Publication Date
In 2025 | 0 |
Since 2024 | 1 |
Since 2021 (last 5 years) | 2 |
Since 2016 (last 10 years) | 5 |
Since 2006 (last 20 years) | 15 |
Descriptor
Error of Measurement | 15 |
Item Response Theory | 15 |
Nonparametric Statistics | 15 |
Sample Size | 6 |
Statistical Analysis | 6 |
Test Items | 6 |
Goodness of Fit | 5 |
Models | 4 |
Scores | 4 |
Test Bias | 4 |
Comparative Analysis | 3 |
More ▼ |
Source
Author
Publication Type
Journal Articles | 12 |
Reports - Research | 10 |
Reports - Evaluative | 3 |
Dissertations/Theses -… | 2 |
Speeches/Meeting Papers | 1 |
Education Level
Early Childhood Education | 1 |
Elementary Education | 1 |
Elementary Secondary Education | 1 |
Grade 3 | 1 |
Primary Education | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
Trends in International… | 1 |
What Works Clearinghouse Rating
Turner, Kyle T.; Engelhard, George, Jr. – Measurement: Interdisciplinary Research and Perspectives, 2023
The purpose of this study is to illustrate the use of functional data analysis (FDA) as a general methodology for analyzing person response functions (PRFs). Applications of FDA to psychometrics have included the estimation of item response functions and latent distributions, as well as differential item functioning. Although FDA has been…
Descriptors: Data Analysis, Item Response Theory, Psychometrics, Statistical Distributions
Zebing Wu – ProQuest LLC, 2024
Response style, one common aberrancy in non-cognitive assessments in psychological fields, is problematic in terms of inaccurate estimation of item and person parameters, which leads to serious reliability, validity, and fairness issues (Baumgartner & Steenkamp, 2001; Bolt & Johnson, 2009; Bolt & Newton, 2011). Response style refers to…
Descriptors: Response Style (Tests), Accuracy, Preferences, Psychological Testing
Jinjin Huang – ProQuest LLC, 2020
Measurement invariance is crucial for an effective and valid measure of a construct. Invariance holds when the latent trait varies consistently across subgroups; in other words, the mean differences among subgroups are only due to true latent ability differences. Differential item functioning (DIF) occurs when measurement invariance is violated.…
Descriptors: Robustness (Statistics), Item Response Theory, Test Items, Item Analysis
Dirlik, Ezgi Mor – International Journal of Progressive Education, 2019
Item response theory (IRT) has so many advantages than its precedent Classical Test Theory (CTT) such as non-changing item parameters, ability parameter estimations free from the items. However, in order to get these advantages, some assumptions should be met and they are; unidimensionality, normality and local independence. However, it is not…
Descriptors: Comparative Analysis, Nonparametric Statistics, Item Response Theory, Models
Liang, Longjuan; Browne, Michael W. – Journal of Educational and Behavioral Statistics, 2015
If standard two-parameter item response functions are employed in the analysis of a test with some newly constructed items, it can be expected that, for some items, the item response function (IRF) will not fit the data well. This lack of fit can also occur when standard IRFs are fitted to personality or psychopathology items. When investigating…
Descriptors: Item Response Theory, Statistical Analysis, Goodness of Fit, Bayesian Statistics
Sengul Avsar, Asiye; Tavsancil, Ezel – Educational Sciences: Theory and Practice, 2017
This study analysed polytomous items' psychometric properties according to nonparametric item response theory (NIRT) models. Thus, simulated datasets--three different test lengths (10, 20 and 30 items), three sample distributions (normal, right and left skewed) and three samples sizes (100, 250 and 500)--were generated by conducting 20…
Descriptors: Test Items, Psychometrics, Nonparametric Statistics, Item Response Theory
Socha, Alan; DeMars, Christine E.; Zilberberg, Anna; Phan, Ha – International Journal of Testing, 2015
The Mantel-Haenszel (MH) procedure is commonly used to detect items that function differentially for groups of examinees from various demographic and linguistic backgrounds--for example, in international assessments. As in some other DIF methods, the total score is used to match examinees on ability. In thin matching, each of the total score…
