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

    for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    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. 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.
    2. 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).
    3. 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.
    4. 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.
    5. 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.
    6. 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).
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. Wendy L. Martin & Alexander McKelvie & G. T. Lumpkin, 2016. "Centralization and delegation practices in family versus non-family SMEs: a Rasch analysis," Small Business Economics, Springer, vol. 47(3), pages 755-769, October.
    14. Chang, Hsin-Li & Wu, Shun-Cheng, 2008. "Exploring the vehicle dependence behind mode choice: Evidence of motorcycle dependence in Taipei," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(2), pages 307-320, February.
    15. Silvia Golia, 2015. "Assessing the impact of uniform and nonuniform differential item functioning items on Rasch measure: the polytomous case," Computational Statistics, Springer, vol. 30(2), pages 441-461, June.
    16. Vidya Diwakar & Amanda Lenhardt & Emmanuel Tumusiime & Joseph Simbaya & Arthur Moonga, 2023. "The Relationship Between Psychosocial Interventions and Child Wellbeing in Zambia," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 16(1), pages 395-420, February.
    17. Jesse M. Keenan, 2018. "Regional resilience trust funds: an exploratory analysis for leveraging insurance surcharges," Environment Systems and Decisions, Springer, vol. 38(1), pages 118-139, March.
    18. Maria Cerreta & Simona Panaro & Giuliano Poli, 2021. "A Spatial Decision Support System for Multifunctional Landscape Assessment: A Transformative Resilience Perspective for Vulnerable Inland Areas," Sustainability, MDPI, vol. 13(5), pages 1-22, March.
    19. Daniel Feldmeyer & Daniela Wilden & Christian Kind & Theresa Kaiser & Rüdiger Goldschmidt & Christian Diller & Jörn Birkmann, 2019. "Indicators for Monitoring Urban Climate Change Resilience and Adaptation," Sustainability, MDPI, vol. 11(10), pages 1-17, May.
    20. Jesper Tijmstra & Maria Bolsinova, 2019. "Bayes Factors for Evaluating Latent Monotonicity in Polytomous Item Response Theory Models," Psychometrika, Springer;The Psychometric Society, vol. 84(3), pages 846-869, September.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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.