NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 6 results Save | Export
Strategies for Testing Statistical and Practical Significance in Detecting DIF with Logistic Regression Models
Peer reviewed Peer reviewed
Direct linkDirect link
Fidalgo, Angel M.; Alavi, Seyed Mohammad; Amirian, Seyed Mohammad Reza – Language Testing, 2014
This study examines three controversial aspects in differential item functioning (DIF) detection by logistic regression (LR) models: first, the relative effectiveness of different analytical strategies for detecting DIF; second, the suitability of the Wald statistic for determining the statistical significance of the parameters of interest; and…
Descriptors: Test Bias, Regression (Statistics), Statistical Significance, Language Tests
GMHDIF: A Computer Program for Detecting DIF in Dichotomous and Polytomous Items Using Generalized Mantel-Haenszel Statistics
Peer reviewed Peer reviewed
Direct linkDirect link
Fidalgo, Angel M. – Applied Psychological Measurement, 2011
Mantel-Haenszel (MH) methods constitute one of the most popular nonparametric differential item functioning (DIF) detection procedures. GMHDIF has been developed to provide an easy-to-use program for conducting DIF analyses. Some of the advantages of this program are that (a) it performs two-stage DIF analyses in multiple groups simultaneously;…
Descriptors: Test Bias, Computer Software, Statistics, Comparative Analysis
A Comparison between Some Generalized Mantel-Haenszel Statistics for Detecting DIF in Data Simulated under the Graded Response Model
Peer reviewed Peer reviewed
Direct linkDirect link
Fidalgo, Angel M.; Bartram, Dave – Applied Psychological Measurement, 2010
The main objective of this study was to establish the relative efficacy of the generalized Mantel-Haenszel test (GMH) and the Mantel test for detecting large numbers of differential item functioning (DIF) patterns. To this end this study considered a topic not dealt with in the literature to date: the possible differential effect of type of scores…
Descriptors: Test Bias, Statistics, Scoring, Comparative Analysis
Using Generalized Mantel-Haenszel Statistics to Assess DIF among Multiple Groups
Peer reviewed Peer reviewed
Direct linkDirect link
Fidalgo, Angel M.; Scalon, Joao D. – Journal of Psychoeducational Assessment, 2010
In spite of the growing interest in cross-cultural research and assessment, there is little research on statistical procedures that can be used to simultaneously assess the differential item functioning (DIF) across multiple groups. The chief objective of this work is to show a unified framework for the analysis of DIF in multiple groups using one…
Descriptors: Test Bias, Statistics, Evaluation, Item Response Theory
Generalized Mantel-Haenszel Methods for Differential Item Functioning Detection
Peer reviewed Peer reviewed
Direct linkDirect link
Fidalgo, Angel M.; Madeira, Jaqueline M. – Educational and Psychological Measurement, 2008
Mantel-Haenszel methods comprise a highly flexible methodology for assessing the degree of association between two categorical variables, whether they are nominal or ordinal, while controlling for other variables. The versatility of Mantel-Haenszel analytical approaches has made them very popular in the assessment of the differential functioning…
Descriptors: Test Bias, Statistical Analysis, Generalization, Evaluation Research
Empirical Bayes versus Standard Mantel-Haenszel Statistics for Detecting Differential Item Functioning under Small Sample Conditions
Peer reviewed Peer reviewed
Direct linkDirect link
Fidalgo, Angel M.; Hashimoto, Kanako; Bartram, Dave; Muniz, Jose – Journal of Experimental Education, 2007
In this study, the authors assess several strategies created on the basis of the Mantel-Haenszel (MH) procedure for conducting differential item functioning (DIF) analysis with small samples. One of the analytical strategies is a loss function (LF) that uses empirical Bayes Mantel-Haenszel estimators, whereas the other strategies use the classical…
Descriptors: Bayesian Statistics, Test Bias, Statistical Analysis, Sample Size