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

Thomas Salzberger, Fiona Joy Newton, Michael Thomas Ewing

Research output: Contribution to journal › Article › Research › peer-review

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.
Original languageEnglish
Pages (from-to)598 - 607
Number of pages10
JournalJournal of Business Research
Volume67
Issue number4
DOIs
Publication statusPublished - 2014

Cite this

Salzberger, Thomas ; Newton, Fiona Joy ; Ewing, Michael Thomas. / Detecting gender item bias and differential manifest response behavior: A Rasch-based solution. In: Journal of Business Research. 2014 ; Vol. 67, No. 4. pp. 598 - 607.
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Salzberger, T, Newton, FJ & Ewing, MT 2014, 'Detecting gender item bias and differential manifest response behavior: A Rasch-based solution' Journal of Business Research, vol. 67, no. 4, pp. 598 - 607. https://doi.org/10.1016/j.jbusres.2013.02.045

Detecting gender item bias and differential manifest response behavior: A Rasch-based solution. / Salzberger, Thomas; Newton, Fiona Joy; Ewing, Michael Thomas.

In: Journal of Business Research, Vol. 67, No. 4, 2014, p. 598 - 607.

Research output: Contribution to journal › Article › Research › peer-review

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Salzberger T, Newton FJ, Ewing MT. Detecting gender item bias and differential manifest response behavior: A Rasch-based solution. Journal of Business Research. 2014;67(4):598 - 607. https://doi.org/10.1016/j.jbusres.2013.02.045

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