Generalized Mantel-Haenszel Estimators for Simultaneous Differential Item Functioning Tests

被引:1
作者
Liu, Ivy [1 ]
Suesse, Thomas [2 ]
Harvey, Samuel [1 ]
Gu, Peter Yongqi [1 ]
Fernandez, Daniel [3 ,4 ,5 ]
Randal, John [1 ]
机构
[1] Victoria Univ Wellington, Wellington, New Zealand
[2] Univ Wollongong, Wollongong, NSW, Australia
[3] Univ Politecn Cataluna, BarcelonaTech, Barcelona, Spain
[4] UPC BarcelonaTech, Inst Math, Barcelona, Spain
[5] Ctr Invest Biomed Red Salud Mental, Madrid, Spain
关键词
differential item functioning; dually consistent; Mantel-Haenszel estimator; multiple items; COMMON ODDS RATIO; LOGISTIC-REGRESSION; MODEL; STRATEGIES; SIZE;
D O I
10.1177/00131644221128341
中图分类号
G44 [教育心理学];
学科分类号
0402 ; 040202 ;
摘要
The Mantel-Haenszel estimator is one of the most popular techniques for measuring differential item functioning (DIF). A generalization of this estimator is applied to the context of DIF to compare items by taking the covariance of odds ratio estimators between dependent items into account. Unlike the Item Response Theory, the method does not rely on the local item independence assumption which is likely to be violated when one item provides clues about the answer of another item. Furthermore, we use these (co)variance estimators to construct a hypothesis test to assess DIF for multiple items simultaneously. A simulation study is presented to assess the performance of several tests. Finally, the use of these DIF tests is illustrated via application to two real data sets.
引用
收藏
页码:1007 / 1032
页数:26
相关论文
共 67 条
[1]   Modeling a categorical variable allowing arbitrarily many category choices [J].
Agresti, A ;
Liu, IM .
BIOMETRICS, 1999, 55 (03) :936-943
[2]   Strategies for modeling a categorical variable allowing multiple category choices [J].
Agresti, A ;
Liu, I .
SOCIOLOGICAL METHODS & RESEARCH, 2001, 29 (04) :403-434
[3]  
Andersen E.B., 1980, DISCRETE STAT MODELS
[4]  
Baghaei P., 2008, RASCH MEASUREMENT T, V21, P1105
[5]   mipfp: An R Package for Multidimensional Array Fitting and Simulating Multivariate Bernoulli Distributions [J].
Barthelemy, Johan ;
Suesse, Thomas .
JOURNAL OF STATISTICAL SOFTWARE, 2018, 86 (CN2) :1-20
[6]  
Bates Douglas., 2021, Matrix: Sparse and Dense Matrix Classes and Methods
[7]   CONTROLLING THE FALSE DISCOVERY RATE - A PRACTICAL AND POWERFUL APPROACH TO MULTIPLE TESTING [J].
BENJAMINI, Y ;
HOCHBERG, Y .
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 1995, 57 (01) :289-300
[8]   Adaptive linear step-up procedures that control the false discovery rate [J].
Benjamini, Yoav ;
Krieger, Abba M. ;
Yekutieli, Daniel .
BIOMETRIKA, 2006, 93 (03) :491-507
[9]   A Bayesian random effects model for testlets [J].
Bradlow, ET ;
Wainer, H ;
Wang, XH .
PSYCHOMETRIKA, 1999, 64 (02) :153-168
[10]  
BRESLOW N, 1981, BIOMETRIKA, V68, P73, DOI 10.1093/biomet/68.1.73