The model is proposed and validated through a survey-based research, applying structural equation modeling.
A three stage analysis applying Structural Equation Modelling (SEM); multiple regression; and multinomial logistic regression is used.
We applied structural equation modeling to study relations of latent variables (family SEP, family structure, school career, HCB, HEB) in adolescence, to the educational level in adulthood.
Table 12 presents the fit-values of the applied structural equation models.
We located prominent reading areas using fMRI and applied structural equation modeling to pinpoint distinct neural pathways.
To examine the role of co-varying factors, we constructed and applied structural equation models (SEMs) for each ecosystem process.
Therefore, we applied structural equation modeling (SEM) as a more flexible alternative statistical technique to achieve the stated aims of the current study.
To explore the extent of this bias, we applied structural equation modeling to data from a prospective study of developmental methylmercury neurotoxicity in the Faroe Islands.
We applied structural equation modeling (SEM) to examine in more detail the functional relationship between conjunction-preferred (rDLPFC, rVLPFC, left parietal) and conjunction-least-preferred (temporo-occipital) regions.
Additionally, we applied structural equation models to examine genetic and environmental influences on adiposity, adiposity change over time (ACO), ISI 0,120), and the interrelationships among them.
