growth model, LGC, growth curve model, Gizil Büyüme Eğrisi ModeliLME, LMM, mixed model, random effects model
Relaterte54
SammendragThe 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.
ScholarGateDatasett
  1. v1
  2. 1 Kilder
  3. PUBLISHED
  1. v1
  2. 2 Kilder
  3. PUBLISHED

Gå til søk Last ned lysbilder

ScholarGateSammenlign metoder: LGC Model · Mixed Effects Model. Hentet 2026-06-19 fra https://scholargate.app/no/compare