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Comparison Of Parametric And Nonparametric Irt Equating Methods Under The Common Item Nonequivalent Groups Design
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Book Synopsis Comparison of Parametric and Nonparametric IRT Equating Methods Under the Common-item Nonequivalent Groups Design by : Yuki Nozawa
Download or read book Comparison of Parametric and Nonparametric IRT Equating Methods Under the Common-item Nonequivalent Groups Design written by Yuki Nozawa and published by . This book was released on 2008 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Comparison of Four Linear Equating Methods for the Common-Item Nonequivalent Groups Design Using Simulation Methods. ACT Research Report Series, 2013 (2) by : Anna Topczewski
Download or read book A Comparison of Four Linear Equating Methods for the Common-Item Nonequivalent Groups Design Using Simulation Methods. ACT Research Report Series, 2013 (2) written by Anna Topczewski and published by . This book was released on 2013 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper investigates four methods of linear equating under the common item nonequivalent groups design. Three of the methods are well known: Tucker, Angoff-Levine, and Congeneric-Levine. A fourth method is presented as a variant of the Congeneric-Levine method. Using simulation data generated from the three-parameter logistic IRT model we compare the accuracy of the four methods under a variety of conditions involving group differences between the old and new groups. The sampling properties of the methods' parameter estimates are also investigated. The results indicate that the Tucker method is less accurate than the other three methods when group differences exist, especially when sample size is large (800). However, the Tucker method's gamma has the smallest sampling error, especially when sample size is small. Appended are: (1) Tables A1-A8; and (2) Figures B-1 through B-7.
Book Synopsis A Comparison of Bootstrap Standard Errors of IRT Equating Methods for the Common Item Nonequivalent Groups Design by : Tsung-Hsun Tsai
Download or read book A Comparison of Bootstrap Standard Errors of IRT Equating Methods for the Common Item Nonequivalent Groups Design written by Tsung-Hsun Tsai and published by . This book was released on 1998 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Comparison of IRT Linking Approaches Under the Nonequivalent Groups Anchor Test Design by : Jiajing Huang
Download or read book A Comparison of IRT Linking Approaches Under the Nonequivalent Groups Anchor Test Design written by Jiajing Huang and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The nonequivalent-groups anchor-test (NEAT) data-collection design is commonly used in large-scale assessments. Under this design, different test groups take different test forms. Each test form has its own unique items and all test forms share a set of common items. If item response theory (IRT) models are applied to analyze the test data, the estimates of item parameters in different test forms and ability scores of different test groups may not be on the same scale because of the IRT property of scale indeterminacy. To compare the items in different forms and examinees in different test groups, a statistical procedure, linking, is needed to convert the item parameters and ability scores to a common scale. There are several IRT linking approaches under the NEAT design. Some of the approaches make use of the common (anchor) items shared by test forms and are referred to as common-item linking approaches. The often used common-item linking approaches under the NEAT design include concurrent calibration, separate calibration with moments-linking approaches (e.g., mean/mean and mean/sigma), and characteristic-curve linking approaches (e.g., Haebara approach and Stocking-Lord approach). All common-item linking approaches hold the same key assumption - that common items perform in the same way across different test forms, which means the common-item parameters are assumed to be invariant. When the common-item parameters are non-invariant, the results of common-item linking might be affected. The other type of linking approach studied in this dissertation, common-population linking, does not assume the invariance of common items. This linking approach makes use of one group's ability distributions derived from different calibration runs to do linking, and assumes that the ability distributions of different test groups are the same in one of the steps involved. Under the NEAT design, the test groups possibly come from different populations, which means the equivalence assumption for group ability distributions might be violated. Violation of this assumption might threaten the accuracy of common-population linking results. Many studies have compared the performance of several popular common-item linking approaches under a variety of conditions. However, no study has compared the common-population linking approach with common-item linking approaches under the NEAT design. This study aimed to compare the performance of common-population linking and common-item linking approaches (specifically, concurrent calibration and separate calibration with Stocking-Lord linking approach) under some simulated conditions. The design factors included differences in ability distributions, parameter drift for some anchor (common) items, sample size, test length, and the numbers of anchor items. The simulated study findings showed that no one approach always outperformed the other two approaches across all conditions in the scenario that the scores of the focal group (taking the new form) were linked to the scale of the reference group (taking the old form). Generally, the type of parameter drift for anchor items impacted the performance of the Stocking-Lord and the concurrent calibration approaches, but even under conditions of drift, these two approaches still performed well. The concurrent calibration was more sensitive to sample size and the number of anchor items than the Stocking-Lord approach. For the common-population approach, when the ability distribution of the focal group had same mean and standard deviation as the reference group, this approach sometimes performed equally well or slightly better than the other two approaches. Once the two groups had different means and standard deviations, its performance was poor. In addition to a simulation study, empirical data from the Florida Standards Assessments (FSA) were used to demonstrate the applications of these approaches in a practical test setting. Florida Department of Education (FLDOE) applies separate calibrations with the Stocking-Lord linking approach. In this empirical study, concurrent calibration with nonequivalent groups and a common-population linking approach were applied and were compared with the original results generated from the FLDOE's separate calibration with Stocking-Lord linking. Results showed that the scale scores from the concurrent calibration and the common-population linking correlated strongly with the original FSA scale scores. The linked item parameters from the two linking approaches were also similar to the corresponding ones on the FSA scale. In conclusion, when some anchor items had parameter drift and the two test groups had different ability distributions, the Stocking-Lord approach generally performed the best; the common-population approach performed the worst in the majority of simulated conditions except when its underlying assumption of equal ability distributions across groups was not violated.
