The aim of this paper is to propose a general nonparametric model to estimate latent variables with scores non indeterminate; in this paper, following other approaches (PLS, RCD, RCDR), a latent variable (LV) is conceived as a linear combination of predictors (causes) which best predicts a set of dependent variables (indicators), maximising, in this manner, all available information about a LV in the specified model. The model is also extented to categorical variables (nominal, ordinal) by means of optimal scaling methodology and applied to the estimate of a bidimensional LV as a proxy of human capital for US families in 1983
Lovaglio, P. (2002). La stima di Variabili Latenti da variabili osservate miste. STATISTICA, LXII, 203-213.
La stima di Variabili Latenti da variabili osservate miste
LOVAGLIO, PIETRO GIORGIO
2002
Abstract
The aim of this paper is to propose a general nonparametric model to estimate latent variables with scores non indeterminate; in this paper, following other approaches (PLS, RCD, RCDR), a latent variable (LV) is conceived as a linear combination of predictors (causes) which best predicts a set of dependent variables (indicators), maximising, in this manner, all available information about a LV in the specified model. The model is also extented to categorical variables (nominal, ordinal) by means of optimal scaling methodology and applied to the estimate of a bidimensional LV as a proxy of human capital for US families in 1983
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
