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Camargo, FR; Henson, B (2015)
Publisher: Institute of Physics Publishing
Languages: English
Types: Other
Subjects:
The notion of that more or less of a physical feature affects in different degrees the users' impression with regard to an underlying attribute of a product has frequently been applied in affective engineering. However, those attributes exist only as a premise that cannot directly be measured and, therefore, inferences based on their assessment are error-prone. To establish and improve measurement of latent attributes it is presented in this paper the concept of a stochastic framework using the Rasch model for a wide range of independent variables referred to as an item bank. Based on an item bank, computerized adaptive testing (CAT) can be developed. A CAT system can converge into a sequence of items bracketing to convey information at a user's particular endorsement level. It is through item banking and CAT that the financial benefits of using the Rasch model in affective engineering can be realised.
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    • [1] Barnes C and Lillford S 2009 J. of Eng. Design 20 477 - 492.
    • [2] Camargo F R and Henson B 2012 Int. J. of Hum. Factors and Ergon. 1 204 - 219.
    • [3] Choppin B H 1978 Item banking and the monitoring of achievement (Slough: National Foundation for Educational Research).
    • [4] Eckes T 2011 Psychol. Test and Assessm. Model. 53 414 - 439.
    • [5] Rasch G 1960, 1980 Probabilistic models for some intelligence and attainment tests (Copenhagen: Danish Institute for Educational Research), expanded edition (1980) (Chicago: The University of Chicago Press).
    • [6] Krantz D H, Luce R D, Suppes P and Tversky A 1971 Foundations of measurement 1 (New York: Academic Press).
    • [7] Andrich D 1988 Rasch models for measurement 68 (London: Sage Publications)
    • [8] Wright B and Panchapakesan N 1969 Educ. and Psychol. Meas. 29 23 - 48.
    • [9] Camargo F R and Henson B 2013 J. Phys.: Conf. Ser. 4 59.
    • [10] Linacre J M 1989 Many-facet Rasch measurement (Chicago: MESA Press)
    • [11] Fisher R A 1922 Philos. T. R. Soc. A 222 309 - 368.
    • [12] Linacre J M 1999 J. Outcome Meas. 3 382 - 485.
    • [13] Tennant A and Conaghan P G 2007 Arthritis Rheum. 57 1358 - 62.
    • [14] Wright B D 1993 Rasch Measurement Transactions 7 288.
    • [15] Hahn E A, Cella D, Bode R K, Gershon R and Lay J 2006 Med. Care 44 S189 - S197.
    • [16] Embretson S E and Reise S P 2000 Item response theory for psychologists (Mahwah: Lawrence Erlbaum).
    • [17] Timminga E and Adema J J 1995 Rasch models: foundations, recent developments and applications ed G H Fisher and I W Molenaar (New York: Spring-Verlag) 111 - 127
    • [18] VIM - International Vocabulary of Metrology 2012 Basic and general concepts and associated terms, 3rd ed (The Joint Committee for Guides in Metrology - JCGM)
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