قارن الطرق

	تحليل الشرط الضروري	نمذجة المعادلات الهيكلية بالحد الأدنى من المربعات الجزئية
المجال	القياس النفسي	القياس النفسي
العائلة	Latent structure	Latent structure
سنة النشأة	2016	1985
صاحب الطريقة	Jan Dul	Herman Wold
النوع	Set-theoretic configurational analysis	Component-based structural equation model
المصدر التأسيسي	Dul, J. (2016). Necessary Condition Analysis (NCA): Logic and methodology of "necessary but not sufficient" causality. Organizational Research Methods, 19(1), 10-52.	Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd ed.). Sage Publications. ISBN: 9781483377445
الأسماء البديلة	NCA	PLS-SEM, PLS path modeling
ذات صلة	5	5
الملخص	Necessary Condition Analysis (NCA) is a set-theoretic method developed by Dul (2016) that identifies conditions necessary (but not necessarily sufficient) for an outcome to occur. Unlike regression, which estimates average effects, NCA identifies absolute thresholds: conditions that must be present at a certain level for the outcome to be possible, regardless of other factors.	PLS-SEM is a variance-based approach to structural equation modeling developed by Herman Wold (1985) that estimates latent variable models by maximizing the variance explained in dependent variables. Unlike covariance-based SEM, PLS-SEM is particularly useful for exploratory research, small to medium samples, complex models with many constructs, and non-normal data.