IDEAS home Printed from https://ideas.repec.org/a/spr/ariqol/v16y2021i1d10.1007_s11482-019-09761-w.html
   My bibliography  Save this article

Rasch Analysis of the Families in Early Intervention Quality of Life (FEIQoL) Scale

Author

Listed:
  • Pau García-Grau

    (The University of Alabama)

  • R. A. McWilliam

    (The University of Alabama)

  • Gabriel Martínez-Rico

    (Universidad Católica de Valencia San Vicente Mártir)

  • Catalina P. Morales-Murillo

    (Universidad Católica de Valencia San Vicente Mártir, Campus Capacitas)

Abstract

Family quality of life (FQoL) has become one of the main outcomes of services for people with disabilities and their families, especially in early intervention, which nowadays is all about families. In this article, we analyze and validate the psychometric properties of the FEIQoL scale with Spanish families in early intervention, through Rasch analysis. A total of 776 families of children 0–6 completed the FEIQoL. To assess the Rasch model, we analyzed the item fit, reliability and separation, unidimensionality, response forms, and DIF analyses. The results indicated that the scores on the FEIQoL were reliable and fit the Rasch model. The response forms were adequate, the item difficulty matched respondents’ ability levels, and we found unidimensionality in the 3 factors. DIF analysis indicated that the items did not function differently by child age. The FEIQoL could be improved by modifying misfitting items and possibly including more difficult items for respondents with high FQoL.

Suggested Citation

  • Pau García-Grau & R. A. McWilliam & Gabriel Martínez-Rico & Catalina P. Morales-Murillo, 2021. "Rasch Analysis of the Families in Early Intervention Quality of Life (FEIQoL) Scale," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 16(1), pages 383-399, February.
    • Handle: RePEc:spr:ariqol:v:16:y:2021:i:1:d:10.1007_s11482-019-09761-w
    DOI: 10.1007/s11482-019-09761-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11482-019-09761-w
    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/s11482-019-09761-w?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. Geoff Masters, 1982. "A rasch model for partial credit scoring," Psychometrika, Springer;The Psychometric Society, vol. 47(2), pages 149-174, June.
    2. Pau García-Grau & R. A. McWilliam & Gabriel Martínez-Rico & María D. Grau-Sevilla, 2018. "Factor Structure and Internal Consistency of a Spanish Version of the Family Quality of Life (FaQoL)," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 13(2), pages 385-398, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ghaleb H. Alnahdi & Arwa Alwadei & Flora Woltran & Susanne Schwab, 2022. "Measuring Family Quality of Life: Scoping Review of the Available Scales and Future Directions," IJERPH, MDPI, vol. 19(23), pages 1-26, November.

    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. César Merino-Soto & Gina Chávez-Ventura & Verónica López-Fernández & Guillermo M. Chans & Filiberto Toledano-Toledano, 2022. "Learning Self-Regulation Questionnaire (SRQ-L): Psychometric and Measurement Invariance Evidence in Peruvian Undergraduate Students," Sustainability, MDPI, vol. 14(18), pages 1-17, September.
    2. Roberto Burro & Riccardo Sartori & Giulio Vidotto, 2011. "The method of constant stimuli with three rating categories and the use of Rasch models," Quality & Quantity: International Journal of Methodology, Springer, vol. 45(1), pages 43-58, January.
    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. 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. 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.
    6. 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.
    7. Thilo J. Ketschau & Janne Kleinhans, 2019. "Concept and Implementation of a Two-Stage Coding Scheme for the Development of Computer-Based Testing (CBT)-Items in Traditional Test Software," J, MDPI, vol. 2(1), pages 1-9, January.
    8. David J. Hessen, 2023. "Fitting and Testing Log-Linear Subpopulation Models with Known Support," Psychometrika, Springer;The Psychometric Society, vol. 88(3), pages 917-939, September.
    9. 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.
    10. C. Glas & Anna Dagohoy, 2007. "A Person Fit Test For Irt Models For Polytomous Items," Psychometrika, Springer;The Psychometric Society, vol. 72(2), pages 159-180, June.
    11. 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.
    12. Salzberger, Thomas & Koller, Monika, 2013. "Towards a new paradigm of measurement in marketing," Journal of Business Research, Elsevier, vol. 66(9), pages 1307-1317.
    13. Fumiko Samejima, 1995. "Acceleration model in the heterogeneous case of the general graded response model," Psychometrika, Springer;The Psychometric Society, vol. 60(4), pages 549-572, December.
    14. Richard N McNeely & Salissou Moutari & Samuel Arba-Mosquera & Shwetabh Verma & Jonathan E Moore, 2018. "An alternative application of Rasch analysis to assess data from ophthalmic patient-reported outcome instruments," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-32, June.
    15. Francesca DE BATTISTI & Giovanna NICOLINI & Silvia SALINI, 2008. "Methodological overview of Rasch model and application in customer satisfaction survey data," Departmental Working Papers 2008-04, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    16. Kuan-Yu Jin & Yi-Jhen Wu & Hui-Fang Chen, 2022. "A New Multiprocess IRT Model With Ideal Points for Likert-Type Items," Journal of Educational and Behavioral Statistics, , vol. 47(3), pages 297-321, June.
    17. van der Ark, L. Andries, 2012. "New Developments in Mokken Scale Analysis in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i05).
    18. Maren M. Michaelsen, 2012. "Mental Health and Labour Supply: Evidence from Mexico�s Ongoing Violent Conflicts," HiCN Working Papers 117, Households in Conflict Network.
    19. Piotr Tarka, 2013. "Model of latent profile factor analysis for ordered categorical data," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 14(1), pages 171-182, March.
    20. Xiaohui Zheng & Sophia Rabe-Hesketh, 2007. "Estimating parameters of dichotomous and ordinal item response models with gllamm," Stata Journal, StataCorp LP, vol. 7(3), pages 313-333, 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:spr:ariqol:v:16:y:2021:i:1:d:10.1007_s11482-019-09761-w. 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.