PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
2020 | 67 | z. 1 | 51--76
Tytuł artykułu

A Proposal for Perception Measurement on a Linguistic Scale Coded with Unconventional Fuzzy Numbers

Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The aim of this paper is to formulate a new proposal for perception measurement on a linguistic scale coded with fuzzy numbers. Additionally, an attempt is made to show the assessment process of the adequacy of a linguistic scale. The basis for the proposal is the discussion of issues related to the ambiguity of the results of measurements made by means of a subjective type of measurement scales. The proposed assessment technique is relevant when the results of the measurement based on a linguistic scale are coded with numerical equivalents in the form of e.g. unconventional fuzzy numbers. The issue the subjective perception of the products' quality illustrates the objectivity level of measurement results. Subjective perception is measured with a specially designed IT tool allowing the respondent to determine all the characteristics of the resulting fuzzy numbers. The scale adequacy assessment tool is based on the Item Response Theory, and particulary so on the model devised by Georg Rasch. The measurement of socio-economic phenomena, including material and subjective wellbeing of households, the quality of households' durable goods, and the assessment of the quality of goods available on the market requires special tools. It seems that one of the most useful and powerful tools for the measurement of socio-economic phenomena is a linguistic scale. The problematic issue in the analysis presented in the paper is coding verbal terms with their numerical equivalents. (original abstract)
Rocznik
Tom
67
Numer
Strony
51--76
Opis fizyczny
Twórcy
  • Wrocław University of Economic sand Business
Bibliografia
  • Abdi H., (2010), Guttman Scaling, in: N. Salkind, (ed.), Encyclopedia of Research Design, Sage, Thousand Oaks.
  • Ackerman T., (2005), Multidimensional Item Response Theory Models, in: B. Everitt, D. Howell, (ed.), Encyclopedia of Statistics in Behavioural Science, vol. 3, Wiley, Chichester.
  • Arguelles Mendez L., (2016), From Fuzzy Sets to Linguistic Variables, in: L. Arguelles Mendez, (ed.), A Practical Introduction to Fuzzy Logic using LISP, Springer, Berlin, 169-228. DOI: 10.1007/978-3-319-23186-0_6.
  • Ark van der A., (2012), New Developments in Mokken Scale ... in R., Journal of Statistical Software, 48(5). DOI: 10.18637/jss.v048.i05.
  • Brzezińska J., (2016), Modele IRT i modele Rascha w badaniach testowych, in: K. Jajuga, M. Walesiak, (ed.), Taksonomia 27: Klasyfikacja i analiza danych - teoria i zastosowania, 49-57.
  • Combrinck C., (2018), The use of Rasch Measurement Theory to Address Measurement and Analysis Challenges in Social Science Research, PhD thesis, University of Pretoria, https://repository. up.ac.za/bitstream/handle/2263/67982/Combrinck_Use_2018.pdf?sequence=1&isAllowed=y (accessed 20.11.2019).
  • DeMars C., (2018), Classical Test Theory and Item Response Theory, chapter 2, in: P. Irwing, T. Booth, D. Hughes, (ed.), The Wiley Handbook of Psychometric Testing: A Multidisciplinary Reference on Survey, Scale and Test Development, Wiley, New York, 49-73. DOI: 10.1002/ 9781118489772.ch2.
  • DePaoli S., Tiemensma J., Felt, J., (2018), Assessment of health surveys. Fitting a multidimensional graded response model, Psychology, Health & Medicine, 23(1), 1299-1317. DOI: 10.1080/ 13548506.2018.1447136.
  • Diener E., Oishi S., Tay L., (2018), Handbook of Well-Being, DEF Publishers, Salt Lake City.
  • Edelen M., Reeve B., (2007), Applying Item Response Theory (IRT) Modelling to Questionnaire Development, Evaluation and Refinement, Quality of Life Research, 16(5), 5-18. DOI: 10.1007/s11136-007-9198-0.
  • European Commission, (2017), Qualitative Analysis. Verticals and Environments, chapter 5, in: Identification and Quantification of Key Socioeconomic Data to Support Strategic Planning for the Introduction of 5G in Europe, Publications Office of the European Union, Luxembourg, 6-7.
  • Fattore M., Maggino F., Greselin F., (2011), Socioeconomic Evaluation with Ordinal Variables. Integrating Counting and POSET Approaches, Statistica and Applicazioni, Special issue, 31-42.
