Commentary: Structural equation modelling in epidemiology: some problems and prospects

Problems and Prospects of Introducing Islamic Microfinance in Azerbaijan Republic

Component-based Structural Equation Modelling

Two complementary schools have come to the fore in the field of Structural Equation Modelling (SEM): covariance-based SEM and component-based SEM. The first approach has been developed around Karl Jöreskog and the second one around Herman Wold under the name "PLS" (Partial Least Squares). Hwang and Takane have proposed a new component-based SEM method named Generalized Structured Component Anal...

Invited commentary: structural equation models and epidemiologic analysis.

In this commentary, structural equation models (SEMs) are discussed as a tool for epidemiologic analysis. Such models are related to and compared with other analytic approaches often used in epidemiology, including regression analysis, causal diagrams, causal mediation analysis, and marginal structural models. Several of these other approaches in fact developed out of the SEM literature. Howeve...

global results on some nonlinear partial differential equations for direct and inverse problems

در این رساله به بررسی رفتار جواب های رده ای از معادلات دیفرانسیل با مشتقات جزیی در دامنه های کراندار می پردازیم . این معادلات به فرم نیم-خطی و غیر خطی برای مسایل مستقیم و معکوس مورد مطالعه قرار می گیرند . به ویژه، تاثیر شرایط مختلف فیزیکی را در مساله، نظیر وجود موانع و منابع، پراکندگی و چسبندگی در معادلات موج و گرما بررسی می کنیم و به دنبال شرایطی می گردیم که متضمن وجود سراسری یا عدم وجود سراسر...

Structural Equation Modelling for small samples

Covariance-based SEM is usually used with an objective of model validation and needs a large sample (what is large varies from an author to another: more than 100 subjects and preferably more than 200 subjects are often mentioned). Component-based SEM is mainly used for score computation and can be carried out on very small samples. A research based on 6 subjects has been published by Tenenhaus...