Book Synopsis Equating Using Unidimensional Dichotomous and Polytomous IRT Models for Testlet-based Tests Under Common-item Nonequivalent Groups Design by : Lidong Zhang
Download or read book Equating Using Unidimensional Dichotomous and Polytomous IRT Models for Testlet-based Tests Under Common-item Nonequivalent Groups Design written by Lidong Zhang and published by . This book was released on 2013 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: The relative equating performance of the Graded Response Model (GRM) and the Generalized Partial Credit (GPC) model was compared with that of the two parameter logistic (2PL) model using simulated testlet data under a common-item nonequivalent groups design. Impacts of various levels of testlet effects, calibration procedures, group differences, number of common items, sample size were investigated. Three traditional linear equating methods were used as criteria for the IRT true score equating and IRT observed score equating results from the three item response theory models. In general, the equating performance based on the two polytomous models yielded results that were more compatible with the results of the traditional equating methods with the presence of testlet effects. Even in some conditions without testlet effects, the equating performance of the two polytomous models was more similar to that of the traditional methods than the dichotomous 2PL model, particularly when the number of common items was larger. Of the two polytomous models, the GRM was found to render results in more agreement with those of traditional linear methods in conditions of separate calibration with linking. The characteristic curve linking methods outperformed the moment methods in a majority of conditions. The separate calibration procedures were better than the concurrent calibration procedure in most of the conditions, especially when the number of common items was small.
Book Synopsis A Comparison of Four Linear Equating Methods for the Common-item Nonequivalent Groups Design Using Simulation Methods by : Anna Topczewski
Download or read book A Comparison of Four Linear Equating Methods for the Common-item Nonequivalent Groups Design Using Simulation Methods written by Anna Topczewski and published by . This book was released on 2013 with total page 39 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Comparison of the Common-Item and Random-Groups Equating Designs Using Empirical Data by : Dong-In Kim
Download or read book A Comparison of the Common-Item and Random-Groups Equating Designs Using Empirical Data written by Dong-In Kim and published by . This book was released on 2008 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We designed this study to evaluate several data collection and equating designs in the context of item response theory (IRT) equating. The random-groups design and the common-item design have been widely used for collecting data for IRT equating. In this study, we investigated four equating methods based upon these two data collection designs, using empirical data from a number of different testing programs. When the randomly equivalent group assumption was reasonably met, the four equating methods tended to produce highly comparable results. On the other hand, equating methods based upon either of the equating designs produced dissimilar results. Sample size can have differential effects on the equating results produced by the different equating methods. In practice, a common-item equivalent-groups design often produces unacceptably large differences in the group mean due to various anomalies such as context effects, poor quality of common items, or a very small number of common items. In such cases, a random-groups design would produce more stable equating results.