  • FisPro: An Open Source Portable Software for Fuzzy Inference Systems, (2018), https://www. fispro.org/en/documentation (accessed 20.11.2019).
  • Guttman L., (1944), A Basis for Scaling Qualitative Data, American Sociological Review, 9(2), 139- 150. DOI: 10.2307/2086306.
  • Guttman L., Stouffer S., Suchman E., Lazarsfeld P., Star S., Clausen J., (1950), Measurement and Prediction, Princeton University Press, Princeton.
  • Hambleton R., Swaminathan H., (1991a), Assumptions of Item Response Theory, in: R. Hambleton, H. Swaminathan, Item Response Theory. Principles and Applications, Springer, Berlin.
  • Hambleton R., Swaminathan H., (1991b), Item Response Theory. Principles and Applications, Springer, Berlin.
  • Hambleton R., Swaminathan H., (1991c), Shortcomings of Standard Testing Methods, in: R. Hambleton, H. Swaminathan, Item Response Theory. Principles and Applications, Springer, Berlin, DOI: 10.1007/978-94-017-1988-9.
  • Hartig J., Hoehler J., (2009), Multidimensional IRT Models for the Assessment of Competencies, Studies in Educational Evaluation, 35(2-3), 57-63. DOI: 10.1016/j.stueduc.2009.10.002.
  • Hofmann R., (1979), On Testing a Guttman Scale for Significance, Educational and Psychological Measurement, 39(2), 297-301. DOI: 10.1177/001316447903900206.
  • Immekus J., Snyder K., Ralston P., (2019), Multidimensional Item Response Theory for Factor Structure Assessment in Educational Psychology Research, Frontiers in Education, 4, 1-15. DOI: 10.3389/feduc.2019.00045.
  • Jabrayilov R., Emons W., Sijtsma K., (2016), Comparison of Classical Test Theory and Item Response Theory in Individual Change Assessment, Applied Psychological Measurement, 40(8), 559-572. DOI: 10.1177/0146621616664046.
  • Jefmański B., (2014), Application of Rating Scale Model in Conversion of Rating Scales\\' Points to the Form of Triangular Fuzzy Numbers, Folia Oeconomica Stetinensa, 14(2), 7-18. DOI: 10.1515/foli-2015-0010.
  • Jumailiyah M., (2017), Item Response Theory: A Basic Concept, Educational Research and Reviews, 12(5), 258-266. DOI: 10.5897/ERR2017.3147.
  • Kacprzyk J., Roubens M., (ed.), (1988), Non-Conventional Preference Relations in Decision Making, Springer, Berlin.
  • Kappenburg -ten Holt J., (2014), A Comparison Between Factor Analysis and Item Response Theory Modelling in Scale Analysis, PhD thesis, University of Groningen, https://www.rug.nl/research /portal/files/13080475/20140623_Gmw_TenHolt.pdf (accessed 20.11.2019).
  • Kong, N., (2018), Numerical Comparisons across General Total Score, Total Score, and Item Response Theory, https://www.researchgate.net/publication/323931094_Numerical_Comparisons_across_Ge neral_Total_Score_Total_Score_and_Item_Response_Theory. DOI: 10.13140/RG.2.2.21519.89768.
  • Linacre J., (2000), Comparing and Choosing between Partial Credit Models (PCM) and Rating Scale Models (RSM), Rasch Measurement Transactions, 14(3), 768.
  • Linacre J., (2002), Optimizing Rating Scale Category Effectiveness, Journal of Applied Measurement, 3(1), 85-106.
  • Lynn P., (2019), Applying Prospect Theory to Participation in a CAPI/WEB Panel Survey, Public Opinion Quarterly, 83(3), 559-567. DOI: 10.1093/poq/nfz030.
  • Magno C., (2009), Demonstrating the Difference between Classical Test Theory and Item Response Theory Using Derived Test Data, The International Journal of Educational and Psychological Assessment, 1(1), 1-11.
  • Maydeu-Olivares A., Cai L., Hernandez A., (2011), Comparing the Fit of Item Response Theory and Factor Analysis Models, Structural Equation Modelling, 18(3), 333-356. DOI: 10.1080/ 10705511.2011.581993.
  • Michalos A., (ed.) (2014), Encyclopedia of Quality of Life and Wellbeing Research, Dordrecht, Berlin.
  • Mokken R., (1971), A Theory and Procedure of Scale Analysis with Applications in Political Research, de Gruyter, Berlin.
  • NAP, (2017), Improving Motor Carrier Safety Measurement, The National Academies Press, Washington.
  • ONS, (2019a), Measuring National Wellbeing in the UK: International Comparisons, Office for National Statistics, https://www.ons.gov.uk/peoplepopulationandcommunity/wellbeing/articles/ measuringnationalwellbeing/internationalcomparisons2019
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171610179

Zgłoszenie zostało wysłane

Zgłoszenie zostało wysłane

Musisz być zalogowany aby pisać komentarze.
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.