Return to search

Differential Item Functioning Identification Strategy for Items with Dichotomous Responses Using the Item Information Curve: A Weighted Area Method (WAM)

Frequently researchers base their decisions and interpretations on conclusions drawn from data analyses, but what happens when the data used in the analyses are collected from unreliable instruments or surveys? The instrument may include a particular question that invokes different interpretations based on group membership, thereby placing one of the two groups at an unfair disadvantage. Another challenge occurs when the size of the sample under investigation (i.e., number of respondents or participants) is unavoidably small, adding more uncertainty to parameter estimates. Over the past 50 years, researchers have suggested many different approaches for identifying problematic questions (i.e., items that are biased), but no consensus has been reached as to which method is best. In addition, selecting appropriate methods becomes even more challenging when smaller sample sizes are involved (Lai, Teresi, & Gershon, 2005). This dissertation presents the findings of a study introducing a new method for identifying DIF and potentially biased items. The study explored the use of the Item Information Curve (IIC) as a weighting strategy (i.e., Weighted Area Method - WAM) to the area between Item Characteristic Curves (ICC) as a way to identify problematic questions. Through thousands of simulations, the performance of WAM was compared to two other commonly used methods for detecting DIF - the Mantel-Haenszel approach (Mantel & Haenszel, 1959) and the Rudner's Area method (Rudner, 1977). The results show the effects of sample size variations on identifying modeled DIF items, and the opportunity for future Differential Item Functioning (DIF) analyses using WAM. / A Dissertation submitted to the Department of Educational Psychology and Learning Systems in partial fulfillment of the
requirements for the degree of Doctor of Philosophy. / Fall Semester, 2013. / November 8, 2013. / Differential Item Functioning DIF, Item information curve IIC, Item response theory IRT, Monte Carlo, Simulation study, WAM / Includes bibliographical references. / Betsy Becker, Professor Directing Dissertation; Akihito Kamata, Professor Co-Directing Dissertation; Fred Huffer, University Representative; Yanyun Yang, Committee Member; Insu Paek, Committee Member.

Identiferoai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_254504
ContributorsSiebert, Carl F. (authoraut), Becker, Betsy (professor directing dissertation), Kamata, Akihito (professor co-directing dissertation), Huffer, Fred (university representative), Yang, Yanyun (committee member), Paek, Insu (committee member), Department of Educational Psychology and Learning Systems (degree granting department), Florida State University (degree granting institution)
PublisherFlorida State University, Florida State University
Source SetsFlorida State University
LanguageEnglish, English
Detected LanguageEnglish
TypeText, text
Format1 online resource, computer, application/pdf
RightsThis Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). The copyright in theses and dissertations completed at Florida State University is held by the students who author them.

Page generated in 0.002 seconds