IDEAS home Printed from https://ideas.repec.org/a/sae/sagope/v14y2024i3p21582440241271087.html
   My bibliography  Save this article

The Chinese Version of the Couples Satisfaction Index: Psychometric Assessment and Differential Item Functioning Analysis with Item Response Theory

Author

Listed:
  • Shaojie Wang
  • Won-Chan Lee
  • Huixia Ma

Abstract

The Couples Satisfaction Index (CSI) is one of the most widely used instruments to assess intimate relationship satisfaction and status. However, its performance in the Chinese population has yet to be validated, including investigation of potential differential item functioning (DIF). To verify the performance of the adapted Chinese CSI, data were collected from 740 participants (235 males and 505 females). Under the item response theory (IRT) framework, the graded response (GR) model was fit. Key assumptions and model fit were checked first, followed by a DIF analysis. Category response curves and information functions were also examined. Results showed that the two IRT assumptions—unidimensionality and local independence—were generally satisfied. The GR model fit the data well. Moreover, the items from the CSI scale performed very well in assessing and differentiating among participants of differing levels of intimate relationship satisfaction. Meanwhile, high test information distributed across a wide range of latent ability ensured that the CSI was reliable and accurate. Moreover, there was no significant DIF for all CSI items, which supported its equity and fairness when administered to different gender groups. Overall, the CSI shows good psychometric characteristics, has no systematic DIF between genders, and holds promise to facilitate further research on intimate relationship satisfaction.

Suggested Citation

  • Shaojie Wang & Won-Chan Lee & Huixia Ma, 2024. "The Chinese Version of the Couples Satisfaction Index: Psychometric Assessment and Differential Item Functioning Analysis with Item Response Theory," SAGE Open, , vol. 14(3), pages 21582440241, August.
    • Handle: RePEc:sae:sagope:v:14:y:2024:i:3:p:21582440241271087
    DOI: 10.1177/21582440241271087
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/21582440241271087
    Download Restriction: no
    File URL: https://libkey.io/10.1177/21582440241271087?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
    ---><---

