Results 131 to 140 of about 803 (164)
Transforming SIBTEST to Account for Multilevel Data Structures
Journal of Educational Measurement, 2015 SIBTEST is a differential item functioning (DIF) detection method that is accurate and effective with small samples, in the presence of group mean differences, and for assessment of both uniform and nonuniform DIF. The presence of multilevel data with DIF detection has received increased attention. Ignoring such structure can inflate Type I error. This
Brian F. French, W. Holmes Finch
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Improving the Crossing-SIBTEST Statistic for Detecting Non-uniform DIF
Psychometrika, 2017 This paper demonstrates that, after applying a simple modification to Li and Stout’s (Psychometrika 61(4):647–677, 1996) CSIBTEST statistic, an improved variant of the statistic could be realized. It is shown that this modified version of CSIBTEST has a more direct association with the SIBTEST statistic presented by Shealy and Stout (Psychometrika 58(2)
R. Philip Chalmers
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SMALL‐SAMPLE DIF ESTIMATION USING LOG‐LINEAR SMOOTHING: A SIBTEST APPLICATION
ETS Research Report Series, 2007 ABSTRACTThe purpose of the current study was to examine whether log‐linear smoothing of observed score distributions in small samples results in more accurate differential item functioning (DIF) estimates under the simultaneous item bias test (SIBTEST) framework.
Gautam Puhan +3 more
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Improved Type I Error Control and Reduced Estimation Bias for DIF Detection Using SIBTEST
Journal of Educational and Behavioral Statistics, 1998 One emphasis in the development and evaluation of SIBTEST has been the control of Type I error (false flagging of non-differential item functioning [DIF] items) inflation and estimation bias. SIBTEST has performed well in comparative simulation studies of Type I error and estimation bias relative to other procedures such as the Mantel-Haenszel and ...
Hai Jiang, William Stout
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A Power Formula for the SIBTEST Procedure for Differential Item Functioning
Applied Psychological Measurement, 2014 A power formula for the SIBTEST procedure for differential item functioning (DIF) is derived. The power of SIBTEST is related to the item response function (IRF) for the studied item, the latent trait distributions and the sample sizes for the reference and focal groups, and the proportion of each group in the sample.
Zhushan Li
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Simulated Tests of Differential Item Functioning Using SIBTEST With and Without Impact
Journal of Educational Measurement, 2008 Monte Carlo simulations with 20,000 replications are reported to estimate the probability of rejecting the null hypothesis regarding DIF using SIBTEST when there is DIF present and/or when impact is present due to differences on the primary dimension to be measured. Sample sizes are varied from 250 to 2000 and test lengths from 10 to 40 items. Results
Alan J. Klockars, Yoon Sun Lee
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Small-Sample DIF Estimation Using SIBTEST, Cochran’s Z, and Log-Linear Smoothing
Applied Psychological Measurement, 2013 Minimum sample sizes of about 200 to 250 per group are often recommended for differential item functioning (DIF) analyses. However, there are times when sample sizes for one or both groups of interest are smaller than 200 due to practical constraints. This study attempts to examine the performance of Simultaneous Item Bias Test (SIBTEST), Cochran’s Z ...
Pui‐Wa Lei, Hongli Li
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Multi-Group Generalizations of SIBTEST and Crossing-SIBTEST
Applied Measurement in Education, 2023 R. Philip Chalmers, Guoguo Zheng
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Journal of Educational and Behavioral Statistics, 1996 Smoothed SIBTEST, a nonparametric DIF detection procedure, amalgamates SIBTEST and kernel-smoothed item response function estimation. This procedure assesses DIF as a function of the latent trait θ that the test is designed to measure. Smoothed SIBTEST estimates this Junction with increased efficiency, as compared to SIBTEST, while providing ...
Jeffrey A. Douglas +2 more
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The impact of multidimensionality on the detection of differential bundle functioning using SIBTEST
, 2008 In response to public concern over fairness in testing, conducting a differential item functioning (DIF) analysis is now standard practice for many large-scale testing programs (e.g., Scholastic Aptitude Test, intelligence tests, licensing exams). As highlighted by the Standards for Educational and Psychological Testing manual, the legal and ethical ...
Terris Raiford Ross
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