caa a22 4500 606242163 CHVBK 20210128101317.0 cr unu---uuuuu 210128e20151201xx s 000 0 eng 10.1007/s11336-015-9450-4 doi (NATIONALLICENCE)springer-10.1007/s11336-015-9450-4 Minimum $$\phi $$ ϕ -Divergence Estimation in Constrained Latent Class Models for Binary Data [Elektronische Daten] [A. Felipe, P. Miranda, L. Pardo] The main purpose of this paper is to introduce and study the behavior of minimum $$\phi $$ ϕ -divergence estimators as an alternative to the maximum-likelihood estimator in latent class models for binary items. As it will become clear below, minimum $$\phi $$ ϕ -divergence estimators are a natural extension of the maximum-likelihood estimator. The asymptotic properties of minimum $$\phi $$ ϕ -divergence estimators for latent class models for binary data are developed. Finally, to compare the efficiency and robustness of these new estimators with that obtained through maximum likelihood when the sample size is not big enough to apply the asymptotic results, we have carried out a simulation study. The Psychometric Society, 2015 latent class models nationallicence minimum phi-divergence estimator nationallicence maximum-likelihood estimator nationallicence asymptotic distribution nationallicence Felipe A. Department of Statistics and Operations Research, Faculty of Mathematics, Complutense University of Madrid, 28040, Madrid, Spain aut Miranda P. Department of Statistics and Operations Research, Faculty of Mathematics, Complutense University of Madrid, 28040, Madrid, Spain aut Pardo L. Department of Statistics and Operations Research, Faculty of Mathematics, Complutense University of Madrid, 28040, Madrid, Spain aut Psychometrika Springer US; http://www.springer-ny.com 80/4(2015-12-01), 1020-1042 0033-3123 80:4<1020 2015 80 11336 https://doi.org/10.1007/s11336-015-9450-4 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11336-015-9450-4 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Felipe A. Department of Statistics and Operations Research, Faculty of Mathematics, Complutense University of Madrid, 28040, Madrid, Spain aut NATIONALLICENCE 700 1- Miranda P. Department of Statistics and Operations Research, Faculty of Mathematics, Complutense University of Madrid, 28040, Madrid, Spain aut NATIONALLICENCE 700 1- Pardo L. Department of Statistics and Operations Research, Faculty of Mathematics, Complutense University of Madrid, 28040, Madrid, Spain aut NATIONALLICENCE 773 0- Psychometrika Springer US; http://www.springer-ny.com 80/4(2015-12-01), 1020-1042 0033-3123 80:4<1020 2015 80 11336