    References listed on IDEAS

    as
    1. Choi, Seung W. & Gibbons, Laura E. & Crane, Paul K., 2011. "lordif: An R Package for Detecting Differential Item Functioning Using Iterative Hybrid Ordinal Logistic Regression/Item Response Theory and Monte Carlo Simulations," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 39(i08).
    2. Chalmers, R. Philip, 2012. "mirt: A Multidimensional Item Response Theory Package for the R Environment," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i06).
    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. Yikun Luo & Qipeng Chen & Jianyong Chen & Peida Zhan, 2024. "Development and validation of two shortened anxiety sensitive index-3 scales based on item response theory," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-7, December.
    2. Cervantes, Víctor H., 2017. "DFIT: An R Package for Raju's Differential Functioning of Items and Tests Framework," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 76(i05).
    3. Benjamin D. Schalet & Sangdon Lim & David Cella & Seung W. Choi, 2021. "Linking Scores with Patient-Reported Health Outcome Instruments:A VALIDATION STUDY AND COMPARISON OF THREE LINKING METHODS," Psychometrika, Springer;The Psychometric Society, vol. 86(3), pages 717-746, September.
    4. Rikkert M. van der Lans & Ridwan Maulana & Michelle Helms-Lorenz & Carmen-María Fernández-García & Seyeoung Chun & Thelma de Jager & Yulia Irnidayanti & Mercedes Inda-Caro & Okhwa Lee & Thys Coetze, 2021. "Student Perceptions of Teaching Quality in Five Countries: A Partial Credit Model Approach to Assess Measurement Invariance," SAGE Open, , vol. 11(3), pages 21582440211, August.
    5. Kai Liu & Longfei Zhang & Dongbo Tu & Yan Cai, 2022. "Developing an Item Bank of Computerized Adaptive Testing for Eating Disorders in Chinese University Students," SAGE Open, , vol. 12(4), pages 21582440221, December.
    6. Ke-Hai Yuan & Hongyun Liu & Yuting Han, 2021. "Differential Item Functioning Analysis Without A Priori Information on Anchor Items: QQ Plots and Graphical Test," Psychometrika, Springer;The Psychometric Society, vol. 86(2), pages 345-377, June.
    7. Jeanne A. Teresi & Chun Wang & Marjorie Kleinman & Richard N. Jones & David J. Weiss, 2021. "Differential Item Functioning Analyses of the Patient-Reported Outcomes Measurement Information System (PROMIS®) Measures: Methods, Challenges, Advances, and Future Directions," Psychometrika, Springer;The Psychometric Society, vol. 86(3), pages 674-711, September.
    8. Luo, Nanyu & Ji, Feng & Han, Yuting & He, Jinbo & Zhang, Xiaoya, 2024. "Fitting item response theory models using deep learning computational frameworks," OSF Preprints tjxab, Center for Open Science.
    9. Melissa Gladstone & Gillian Lancaster & Gareth McCray & Vanessa Cavallera & Claudia R. L. Alves & Limbika Maliwichi & Muneera A. Rasheed & Tarun Dua & Magdalena Janus & Patricia Kariger, 2021. "Validation of the Infant and Young Child Development (IYCD) Indicators in Three Countries: Brazil, Malawi and Pakistan," IJERPH, MDPI, vol. 18(11), pages 1-19, June.
    10. Björn Andersson & Tao Xin, 2021. "Estimation of Latent Regression Item Response Theory Models Using a Second-Order Laplace Approximation," Journal of Educational and Behavioral Statistics, , vol. 46(2), pages 244-265, April.
    11. Victoria T. Tanaka & George Engelhard & Matthew P. Rabbitt, 2020. "Using a Bifactor Model to Measure Food Insecurity in Households with Children," Journal of Family and Economic Issues, Springer, vol. 41(3), pages 492-504, September.
    12. Klaas Sijtsma & Jules L. Ellis & Denny Borsboom, 2024. "Recognize the Value of the Sum Score, Psychometrics’ Greatest Accomplishment," Psychometrika, Springer;The Psychometric Society, vol. 89(1), pages 84-117, March.
    13. Çetin Toraman & Güneş Korkmaz, 2023. "What is the “Meaning of School†to High School Students? A Scale Development and Implementation Study Based on IRT and CTT," SAGE Open, , vol. 13(3), pages 21582440231, September.
    14. Elina Tsigeman & Sebastian Silas & Klaus Frieler & Maxim Likhanov & Rebecca Gelding & Yulia Kovas & Daniel Müllensiefen, 2022. "The Jack and Jill Adaptive Working Memory Task: Construction, Calibration and Validation," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-29, January.
    15. Joshua B. Gilbert & James S. Kim & Luke W. Miratrix, 2023. "Modeling Item-Level Heterogeneous Treatment Effects With the Explanatory Item Response Model: Leveraging Large-Scale Online Assessments to Pinpoint the Impact of Educational Interventions," Journal of Educational and Behavioral Statistics, , vol. 48(6), pages 889-913, December.
    16. Bing Li & Cody Ding & Huiying Shi & Fenghui Fan & Liya Guo, 2023. "Assessment of Psychological Zone of Optimal Performance among Professional Athletes: EGA and Item Response Theory Analysis," Sustainability, MDPI, vol. 15(10), pages 1-15, May.
    17. Joakim Wallmark & James O. Ramsay & Juan Li & Marie Wiberg, 2024. "Analyzing Polytomous Test Data: A Comparison Between an Information-Based IRT Model and the Generalized Partial Credit Model," Journal of Educational and Behavioral Statistics, , vol. 49(5), pages 753-779, October.
    18. Ick Hoon Jin & Minjeong Jeon, 2019. "A Doubly Latent Space Joint Model for Local Item and Person Dependence in the Analysis of Item Response Data," Psychometrika, Springer;The Psychometric Society, vol. 84(1), pages 236-260, March.
    19. Michela Gnaldi & Silvia Bacci & Thiemo Kunze & Samuel Greiff, 2020. "Students’ Complex Problem Solving Profiles," Psychometrika, Springer;The Psychometric Society, vol. 85(2), pages 469-501, June.
    20. Alessandro Chiarotto & Annette Bishop & Nadine E Foster & Kirsty Duncan & Ebenezer Afolabi & Raymond W Ostelo & Muirne C S Paap, 2018. "Item response theory evaluation of the biomedical scale of the Pain Attitudes and Beliefs Scale," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-17, September.

    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:sae:sagope:v:14:y:2024:i:3:p:21582440241271087. 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: SAGE Publications (email available below). General contact details of provider: .

    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.