Multinomial logistic estimation in dual frame surveys
Molina, David (Universidad de Granada. Departamento de Estadística)
Rueda, Maria del Mar (Universidad de Granada. Departamento de Estadística)
Arcos, Antonio (Universidad de Granada. Departamento de Estadística)
Ranalli, Maria Giovanna (Università di Perugia. Department of Political Sciences)

Date: 2015
Abstract: We consider estimation techniques from dual frame surveys in the case of estimation of proportions when the variable of interest has multinomial outcomes. We propose to describe the joint distribution of the class indicators by a multinomial logistic model. Logistic generalized regression estimators and model calibration estimators are introduced for class frequencies in a population. Theoretical asymptotic properties of the proposed estimators are shown and discussed. Monte Carlo experiments are also carried out to compare the efficiency of the proposed procedures for finite size samples and in the presence of different sets of auxiliary variables. The simulation studies indicate that the multinomial logistic formulation yields better results than the classical estimators that implicitly assume individual linear models for the variables. The proposed methods are also applied in an attitude survey.
Rights: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades. Creative Commons
Language: Anglès.
Document: article ; recerca ; publishedVersion
Subject: Finite population ; Survey sampling ; Auxiliary information ; Model assisted inference ; Calibration
Published in: SORT : statistics and operations research transactions, Vol. 39 Núm. 2 (July-December 2015) , p. 309-336 (Articles) , ISSN 1696-2281

Adreça alternativa: https://www.raco.cat/index.php/SORT/article/view/302265


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 Record created 2015-12-23, last modified 2019-04-17



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