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تحلیل عاملی تأییدی×مدل‌سازی خطی سلسله‌مراتبی (HLM / مدل‌سازی چندسطحی)×
حوزهروان‌سنجیآمار
خانوادهLatent structureHypothesis test
سال پیدایش19691986
پدیدآورKarl JöreskogRaudenbush & Bryk (popularized); Goldstein (parallel development)
نوعMeasurement model / latent variable analysisParametric nested-data regression
منبع بنیادینBrown, T. A. (2015). Confirmatory Factor Analysis for Applied Research (2nd ed.). Guilford Press. ISBN: 978-1462515363Raudenbush, S.W. & Bryk, A.S. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods (2nd ed.). Sage. ISBN: 978-0761919049
نام‌های دیگرDoğrulayıcı Faktör Analizi — Ölçek Doğrulama (CFA), confirmatory factor analysis, measurement model testingHLM, MLM, multilevel modeling, multilevel analysis
مرتبط64
خلاصهConfirmatory factor analysis is a measurement modelling technique that tests whether a hypothesised factor structure — typically derived from theory or an earlier exploratory analysis — fits observed data from a new sample. Developed by Karl Jöreskog in 1969, it became the dominant tool for validating psychological scales because it requires the researcher to specify in advance which items belong to which latent factor and then assesses the adequacy of that specification against explicit statistical fit criteria.Hierarchical Linear Modeling (HLM), also known as Multilevel Modeling (MLM), is a parametric statistical method for analyzing nested or clustered data — for example students within classrooms, patients within hospitals, or employees within organizations. Formalized by Raudenbush and Bryk in their 2002 seminal text (building on work from the mid-1980s), HLM simultaneously estimates individual-level and group-level effects while correctly partitioning variance across levels.
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ScholarGateمقایسهٔ روش‌ها: CFA — Scale Validation · Hierarchical Linear Modeling. بازیابی‌شده در 2026-06-17 از https://scholargate.app/fa/compare