Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 0 |
Since 2016 (last 10 years) | 0 |
Since 2006 (last 20 years) | 60 |
Descriptor
Item Response Theory | 61 |
Test Bias | 54 |
Test Items | 53 |
Simulation | 31 |
Item Bias | 29 |
Statistical Bias | 27 |
Models | 26 |
Computation | 22 |
Error of Measurement | 21 |
Monte Carlo Methods | 19 |
Comparative Analysis | 18 |
More ▼ |
Source
Applied Psychological… | 114 |
Author
Woods, Carol M. | 6 |
Cohen, Allan S. | 5 |
Raju, Nambury S. | 5 |
Drasgow, Fritz | 4 |
Finch, Holmes | 4 |
Kim, Seock-Ho | 4 |
Oshima, T. C. | 4 |
Penfield, Randall D. | 4 |
Wang, Wen-Chung | 4 |
van der Linden, Wim J. | 4 |
Chang, Hua-Hua | 3 |
More ▼ |
Publication Type
Journal Articles | 111 |
Reports - Research | 52 |
Reports - Evaluative | 51 |
Reports - Descriptive | 8 |
Information Analyses | 3 |
Speeches/Meeting Papers | 3 |
Book/Product Reviews | 1 |
Education Level
Elementary Education | 1 |
Grade 4 | 1 |
Higher Education | 1 |
Intermediate Grades | 1 |
Audience
Practitioners | 1 |
Laws, Policies, & Programs
Assessments and Surveys
Armed Services Vocational… | 2 |
General Aptitude Test Battery | 1 |
Graduate Record Examinations | 1 |
Law School Admission Test | 1 |
Program for International… | 1 |
What Works Clearinghouse Rating
Lei, Pui-Wa; Li, Hongli – 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),…
Descriptors: Sample Size, Test Bias, Computation, Accuracy
Cheng, Ying; Chen, Peihua; Qian, Jiahe; Chang, Hua-Hua – Applied Psychological Measurement, 2013
Differential item functioning (DIF) analysis is an important step in the data analysis of large-scale testing programs. Nowadays, many such programs endorse matrix sampling designs to reduce the load on examinees, such as the balanced incomplete block (BIB) design. These designs pose challenges to the traditional DIF analysis methods. For example,…
Descriptors: Test Bias, Equated Scores, Test Items, Effect Size
Wang, Wei; Tay, Louis; Drasgow, Fritz – Applied Psychological Measurement, 2013
There has been growing use of ideal point models to develop scales measuring important psychological constructs. For meaningful comparisons across groups, it is important to identify items on such scales that exhibit differential item functioning (DIF). In this study, the authors examined several methods for assessing DIF on polytomous items…
Descriptors: Test Bias, Effect Size, Item Response Theory, Statistical Analysis
Dai, Yunyun – Applied Psychological Measurement, 2013
Mixtures of item response theory (IRT) models have been proposed as a technique to explore response patterns in test data related to cognitive strategies, instructional sensitivity, and differential item functioning (DIF). Estimation proves challenging due to difficulties in identification and questions of effect size needed to recover underlying…
Descriptors: Item Response Theory, Test Bias, Computation, Bayesian Statistics
De Boeck, Paul; Cho, Sun-Joo; Wilson, Mark – Applied Psychological Measurement, 2011
The models used in this article are secondary dimension mixture models with the potential to explain differential item functioning (DIF) between latent classes, called latent DIF. The focus is on models with a secondary dimension that is at the same time specific to the DIF latent class and linked to an item property. A description of the models…
Descriptors: Test Bias, Models, Statistical Analysis, Computation
Woods, Carol M. – Applied Psychological Measurement, 2011
Differential item functioning (DIF) occurs when an item on a test, questionnaire, or interview has different measurement properties for one group of people versus another, irrespective of true group-mean differences on the constructs being measured. This article is focused on item response theory based likelihood ratio testing for DIF (IRT-LR or…
Descriptors: Simulation, Item Response Theory, Testing, Questionnaires
Sun, Shan-Shan; Tao, Jian; Chang, Hua-Hua; Shi, Ning-Zhong – Applied Psychological Measurement, 2012
For mixed-type tests composed of dichotomous and polytomous items, polytomous items often yield more information than dichotomous items. To reflect the difference between the two types of items and to improve the precision of ability estimation, an adaptive weighted maximum-a-posteriori (WMAP) estimation is proposed. To evaluate the performance of…
Descriptors: Monte Carlo Methods, Computation, Item Response Theory, Weighted Scores
van der Linden, Wim J.; Wiberg, Marie – Applied Psychological Measurement, 2010
For traditional methods of observed-score equating with anchor-test designs, such as chain and poststratification equating, it is difficult to satisfy the criteria of equity and population invariance. Their equatings are therefore likely to be biased. The bias in these methods was evaluated against a simple local equating method in which the…
Descriptors: Methods, Equated Scores, Test Items, Bias
Doebler, Anna – Applied Psychological Measurement, 2012
It is shown that deviations of estimated from true values of item difficulty parameters, caused for example by item calibration errors, the neglect of randomness of item difficulty parameters, testlet effects, or rule-based item generation, can lead to systematic bias in point estimation of person parameters in the context of adaptive testing.…
Descriptors: Adaptive Testing, Computer Assisted Testing, Computation, Item Response Theory
Carter, Nathan T.; Zickar, Michael J. – Applied Psychological Measurement, 2011
Recently, applied psychological measurement researchers have become interested in the application of the generalized graded unfolding model (GGUM), a parametric item response theory model that posits an ideal point conception of the relationship between latent attributes and observed item responses. Little attention has been given to…
Descriptors: Test Bias, Maximum Likelihood Statistics, Item Response Theory, Models
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
Seybert, Jacob; Stark, Stephen – Applied Psychological Measurement, 2012
A Monte Carlo study was conducted to examine the accuracy of differential item functioning (DIF) detection using the differential functioning of items and tests (DFIT) method. Specifically, the performance of DFIT was compared using "testwide" critical values suggested by Flowers, Oshima, and Raju, based on simulations involving large numbers of…
Descriptors: Test Bias, Monte Carlo Methods, Form Classes (Languages), Simulation
Finch, W. Holmes – Applied Psychological Measurement, 2012
Increasingly, researchers interested in identifying potentially biased test items are encouraged to use a confirmatory, rather than exploratory, approach. One such method for confirmatory testing is rooted in differential bundle functioning (DBF), where hypotheses regarding potential differential item functioning (DIF) for sets of items (bundles)…
Descriptors: Test Bias, Test Items, Statistical Analysis, Models
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
Penfield, Randall D. – Applied Psychological Measurement, 2010
Crossing, or intersecting, differential item functioning (DIF) is a form of nonuniform DIF that exists when the sign of the between-group difference in expected item performance changes across the latent trait continuum. The presence of crossing DIF presents a problem for many statistics developed for evaluating DIF because positive and negative…
Descriptors: Test Bias, Test Items, Statistics, Test Theory