Nonlinear CUB models have been recently introduced in the literature to model ordinal data taking into account the unequal spacing among response categories. Nonlinear CUB models can be effectively used in a variety of fields, typically when human perceptions and attitudes are measured by questionnaires with questions having ordered response categories. This paper introduces the code developed in the free software environment R for Nonlinear CUB estimation, graphical representation of a variety of outputs, fit evaluation, along with data simulation according to the Nonlinear CUB data generating process.

Nonlinear CUB models: the R code

MANISERA, Marica;ZUCCOLOTTO, Paola
2014-01-01

Abstract

Nonlinear CUB models have been recently introduced in the literature to model ordinal data taking into account the unequal spacing among response categories. Nonlinear CUB models can be effectively used in a variety of fields, typically when human perceptions and attitudes are measured by questionnaires with questions having ordered response categories. This paper introduces the code developed in the free software environment R for Nonlinear CUB estimation, graphical representation of a variety of outputs, fit evaluation, along with data simulation according to the Nonlinear CUB data generating process.
2014
UE
PE1_14 Statistics
PE1_13 Probability
SH1_4 Econometrics, statistical methods
Esperti anonimi
Inglese
Internazionale
STAMPA
12
2
205
223
19
rating data, Likert scales, CUB models, EM algorithm, gradient approximation procedures, transition probabilities, transition plot
Altra università italiana
2
info:eu-repo/semantics/article
262
Manisera, Marica; Zuccolotto, Paola
1 Contributo su Rivista::1.1 Articolo in rivista
none
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/462303
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