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مدل آمیخته رشد (GMM)×مدل‌سازی معادلات ساختاری (SEM)×
حوزهآمارآمار
خانوادهLatent structureLatent structure
سال پیدایش19991970
پدیدآورBengt O. Muthén & Kerby SheddenKarl Jöreskog (LISREL framework, 1970s)
نوعLatent class / longitudinal growth modelLatent variable / causal modeling
منبع بنیادینMuthén, B. O. & Shedden, K. (1999). Finite Mixture Modeling with Mixture Outcomes Using the EM Algorithm. Biometrics, 55(2), 463–469. DOI ↗Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage Learning. ISBN: 978-1473756540
نام‌های دیگرBüyüme Karışım Modeli (Growth Mixture Model — GMM), GMM, latent class growth analysis extension, mixture latent growth curve modelYapısal Eşitlik Modellemesi (SEM), structural equation modelling, covariance structure analysis, latent variable modeling
مرتبط55
خلاصهThe Growth Mixture Model, introduced by Muthén and Shedden in 1999, is a longitudinal latent variable method that identifies distinct subpopulations — latent trajectory classes — each following its own growth curve over time. It extends the standard Latent Growth Curve (LGC) model by allowing the sample to be composed of an unknown mixture of classes with different intercepts, slopes, and variance structures.Structural equation modeling is a multivariate statistical framework that simultaneously estimates a measurement model — relating observed indicators to latent constructs — and a structural model specifying directional or reciprocal relationships among those constructs. Rooted in the LISREL tradition developed by Karl Jöreskog in the 1970s, SEM is the standard tool for testing complex theoretical models in the social, behavioural, and management sciences.
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ScholarGateمقایسهٔ روش‌ها: GMM · SEM. بازیابی‌شده در 2026-06-17 از https://scholargate.app/fa/compare