Full weighted least squares (full WLS) and robust weighted least squares (robustWLS) are currently the two primary estimation methods designed for structural equationmodeling with ordinal observed variables. These methods assume that continuous latentvariables were coarsely categorized by the...

System of panel models are popular models in applied sciences and the question of spatial errors has created the recent demand for spatial system estimation of panel models. Therefore we propose new diagnostic methods to explore if the spatial component will change significantly the outcome of...

This study aims to measure student’s attitude towards statistics through a model that considers the variables proposed by Auzmendi (1992). Was examined whether the constructs: usefulness, motivation, likeness, confidence and anxiety influence the student's attitude towards statistics. Were...

This paper aims at identifying a most frequently multivariate technique,Principal Components Analysis (PCA), to solve a multicollinear single equation econometric model .results of the method used were compared to Ordinary Least Squares (OLS) and(Two Stages Least Squares (2SLS) to see if...

System of panel models are popular models in applied sciences and the question of spatial errors has created the recent demand for spatial system estimation of panel models. Therefore we propose new diagnostic methods to explore if the spatial component will change significantly the outcome of...

System of panel models are popular models in applied sciences and the question of spatial errors has created the recent demand for spatial system estimation of panel models. Therefore we propose new diagnostic methods to explore if the spatial component will change significantly the outcome of...

System of panel models are popular models in applied sciences and the question of spatial errors has created the recent demand for spatial system estimation of panel models. Therefore we propose new diagnostic methods to explore if the spatial component will change significantly the outcome of...

Estimators of spatial autoregressive (SAR) models depend in a highly non-linear way on the spatial correlation parameter and least squares (LS) estimators cannot be computed in closed form. We first compare two simple LS estimators by distance and covariance properties and then we study the...