Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Power and Type I Error of the Mean and Covariance Structure Analysis Model for Detecting Differential Item Functioning in Graded Response Items

Bibliographic Data

ID19290868
AuthorsVicente González-Romá (0000-0002-0657-7375), Ana Hernández (0000-0002-5237-0535), J Gómez-Benito (0000-0002-4280-3106)
Year2006
Volume41
Issue1
Pages29-53
Publication date2006-03-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueMultivariate Behavioral Research (JOURNAL)
Journal identifiersISSN: 0027-3171 • E-ISSN: 1532-7906
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1207/s15327906mbr4101_3
PMID26788893
OpenAlexW2149823923
LanguageEN
Citations received9
References cited40

In this simulation study, we investigate the power and Type I error rate of a procedure based on the mean and covariance structure analysis (MACS) model in detecting differential item functioning (DIF) of graded response items with five response categories. The following factors were manipulated: type of DIF (uniform and non-uniform), DIF magnitude (low, medium and large), equality/inequality of latent trait distributions, sample size (100, 200, 400, and 800) and equality or inequality of the sample sizes across groups. The simulated test was made up of 10 items, of which only 1 contained DIF. One hundred replications were generated for each simulated condition. Results indicate that the MACS-based procedure showed acceptable power levels (≥ .70) for detecting medium-sized uniform and non-uniform DIF, when both groups' sample sizes were as low as 200/200 and 400/200, respectively. Power increased as sample sizes and DIF magnitude increased. The analyzed procedure tended to better control for its Type I error when both groups' sizes and latent trait distribution were equal across groups and when magnitude of DIF and sample size were small

Analysis of covariance · Covariance · Differential item functioning · Item response theory · Magnitude (astronomy) · Power (physics) · Psychometrics · Sample (material) · Sample size determination · Statistical power · Statistics · Type I and type II errors · Advanced Statistical Modeling Techniques · Behavioral and Psychological Studies · Mathematics · Psychometric Methodologies and Testing

  • The Effects of Self-Construals and Interactive Constraints on Consumer Complaint Behaviors Across Cultures

    Open Access•Ayano Yamaguchi, Min-Sun Kim et al.•Psychological Studies•2016

  • Measurement equivalence

    Open Access•Laura L Pendergast, Nathaniel von der Embse et al.•Journal of School Psychology•2017

  • Accuracy of mixture item response theory models for identifying sample heterogeneity in patient-reported outcomes

    Open Access•Tolulope T Sajobi, Lisa M Lix et al.•Quality of Life Research•2022

  • Item Parceling in Structural Equation Modeling

    Masaki Matsunaga•Communication Methods and Measures•2008

  • Testing a Mediational Model of Bullied Victims' Evaluation of Received Support and Post-Bullying Adaptation

    Masaki Matsunaga•Communication Monographs•2010

  • Differential Functioning of the Chinese Version of Beck Depression Inventory-II in Adolescent Gender Groups

    Open Access•Pei‐Chen Wu•Social Indicators Research•2009

  • The MIMIC Method With Scale Purification for Detecting Differential Item Functioning

    Open Access•Wen-Chung Wang, Wen‐chung Wang et al.•Educational and Psychological…•2009

  • Personality Trait Differences Between Young and Middle‐Aged Adults

    Open Access•Christopher D Nye, Mathias Allemand et al.•Journal of Personality•2016

  • Experiences of Discrimination and Alcohol Involvement Among Young Adults at the Intersection of Race/Ethnicity and Gender

    Open Access•Hector Ismael Lopez-Vergara, William Rozum et al.•Journal of Racial and Ethnic…•2024

  • Robustness?

    Open Access•James V Bradley•British Journal of Mathematical…•1978

  • The Impact of Categorization With Confirmatory Factor Analysis

    Christine Distefano•Structural Equation Modeling: A…•2002

  • A General Method for Studying Differences in Factor Means and Factor Structure Between Groups

    Open Access•Dag Sörbom•British Journal of Mathematical…•1974

  • Estimation of Latent Ability Using a Response Pattern of Graded Scores

    Open Access•Fumiko Samejima•Psychometrika•1969

  • A comparison of some methodologies for the factor analysis of non‐normal Likert variables

    Open Access•Bengt Muthén, D M Kaplan et al.•British Journal of Mathematical…•1985

  • Testing Factorial Invariance across Groups

    Open Access•Gordon W Cheung, Roger B Rensvold•Journal of Management•1999

  • Measurement Invariance, Factor Analysis and Factorial Invariance

    Open Access•William Meredith•Psychometrika•1993

  • Structural Equations with Latent Variables

    Open Access•K A Bollen•Structural Equations with Latent…•1989

  • Testing Measurement Models for Factorial Invariance

    Open Access•Roger B Rensvold, Gordon W Cheung•Educational and Psychological…•1998

  • Detection of Differential Item Functioning on the Kirton Adaption-Innovation Inventory Using Multiple-Group Mean and Covariance Structure Analyses

    David Chan•Multivariate Behavioral Research•2000

  • On The Robustness Of Factor Analysis Against Crude Classification Of The Observations

    Ulf Olsson•Multivariate Behavioral Research•1979

  • Mean and Covariance Structures (Macs) Analyses of Cross-Cultural Data

    Todd D Little•Multivariate Behavioral Research•1997

  • Invariance on the NEO PI-R Neuroticism Scale

    Steven P Reise, Larissa L Smith et al.•Multivariate Behavioral Research•2001

  • Calibration of Invariant Item Parameters in a Continuous Item Response Model Using the Extended Lisrel Measurement Submodel

    Pere J Ferrando•Multivariate Behavioral Research•1996

  • Two Kinds of Factor Analysis For Ordered Categorical Variables

    Ab Mooijaart•Multivariate Behavioral Research•1983

  • A Unidimensional Latent Trait Model for Continuous Item Responses

    Gideon J Mellenbergh•Multivariate Behavioral Research•1994

  • Confirmatory factor analysis and item response theory

    Steven P Reise, Keith F Widaman et al.•Psychological Bulletin•1993

  • Testing for the equivalence of factor covariance and mean structures

    Barbara M Byrne, Richard J Shavelson et al.•Psychological Bulletin•1989

  • Measuring climate for work group innovation

    Open Access•Neil Anderson, Neil R Anderson et al.•Journal of Organizational Behavior•1998

  • Pearson's R and Coarsely Categorized Measures

    K A Bollen, Kenney H Barb•American Sociological Review•1981

Unique citing works9
Citations per year0,5
Citation span2008 - 2024 (17)
Citation velocityrecent
Highly citedNo
Citation typesNeutral: 9
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae