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Rasch model scale calibration analysis for Islamic value


Ishak, Amal Hayati and Osman, Muhamad Rahimi and Abdul Manan, Siti Khadijah and Saidon, Rafeah (2016) Rasch model scale calibration analysis for Islamic value. International Review of Management and Marketing, 6 (S7). pp. 11-16. ISSN 2146-4405

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Abstract

Rasch model is a robust technique for questionnaire validation. It offers a variety of analyses on the instrument’s validity and reliability, as well as analysis on the rating scale design of a measurement scale.Thus, employing Rasch scale calibration analysis, the primary purpose of this article is to empirically analyze the rating scale categories applied in a scale to assess the application of Islamic values in quality management.In the literature, a plethora of Islamic values applied in the context of quality management have been conceptually elaborated in the literature.However, empirical data on that matter is scarce.Yet, an appropriate instrument could not be located.This article briefly explains the scale development process and initially proposes 60 items and eight dimensions. Applying the Rasch model, this article specifically analyses the appropriateness and effectiveness of the rating scale categories based on several indicators pointed by Rasch model.For that purpose, data from 59 responses was analyzed using Winstep.Based on the results, the initial five point Likert-scale is suggested to be modified.

Item Type: Article
Additional Information: Special Issue for "International Soft Science Conference (ISSC 2016), 11-13 April 2016, Universiti Utara Malaysia, Malaysia"
Uncontrolled Keywords: Islamic Values, Rasch Model, Scale Calibration.
Subjects: B Philosophy. Psychology. Religion > BP Islam. Bahaism. Theosophy, etc
H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Divisions: School of Business Management
Depositing User: Mrs. Norazmilah Yaakub
Date Deposited: 06 Dec 2016 08:26
Last Modified: 06 Dec 2016 08:26
URI: http://repo.uum.edu.my/id/eprint/20233

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