Descriptors: Test Items, Educational Testing, Evaluation Methods, Ability Grouping
Guo, Hongwen; Sinharay, Sandip – Educational Testing Service, 2011
Nonparametric, or kernel, estimation of item response curve (IRC) is a concern theoretically and operationally. Accuracy of this estimation, often used in item analysis in testing programs, is biased when the observed scores are used as the regressor because the observed scores are contaminated by measurement error. In this study, we investigate…
Descriptors: Error of Measurement, Nonparametric Statistics, Item Response Theory, Computation
Guo, Hongwen; Sinharay, Sandip – Journal of Educational and Behavioral Statistics, 2011
Nonparametric or kernel regression estimation of item response curves (IRCs) is often used in item analysis in testing programs. These estimates are biased when the observed scores are used as the regressor because the observed scores are contaminated by measurement error. Accuracy of this estimation is a concern theoretically and operationally.…
Descriptors: Testing Programs, Measurement, Item Analysis, Error of Measurement
Monahan, Patrick O.; Ankenmann, Robert D. – Applied Psychological Measurement, 2010
When the matching score is either less than perfectly reliable or not a sufficient statistic for determining latent proficiency in data conforming to item response theory (IRT) models, Type I error (TIE) inflation may occur for the Mantel-Haenszel (MH) procedure or any differential item functioning (DIF) procedure that matches on summed-item…
Descriptors: Error of Measurement, Item Response Theory, Test Bias, Scores
Sueiro, Manuel J.; Abad, Francisco J. – Educational and Psychological Measurement, 2011
The distance between nonparametric and parametric item characteristic curves has been proposed as an index of goodness of fit in item response theory in the form of a root integrated squared error index. This article proposes to use the posterior distribution of the latent trait as the nonparametric model and compares the performance of an index…
Descriptors: Goodness of Fit, Item Response Theory, Nonparametric Statistics, Probability
Liang, Tie; Wells, Craig S. – Educational and Psychological Measurement, 2009
Investigating the fit of a parametric model is an important part of the measurement process when implementing item response theory (IRT), but research examining it is limited. A general nonparametric approach for detecting model misfit, introduced by J. Douglas and A. S. Cohen (2001), has exhibited promising results for the two-parameter logistic…
Descriptors: Sample Size, Nonparametric Statistics, Item Response Theory, Goodness of Fit
Emons, Wilco H. M. – Applied Psychological Measurement, 2008
Person-fit methods are used to uncover atypical test performance as reflected in the pattern of scores on individual items in a test. Unlike parametric person-fit statistics, nonparametric person-fit statistics do not require fitting a parametric test theory model. This study investigates the effectiveness of generalizations of nonparametric…
Descriptors: Simulation, Nonparametric Statistics, Item Response Theory, Goodness of Fit
Mapuranga, Raymond; Dorans, Neil J.; Middleton, Kyndra – ETS Research Report Series, 2008
In many practical settings, essentially the same differential item functioning (DIF) procedures have been in use since the late 1980s. Since then, examinee populations have become more heterogeneous, and tests have included more polytomously scored items. This paper summarizes and classifies new DIF methods and procedures that have appeared since…
Descriptors: Test Bias, Educational Development, Evaluation Methods, Statistical Analysis
Roussos, Louis A.; Ozbek, Ozlem Yesim – Journal of Educational Measurement, 2006
The development of the DETECT procedure marked an important advancement in nonparametric dimensionality analysis. DETECT is the first nonparametric technique to estimate the number of dimensions in a data set, estimate an effect size for multidimensionality, and identify which dimension is predominantly measured by each item. The efficacy of…
Descriptors: Evaluation Methods, Effect Size, Test Bias, Item Response Theory