Treatment of ‘don’t know’ responses in a mixture model for rating data
Abstract In recent years the use of questionnaires to investigate and measure human perceptions has hugely intensified and, correspondingly, there has been an increased need for statistical models able to treat ordered categorical data, that usually derive from questions asking for ratings. In this paper we focus on a specific class of models, called Combination of Uniform and shifted Binomial (CUB), based on the assumption that rating data derive from an unconscious decision process composed of two independent components, called feeling and uncertainty. More precisely, we deal with a recently proposed extension in this context, the Nonlinear CUB model, which beyond being able to measure feeling and uncertainty, gives an idea of the state of mind of respondents toward the scale used to express the ratings. The aim of the paper is to show how the parameters of the Nonlinear CUB model can be adjusted in order to take account of the presence of ‘don’t know’ responses, following a recent idea developed in the CUB context. In addition, a graphical representation is proposed, able to summarize all the results in a unique graph. A case study is presented, concerned with data from the Eurobarometer survey.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 74 (2016)
Issue (Month): 1 (April)
|Contact details of provider:|| Web page: http://www.springer.com|
Web page: http://www.uniroma1.it/
|Order Information:||Web: http://www.springer.com/economics/journal/40300|
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Maria Iannario, 2010. "On the identifiability of a mixture model for ordinal data," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 87-94.
- Romina Gambacorta & Maria Iannario, 2013. "Measuring Job Satisfaction with CUB Models," LABOUR, CEIS, vol. 27(2), pages 198-224, 06.
- D'Elia, Angela & Piccolo, Domenico, 2005. "A mixture model for preferences data analysis," Computational Statistics & Data Analysis, Elsevier, vol. 49(3), pages 917-934, June.
- Leonardo Grilli & Maria Iannario & Domenico Piccolo & Carla Rampichini, 2014. "Latent class CUB models," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 8(1), pages 105-119, March.
- Maria Iannario & Marica Manisera & Domenico Piccolo & Paola Zuccolotto, 2012. "Sensory analysis in the food industry as a tool for marketing decisions," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 6(4), pages 303-321, December.
- Frederic Lord, 1983. "Maximum likelihood estimation of item response parameters when some responses are omitted," Psychometrika, Springer;The Psychometric Society, vol. 48(3), pages 477-482, September.
When requesting a correction, please mention this item's handle: RePEc:spr:metron:v:74:y:2016:i:1:d:10.1007_s40300-015-0075-2. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla)or (Rebekah McClure)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.