IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v67y2014i4p598-607.html
   My bibliography  Save this article

Detecting gender item bias and differential manifest response behavior: A Rasch-based solution

Author

Listed:
  • Salzberger, Thomas
  • Newton, Fiona J.
  • Ewing, Michael T.

Abstract

Although gender is a salient variable in consumer research, researchers largely overlook whether, and how, it influences consumer response to indicators measuring latent variables. The authors therefore extend the framework of measurement equivalence assessment to the largely overlooked issue of differential item response behavior between men and women. This paper demonstrates the efficacy of using item response theory to investigate the presence of gender item bias. This methodological approach affords researchers the means of objectively disentangling actual gender differences and gender bias. Ignoring the possibility of gender item bias has the potential to bias means and thereby compromise any substantive gender-based mean comparisons. The authors conclude with solutions to address gender item bias both pre and post survey construction.

Suggested Citation

  • Salzberger, Thomas & Newton, Fiona J. & Ewing, Michael T., 2014. "Detecting gender item bias and differential manifest response behavior: A Rasch-based solution," Journal of Business Research, Elsevier, vol. 67(4), pages 598-607.
  • Handle: RePEc:eee:jbrese:v:67:y:2014:i:4:p:598-607
    DOI: 10.1016/j.jbusres.2013.02.045
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296313000751
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jbusres.2013.02.045?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. Richard, Marie-Odile & Chebat, Jean-Charles & Yang, Zhiyong & Putrevu, Sanjay, 2010. "A proposed model of online consumer behavior: Assessing the role of gender," Journal of Business Research, Elsevier, vol. 63(9-10), pages 926-934, September.
    2. Geoff Masters, 1982. "A rasch model for partial credit scoring," Psychometrika, Springer;The Psychometric Society, vol. 47(2), pages 149-174, June.
    3. Darren W. Dahl & Jaideep Sengupta & Kathleen D. Vohs, 2009. "Sex in Advertising: Gender Differences and the Role of Relationship Commitment," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 36(2), pages 215-231.
    4. David Andrich, 1995. "Further remarks on nondichotomization of graded responses," Psychometrika, Springer;The Psychometric Society, vol. 60(1), pages 37-46, March.
    5. Jagdip Singh, 1995. "Measurement in Cross-National Research," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 26(3), pages 597-619, September.
    6. Singh, Jagdip, 2004. "Tackling measurement problems with Item Response Theory: Principles, characteristics, and assessment, with an illustrative example," Journal of Business Research, Elsevier, vol. 57(2), pages 184-208, February.
    7. Martijn G. De Jong & Jan-Benedict E. M. Steenkamp & Jean-Paul Fox, 2007. "Relaxing Measurement Invariance in Cross-National Consumer Research Using a Hierarchical IRT Model," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 34(2), pages 260-278, June.
    8. David Andrich, 1995. "Models for measurement, precision, and the nondichotomization of graded responses," Psychometrika, Springer;The Psychometric Society, vol. 60(1), pages 7-26, March.
    9. Wolin, Lori D., 2003. "Gender Issues in Advertising—An Oversight Synthesis of Research: 1970–2002," Journal of Advertising Research, Cambridge University Press, vol. 43(1), pages 111-129, March.
    10. Michaela Gelin & Bruce Carleton & M. Smith & Bruno. Zumbo, 2004. "The Dimensionality and Gender Differential Item Functioning of the Mini Asthma Quality of Life Questionnaire (MiniAQLQ)," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 68(1), pages 91-105, August.
    11. Karl Christensen & Jakob Bjorner & Svend Kreiner & Jørgen Petersen, 2002. "Testing unidimensionality in polytomous Rasch models," Psychometrika, Springer;The Psychometric Society, vol. 67(4), pages 563-574, December.
    12. David Andrich, 1978. "A rating formulation for ordered response categories," Psychometrika, Springer;The Psychometric Society, vol. 43(4), pages 561-573, December.
    13. John A. Fleishman & William D. Spector & Barbara M. Altman, 2002. "Impact of Differential Item Functioning on Age and Gender Differences in Functional Disability," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 57(5), pages 275-284.
    14. Steenkamp, Jan-Benedict E M & Baumgartner, Hans, 1998. "Assessing Measurement Invariance in Cross-National Consumer Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 25(1), pages 78-90, 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. José Alberto Martínez-González & Urszula Kobylinska & Desiderio Gutiérrez-Taño, 2021. "Exploring Personal and Contextual Variables of the Global Entrepreneurship Monitor through the Rasch Mathematical Model," Mathematics, MDPI, vol. 9(16), pages 1-23, August.
    2. Brush, Gregory J. & Soutar, Geoffrey N., 2022. "A Rasch analysis of service performance in a tourism context," Journal of Business Research, Elsevier, vol. 139(C), pages 338-353.
    3. José Alberto Martínez-González & Vidina Tais Díaz-Padilla & Eduardo Parra-López, 2021. "Study of the Tourism Competitiveness Model of the World Economic Forum Using Rasch’s Mathematical Model: The Case of Portugal," Sustainability, MDPI, vol. 13(13), pages 1-20, June.
    4. Ganglmair-Wooliscroft, Alexandra & Wooliscroft, Ben, 2022. "An investigation of sustainable consumption behavior systems – Exploring personal and socio-structural characteristics in different national contexts," Journal of Business Research, Elsevier, vol. 148(C), pages 161-173.
    5. Sarstedt, Marko & Diamantopoulos, Adamantios & Salzberger, Thomas & Baumgartner, Petra, 2016. "Selecting single items to measure doubly concrete constructs: A cautionary tale," Journal of Business Research, Elsevier, vol. 69(8), pages 3159-3167.
    6. Vanessa Yanes-Estévez & Ana María García-Pérez & Juan Ramón Oreja-Rodríguez, 2018. "The Strategic Behaviour of SMEs," Administrative Sciences, MDPI, vol. 8(4), pages 1-21, October.

