Literature DB >> 26795105

Evaluation of MIMIC-Model Methods for DIF Testing With Comparison to Two-Group Analysis.

Carol M Woods1.   

Abstract

Differential item functioning (DIF) occurs when an item on a test or questionnaire has different measurement properties for 1 group of people versus another, irrespective of mean differences on the construct. This study focuses on the use of multiple-indicator multiple-cause (MIMIC) structural equation models for DIF testing, parameterized as item response models. The accuracy of these methods, and the sample size requirements, are not well established. This study examines the accuracy of MIMIC methods for DIF testing when the focal group is small and compares results with those obtained using 2-group item response theory (IRT). Results support the utility of the MIMIC approach. With small focal-group samples, tests of uniform DIF with binary or 5-category ordinal responses were more accurate with MIMIC models than 2-group IRT. Recommendations are offered for the application of MIMIC methods for DIF testing.

Entities:  

Year:  2009        PMID: 26795105     DOI: 10.1080/00273170802620121

Source DB:  PubMed          Journal:  Multivariate Behav Res        ISSN: 0027-3171            Impact factor:   5.923


  41 in total

1.  Modeling and Testing Differential Item Functioning in Unidimensional Binary Item Response Models with a Single Continuous Covariate: A Functional Data Analysis Approach.

Authors:  Yang Liu; Brooke E Magnus; David Thissen
Journal:  Psychometrika       Date:  2015-07-09       Impact factor: 2.500

2.  Analysis of differential item functioning in the depression item bank from the Patient Reported Outcome Measurement Information System (PROMIS): An item response theory approach.

Authors:  Jeanne A Teresi; Katja Ocepek-Welikson; Marjorie Kleinman; Joseph P Eimicke; Paul K Crane; Richard N Jones; Jin-Shei Lai; Seung W Choi; Ron D Hays; Bryce B Reeve; Steven P Reise; Paul A Pilkonis; David Cella
Journal:  Psychol Sci Q       Date:  2009

3.  MIMIC Methods for Detecting DIF Among Multiple Groups: Exploring a New Sequential-Free Baseline Procedure.

Authors:  Seokjoon Chun; Stephen Stark; Eun Sook Kim; Oleksandr S Chernyshenko
Journal:  Appl Psychol Meas       Date:  2016-07-28

4.  The Mediated MIMIC Model for Understanding the Underlying Mechanism of DIF.

Authors:  Ying Cheng; Can Shao; Quinn N Lathrop
Journal:  Educ Psychol Meas       Date:  2015-03-25       Impact factor: 2.821

5.  Item Response Theory With Covariates (IRT-C): Assessing Item Recovery and Differential Item Functioning for the Three-Parameter Logistic Model.

Authors:  Louis Tay; Qiming Huang; Jeroen K Vermunt
Journal:  Educ Psychol Meas       Date:  2015-04-06       Impact factor: 2.821

6.  Multidimensional Extension of Multiple Indicators Multiple Causes Models to Detect DIF.

Authors:  Soo Lee; Okan Bulut; Youngsuk Suh
Journal:  Educ Psychol Meas       Date:  2016-05-25       Impact factor: 2.821

7.  Screening for depression in arthritis populations: an assessment of differential item functioning in three self-reported questionnaires.

Authors:  Jinxiang Hu; Michael M Ward
Journal:  Qual Life Res       Date:  2017-06-17       Impact factor: 4.147

8.  Measurement invariance, the lack thereof, and modeling change.

Authors:  Michael C Edwards; Carrie R Houts; R J Wirth
Journal:  Qual Life Res       Date:  2017-08-17       Impact factor: 4.147

9.  Telomere Length and Psychopathology: Specificity and Direction of Effects Within the Bucharest Early Intervention Project.

Authors:  Mark Wade; Nathan A Fox; Charles H Zeanah; Charles A Nelson; Stacy S Drury
Journal:  J Am Acad Child Adolesc Psychiatry       Date:  2019-03-04       Impact factor: 8.829

10.  Testing measurement equivalence of the SF-36 questionnaire across patients on hemodialysis and healthy people.

Authors:  Zahra Bagheri; Peyman Jafari; Marjan Faghih; Elahe Allahyari; Tania Dehesh
Journal:  Int Urol Nephrol       Date:  2015-09-02       Impact factor: 2.370

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