Book Synopsis Comparison of Bootstrap Standard Errors of Equating Using IRT and Equipercentile Methods with Polytomously-scored Items Under the Common-item Nonequivalent-groups Design by : YoungWoo Cho
Download or read book Comparison of Bootstrap Standard Errors of Equating Using IRT and Equipercentile Methods with Polytomously-scored Items Under the Common-item Nonequivalent-groups Design written by YoungWoo Cho and published by . This book was released on 2007 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Comparison of Kernel Equating and IRT True Score Equating Methods by :
Download or read book A Comparison of Kernel Equating and IRT True Score Equating Methods written by and published by . This book was released on 2007 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This two-part study investigates 1) the impact of loglinear model selection in pre-smoothing observed score distributions on the kernel method of test equating and 2) the differences between kernel equating, chained equipercentile equating, and true score methods of concurrent calibration and Stocking and Lord's transformation method. Data were simulated to emulate realistic situations in which test difficulty differed, sample sizes varied, anchor test lengths were of varying lengths, and test lengths ranged from 20 items to 100 items. Difficulty of anchor tests were held constant. Because data were simulated in a single group (SG) format, traditional unsmoothed equipercentile equating was used as a criterion by which all other methods, which use the non-equivalent groups with an anchor test design (NEAT), were compared. Data were simulated using IceDog (ETS, 2007) and analyzed using KE software (ETS, 2007), MULTILOG (Thissen, 2003), IceDog (ETS, 2007), PARSCALE (Muraki & Bock, 2003) and Fortran programming code developed by the author. Results indicate the impact of equating technique chosen on examinees' test scores in a variety of realistic situations, and have further recommendations for further study."--Abstract from author supplied metadata.
Book Synopsis Robust Scale Transformation Methods in IRT True Score Equating Under Common-item Nonequivalent Groups Design by : Yong He
Download or read book Robust Scale Transformation Methods in IRT True Score Equating Under Common-item Nonequivalent Groups Design written by Yong He and published by . This book was released on 2013 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: Common test items play an important role in equating multiple test forms under the common-item nonequivalent groups design. Inconsistent item parameter estimates among common items can lead to large bias in equated scores for IRT true score equating. Current methods extensively focus on detection and elimination of outlying common items, which usually leads to enlarged random equating error and inadequate content representation of common items. New robust scale transformation methods based on robust regression, the robust Deming regression method, the robust Haebara method, and the least absolute values (LAV) method, were proposed. In simulation studies, performances of the proposed methods were compared to the Stocking-Lord method which yields the least equating errors among the traditional method and to outlier removal methods. The results indicate: 1) the robust Haebara method and the LAV method usually outperform the robust Deming regression method, 2) the robust Haebara method and the LAV method perform as well as the Stocking Lord method under the condition of No outlier, 3) the robust Haebara method and the LAV method perform better than the Stocking-Lord method when a single outlying common item is simulated, 4) the LAV method and the robust Haebara method are better than, or at least comparable to, the existing outlier removal methods in the presence of a single outlying common item, and 5) the LAV method and the robust Haebara method have smaller equated scores than the Stocking-Lord method using the CBASE data of English and Mathematics.
Book Synopsis Test Equating, Scaling, and Linking by : Michael J. Kolen
Download or read book Test Equating, Scaling, and Linking written by Michael J. Kolen and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt: By providing an introduction to test equating which both discusses the most frequently used equating methodologies and covering many of the practical issues involved, this volume expands upon the coverage of the first edition by providing a new chapter on test scaling and a second on test linking.
Book Synopsis Statistical Models for Test Equating, Scaling, and Linking by : Alina von Davier
Download or read book Statistical Models for Test Equating, Scaling, and Linking written by Alina von Davier and published by Springer Science & Business Media. This book was released on 2010-10-19 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of this book is to emphasize the formal statistical features of the practice of equating, linking, and scaling. The book encourages the view and discusses the quality of the equating results from the statistical perspective (new models, robustness, fit, testing hypotheses, statistical monitoring) as opposed to placing the focus on the policy and the implications, which although very important, represent a different side of the equating practice. The book contributes to establishing “equating” as a theoretical field, a view that has not been offered often before. The tradition in the practice of equating has been to present the knowledge and skills needed as a craft, which implies that only with years of experience under the guidance of a knowledgeable practitioner could one acquire the required skills. This book challenges this view by indicating how a good equating framework, a sound understanding of the assumptions that underlie the psychometric models, and the use of statistical tests and statistical process control tools can help the practitioner navigate the difficult decisions in choosing the final equating function. This book provides a valuable reference for several groups: (a) statisticians and psychometricians interested in the theory behind equating methods, in the use of model-based statistical methods for data smoothing, and in the evaluation of the equating results in applied work; (b) practitioners who need to equate tests, including those with these responsibilities in testing companies, state testing agencies, and school districts; and (c) instructors in psychometric, measurement, and psychology programs.
