We investigated whether dichotomous data showed the same latent structure as interval-level from which they originated. Given constancy of dimensionality and factor loadings reflecting data, focus was on variance variable a confirmatory model. This shown to summarize information provided by loadings. The results simulation study did not reveal exact correspondence variances variables derived bu...

This paper introduces a novel approach for modeling set of directed, binary networks in the context cognitive social structures (CSSs) data. We adopt relativist which no assumption is made about existence an underlying true network. More specifically, we rely on generalized linear model that incorporates bilinear structure to transitivity effects within networks, and hierarchical specification ...

Clustering of variables is the task grouping similar into different groups. It may be useful in several situations such as dimensionality reduction, feature selection, and detect redundancies. In present study, we combine two methods features clustering around latent (CLV) algorithm k-means based co-clustering (kCC). Indeed, classical CLV cannot applied to high dimensional data because this app...