IDEAS home Printed from https://ideas.repec.org/a/spr/soinre/v177y2025i1d10.1007_s11205-025-03567-0.html
   My bibliography  Save this article

Comparative Study through Item Analysis of CCRAM28 and CCRAM10

Author

Listed:
  • Kyeongwon Lee

    (Halla University)

  • Hyun Lee

    (Mokwon University)

Abstract

In recent times, the global community has increasingly experienced disasters both directly and indirectly, raising interest in community resiliency to address such challenges. The Conjoint Community Resiliency Assessment Measure (CCRAM) was developed as an integrated and multidimensional scale for assessing community resiliency. This study aims to analyze this scale at the item level for its application in Korean society. The study analyzed responses from a total of 1,200 adults, 400 from each of the three survey phases conducted nationwide. As a result of the factor analysis, items 18 and 26, which showed low factor loadings, were removed, and it was found that the construct consisted of 3 factors. Furthermore, items 14 and 23 were excluded due to poor fit identified through item analysis employing the Rasch model from Item Response Theory. The number of response categories was found to be appropriately set as a 5-point Likert scale, like the original scale. This research facilitates the application of CCRAM in Korea, contributing to the enhancement and restoration of community resiliency.

Suggested Citation

  • Kyeongwon Lee & Hyun Lee, 2025. "Comparative Study through Item Analysis of CCRAM28 and CCRAM10," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 177(1), pages 411-424, March.
    • Handle: RePEc:spr:soinre:v:177:y:2025:i:1:d:10.1007_s11205-025-03567-0
    DOI: 10.1007/s11205-025-03567-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11205-025-03567-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11205-025-03567-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Susan Cutter, 2016. "The landscape of disaster resilience indicators in the USA," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 80(2), pages 741-758, January.
    2. Kirsten Maclean & Helen Ross & Michael Cuthill & Bradd Witt, 2017. "Converging disciplinary understandings of social aspects of resilience," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 60(3), pages 519-537, March.
    3. David Andrich, 1978. "A rating formulation for ordered response categories," Psychometrika, Springer;The Psychometric Society, vol. 43(4), pages 561-573, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Eun-Young Park & Soojung Chae, 2020. "Rasch Analysis of the Korean Parenting Stress Index Short Form (K-PSI-SF) in Mothers of Children with Cerebral Palsy," IJERPH, MDPI, vol. 17(19), pages 1-11, September.
    2. P. A. Ferrari & S. Salini, 2008. "Measuring Service Quality: The Opinion of Europeans about Utilities," Working Papers 2008.36, Fondazione Eni Enrico Mattei.
    3. Chang, Hsin-Li & Yang, Cheng-Hua, 2008. "Explore airlines’ brand niches through measuring passengers’ repurchase motivation—an application of Rasch measurement," Journal of Air Transport Management, Elsevier, vol. 14(3), pages 105-112.
    4. Sullivan, Daniel & Schmitt, Harrison J. & Calloway, Eric E. & Clausen, Whitney & Tucker, Pamela & Rayman, Jamie & Gerhardstein, Ben, 2021. "Chronic environmental contamination: A narrative review of psychosocial health consequences, risk factors, and pathways to community resilience," Social Science & Medicine, Elsevier, vol. 276(C).
    5. Luiz Diego Vidal Santos & Francisco Sandro Rodrigues Holanda & Catuxe Varjão Santana Oliveira & Alceu Pedrotti & Pedro Vinícius Bertulino Menezes & Ana Paula Schervinski Villwock, 2023. "Purchase intention of Amazon sustainable brands: a hybrid approach of structural equation modeling and Rasch model," SN Business & Economics, Springer, vol. 3(12), pages 1-29, December.
    6. Ivana Bassi & Matteo Carzedda & Enrico Gori & Luca Iseppi, 2022. "Rasch analysis of consumer attitudes towards the mountain product label," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 10(1), pages 1-25, December.