Book Synopsis Effects of Outlier Item Parameters on IRT Characteristic Curve Linking Methods Under the Common-item Nonequivalent Groups Design by : Francisco Andres Jimenez
Download or read book Effects of Outlier Item Parameters on IRT Characteristic Curve Linking Methods Under the Common-item Nonequivalent Groups Design written by Francisco Andres Jimenez and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: ABSTRACT: The comparability of test scores on alternate forms of a test has become a matter of considerable importance for test developers and users. This study used a Monte Carlo simulation to investigate the effects of common items with outlier b- and aparameter estimates on the Stocking-Lord (Stocking & Lord, 1983) and Haebara (Haebara, 1980) IRT characteristic curve linking methods under the common-item nonequivalent groups design. The simulation conditions examined in this study included different levels of ability distribution, types of outliers, and number of outliers. Results indicated that neither method seemed to be robust to the presence of common items with outlier b-parameter or items with an interaction of outlier b- and a-parameters, although the Haebara method tended to perform better than the Stocking-Lord method when there were outlier common items with extreme a-parameter.
Book Synopsis Comparison of Item Preequating and Random Groups Equating Using IRT and Equipercentile Methods by : Michael J. Kolen
Download or read book Comparison of Item Preequating and Random Groups Equating Using IRT and Equipercentile Methods written by Michael J. Kolen and published by . This book was released on 1988 with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The Missing Data Assumptions of the Nonequivalent Groups with Anchor Test (NEAT) Design and Their Implications for Test Equating. Research Report. ETS RR-09-16 by : S. Sinharay
Download or read book The Missing Data Assumptions of the Nonequivalent Groups with Anchor Test (NEAT) Design and Their Implications for Test Equating. Research Report. ETS RR-09-16 written by S. Sinharay and published by . This book was released on 2008 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt: The nonequivalent groups with anchor test (NEAT) design involves missing data that are missing by design. Three popular equating methods that can be used with a NEAT design are the poststratification equating method, the chain equipercentile equating method, and the item-response-theory observed-score-equating method. These three methods each make different assumptions about the missing data in the NEAT design. Though studies have compared the equating performance of the three methods under the NEAT design, none has examined the missing data assumptions and their implications for such comparisons. The missing data assumptions can affect equating studies because it is necessary to fill in the missing data or their distribution in some way in order to have a true, or criterion, equating function to compare the accuracy and bias of the different methods. If the missing data or their distribution are filled in using missing data assumptions that correspond to a given method, that may favor that method in any comparison with the others. This paper first describes the missing data assumptions of the three equating methods and then performs a fair comparison of the 3 methods using data from 3 different operational tests. For each data set, we examine how the 3 equating methods perform when the missing data satisfy the assumptions made by only 1 of these equating methods. The chain equating method is somewhat more satisfactory overall than the other methods in our fair comparison of the methods; hence, we recommend that equating practitioners seriously consider the chain equating method when using the NEAT design. In addition, we conclude that the results from the different equating methods will tend to agree with each other when proper equating conditions are in place. Moreover, to uncover problems that might not reveal themselves otherwise, it is important for operational testing programs to apply multiple equating methods and study the differences among their results. Appendices include: (1) Raking; and (2) Proof of Theorem 1. (Contains 15 tables, 7 figures, and 4 notes.).
Book Synopsis Dissertation Abstracts International by :
Download or read book Dissertation Abstracts International written by and published by . This book was released on 2009-08 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Generalized Kernel Equating with Applications in R by : Marie Wiberg
Download or read book Generalized Kernel Equating with Applications in R written by Marie Wiberg and published by CRC Press. This book was released on 2024-11-01 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generalized Kernel Equating is a comprehensive guide for statisticians, psychometricians, and educational researchers aiming to master test score equating. This book introduces the Generalized Kernel Equating (GKE) framework, providing the necessary tools and methodologies for accurate and fair score comparisons. The book presents test score equating as a statistical problem and covers all commonly used data collection designs. It details the five steps of the GKE framework: presmoothing, estimating score probabilities, continuization, equating transformation, and evaluating the equating transformation. Various presmoothing strategies are explored, including log-linear models, item response theory models, beta4 models, and discrete kernel estimators. The estimation of score probabilities when using IRT models is described and Gaussian kernel continuization is extended to other kernels such as uniform, logistic, epanechnikov and adaptive kernels. Several bandwidth selection methods are described. The kernel equating transformation and variants of it are defined, and both equating-specific and statistical measures for evaluating equating transformations are included. Real data examples, guiding readers through the GKE steps with detailed R code and explanations are provided. Readers are equipped with an advanced knowledge and practical skills for implementing test score equating methods.
