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Regresioni i Penalizuar MCP×Modelimi Eksplorativ i Ekuacioneve Strukturore×
FushaPsikometriPsikometri
FamiljaLatent structureLatent structure
Viti i origjinës20102009
KrijuesiCun-Hui ZhangTihomir Asparouhov, Bengt Muthén
LlojiPenalized regression with minimax concave penaltyHybrid exploratory-confirmatory factor modeling
Burimi themeluesZhang, C. H. (2010). Nearly unbiased variable selection under minimax concave penalty. Annals of Statistics, 38(2), 894-942. DOI ↗Asparouhov, T., & Muthén, B. (2009). Exploratory structural equation modeling. Structural Equation Modeling, 16(3), 397-438. DOI ↗
Emërtime të tjeraMCPESEM
Të lidhura45
PërmbledhjaMCP (Minimax Concave Penalty) is a variable selection method developed by Zhang (2010) that uses a concave penalty function for automated feature selection. Like SCAD, MCP addresses bias in lasso by avoiding shrinkage of large coefficients, but uses a different penalty shape that is computationally simpler than SCAD.Exploratory Structural Equation Modeling (ESEM) is a hybrid approach that combines exploratory factor analysis (EFA) with confirmatory factor analysis (CFA) and path modeling, developed by Asparouhov and Muthén (2009). ESEM relaxes restrictive zero-loading assumptions of traditional CFA, allowing all indicators to load on all factors, which can reveal cross-factor complexity and improve model fit while retaining the ability to test substantive structural theories.
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ScholarGateKrahasoni metodat: MCP Penalized Regression · Exploratory Structural Equation Modeling. Marrë më 2026-06-18 nga https://scholargate.app/sq/compare