    7. Fang Zhang & Dengyu Wang & Xi Zhou & Fan Ye, 2024. "Community Resilience Evaluation and Construction Strategies in the Perspective of Public Health Emergencies: A Case Study of Six Communities in Nanjing," Sustainability, MDPI, vol. 16(16), pages 1-24, August.
    8. Antonio Caronni & Marina Ramella & Pietro Arcuri & Claudia Salatino & Lucia Pigini & Maurizio Saruggia & Chiara Folini & Stefano Scarano & Rosa Maria Converti, 2023. "The Rasch Analysis Shows Poor Construct Validity and Low Reliability of the Quebec User Evaluation of Satisfaction with Assistive Technology 2.0 (QUEST 2.0) Questionnaire," IJERPH, MDPI, vol. 20(2), pages 1-19, January.
    9. Zobel, Christopher W. & Baghersad, Milad, 2020. "Analytically comparing disaster resilience across multiple dimensions," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    10. Wanke, Peter Fernandes & Chiappetta Jabbour, Charbel José & Moreira Antunes, Jorge Junio & Lopes de Sousa Jabbour, Ana Beatriz & Roubaud, David & Sobreiro, Vinicius Amorim & Santibanez Gonzalez‬, Erne, 2021. "An original information entropy-based quantitative evaluation model for low-carbon operations in an emerging market," International Journal of Production Economics, Elsevier, vol. 234(C).
    11. Hua-Hua Chang, 1996. "The asymptotic posterior normality of the latent trait for polytomous IRT models," Psychometrika, Springer;The Psychometric Society, vol. 61(3), pages 445-463, September.
    12. Curt Hagquist & Raili Välimaa & Nina Simonsen & Sakari Suominen, 2017. "Differential Item Functioning in Trend Analyses of Adolescent Mental Health – Illustrative Examples Using HBSC-Data from Finland," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 10(3), pages 673-691, September.
    13. Wang, Luming & Finn, Adam, 2014. "A psychometric theory that measures up to marketing reality: An adapted Many Faceted IRT model," Australasian marketing journal, Elsevier, vol. 22(2), pages 93-102.
    14. Yongling Zhang & Zijie Cai & Xiaobing Zhou, 2024. "Spatial-Temporal Evolution and Obstacle Factors of the Disaster Resilience in the Central Plains Urban Agglomeration, China," Sustainability, MDPI, vol. 17(1), pages 1-25, December.
    15. Qiu-Yue Zhong & Bizu Gelaye & Alan M Zaslavsky & Jesse R Fann & Marta B Rondon & Sixto E Sánchez & Michelle A Williams, 2015. "Diagnostic Validity of the Generalized Anxiety Disorder - 7 (GAD-7) among Pregnant Women," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-17, April.
    16. Cristante, Francesca & Robusto, Egidio, 1999. "Assessing dependence among subjects' responses," Mathematical Social Sciences, Elsevier, vol. 38(3), pages 259-274, November.
    17. Meiyan Gao & Zongmin Wang & Haibo Yang, 2022. "Review of Urban Flood Resilience: Insights from Scientometric and Systematic Analysis," IJERPH, MDPI, vol. 19(14), pages 1-19, July.
    18. Amy Snyder & Kenneth Royal, 2016. "Investigating the Financial Awareness and Behaviors of Veterinary Medical Students," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 8(7), pages 201-201, July.
    19. Nicole Gideon & Nick Hawkes & Jonathan Mond & Rob Saunders & Kate Tchanturia & Lucy Serpell, 2016. "Development and Psychometric Validation of the EDE-QS, a 12 Item Short Form of the Eating Disorder Examination Questionnaire (EDE-Q)," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-19, May.
    20. Huang, Jen-Hung & Peng, Kua-Hsin, 2012. "Fuzzy Rasch model in TOPSIS: A new approach for generating fuzzy numbers to assess the competitiveness of the tourism industries in Asian countries," Tourism Management, Elsevier, vol. 33(2), pages 456-465.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:soinre:v:177:y:2025:i:1:d:10.1007_s11205-025-03567-0. See general information about how to correct material in RePEc.

    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 CitEc recognized a bibliographic reference but did not link an item in RePEc 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 RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.