    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. Salzberger, Thomas & Koller, Monika, 2013. "Towards a new paradigm of measurement in marketing," Journal of Business Research, Elsevier, vol. 66(9), pages 1307-1317.
    2. David Andrich, 2010. "Sufficiency and Conditional Estimation of Person Parameters in the Polytomous Rasch Model," Psychometrika, Springer;The Psychometric Society, vol. 75(2), pages 292-308, June.
    3. Strizhakova, Yuliya & Coulter, Robin A. & Price, Linda L., 2008. "The meanings of branded products: A cross-national scale development and meaning assessment," International Journal of Research in Marketing, Elsevier, vol. 25(2), pages 82-93.
    4. Bartolucci, Francesco & Bacci, Silvia & Gnaldi, Michela, 2014. "MultiLCIRT: An R package for multidimensional latent class item response models," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 971-985.
    5. Miloš Kankaraš & Jeroen K. Vermunt & Guy Moors, 2011. "Measurement Equivalence of Ordinal Items: A Comparison of Factor Analytic, Item Response Theory, and Latent Class Approaches," Sociological Methods & Research, , vol. 40(2), pages 279-310, May.
    6. Silvana Bortolotti & Rafael Tezza & Dalton Andrade & Antonio Bornia & Afonso Sousa Júnior, 2013. "Relevance and advantages of using the item response theory," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(4), pages 2341-2360, June.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. Martijn G. de Jong & Jan-Benedict E. M. Steenkamp & Bernard P. Veldkamp, 2009. "A Model for the Construction of Country-Specific Yet Internationally Comparable Short-Form Marketing Scales," Marketing Science, INFORMS, vol. 28(4), pages 674-689, 07-08.
    13. Andreas Engelen & Jan Kemper & Malte Brettel, 2010. "Die Wirkung von operativen Marketing-Mix-Fähigkeiten auf den Unternehmenserfolg — Ein 4-Länder-Vergleich," Schmalenbach Journal of Business Research, Springer, vol. 62(7), pages 710-743, November.
    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. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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).
    20. 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.

    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:eee:jbrese:v:67:y:2014:i:4:p:598-607. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbusres .

    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.