In this paper, multidimensional item response theory models for dichotomous data, developed in the fields of psychometrics and ability assessment, are discussed in connection with the problem of evaluating customer satisfaction. These models allow us to take into account latent constructs at various degrees of complexity and provide interesting new perspectives for services quality assessment. Markov chain Monte Carlo techniques are considered for estimation. An application to a real data set is also presented
Multidimensional item response theory models for dichotomous data in customer satisfaction evaluation / F. Andreis, P.A. Ferrari. - In: JOURNAL OF APPLIED STATISTICS. - ISSN 0266-4763. - 41:9(2014 Apr 10), pp. 1-12. [10.1080/02664763.2014.907395]
Multidimensional item response theory models for dichotomous data in customer satisfaction evaluation
F. AndreisPrimo
;P.A. FerrariSecondo
2014
Abstract
In this paper, multidimensional item response theory models for dichotomous data, developed in the fields of psychometrics and ability assessment, are discussed in connection with the problem of evaluating customer satisfaction. These models allow us to take into account latent constructs at various degrees of complexity and provide interesting new perspectives for services quality assessment. Markov chain Monte Carlo techniques are considered for estimation. An application to a real data set is also presentedFile | Dimensione | Formato | |
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