Evaluating psychometric properties of the Muslim Daily Religiosity Assessment Scale (MUDRAS) in Indonesian samples using the Rasch model
This study aimed to validate the Indonesian version of the Muslim Daily Religiosity Assessment Scale (MUDRAS). This measure was tested on 766 Muslim college students aged 17-24 years (mean age = 20.01, SD = 1.4) who were students from six state Islamic universities and one private Islamic university...
| Authors: | ; ; |
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| Format: | Electronic Article |
| Language: | English |
| Check availability: | HBZ Gateway |
| Journals Online & Print: | Drawer...
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| Fernleihe: | Fernleihe für die Fachinformationsdienste |
| Published: |
Taylor & Francis
2020
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| In: |
Mental health, religion & culture
Year: 2020, Volume: 23, Issue: 3/4, Pages: 331-346 |
| Further subjects: | B
Muslim religiosity
B Factor analysis B partial credit model B MUDRAS B Rasch model B Adaptation |
| Online Access: |
Volltext (lizenzpflichtig) |
| Summary: | This study aimed to validate the Indonesian version of the Muslim Daily Religiosity Assessment Scale (MUDRAS). This measure was tested on 766 Muslim college students aged 17-24 years (mean age = 20.01, SD = 1.4) who were students from six state Islamic universities and one private Islamic university in Indonesia. The data analysis technique used was the Partial Credit Model, which derived the polytomous Rasch model family. The results indicated that the MUDRAS has good psychometric characteristics for measuring religiosity in a sample of Indonesian Muslim students. All assumptions of the Rasch model were fulfilled. The person separation reliability was .92 and Cronbach’s alpha was .93, indicating excellent internal consistency of the Indonesian MUDRAS. Confirmatory factor analysis revealed the higher order factor structure of the Indonesian MUDRAS. These findings provide the first Rasch model contribution to the MUDRAS and its first validation in a Muslim majority country. |
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| ISSN: | 1469-9737 |
| Contains: | Enthalten in: Mental health, religion & culture
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| Persistent identifiers: | DOI: 10.1080/13674676.2020.1795822 |