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1.
Linking item parameters to a base scale 总被引：1，自引：0，他引：1
This paper compares three methods of item calibration??concurrent calibration, separate calibration with linking, and fixed item parameter calibration??that are frequently used for linking item parameters to a base scale. Concurrent and separate calibrations were implemented using BILOG-MG. The Stocking and Lord in Appl Psychol Measure 7:201?C210, (1983) characteristic curve method of parameter linking was used in conjunction with separate calibration. The fixed item parameter calibration (FIPC) method was implemented using both BILOG-MG and PARSCALE because the method is carried out differently by the two programs. Both programs use multiple EM cycles, but BILOG-MG does not update the prior ability distribution during FIPC calibration, whereas PARSCALE updates the prior ability distribution multiple times. The methods were compared using simulations based on actual testing program data, and results were evaluated in terms of recovery of the underlying ability distributions, the item characteristic curves, and the test characteristic curves. Factors manipulated in the simulations were sample size, ability distributions, and numbers of common (or fixed) items. The results for concurrent calibration and separate calibration with linking were comparable, and both methods showed good recovery results for all conditions. Between the two fixed item parameter calibration procedures, only the appropriate use of PARSCALE consistently provided item parameter linking results similar to those of the other two methods. 相似文献
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Increasing use of item pools in large-scale educational assessments calls for an appropriate scaling procedure to achieve a common metric among field-tested items. The present study examines scaling procedures for developing a new item pool under a spiraled block linking design. The three scaling procedures are considered: (a) concurrent calibration, (b) separate calibration with one linking, and (c) separate calibration with three sequential linking. Evaluation across varying sample sizes and item pool sizes suggests that calibrating an item pool simultaneously results in the most stable scaling. The separate calibration with linking procedures produced larger scaling errors as the number of linking steps increased. The Haebara’s item characteristic curve linking resulted in better performances than the test characteristic curve (TCC) linking method. The present article provides an analytic illustration that the test characteristic curve method may fail to find global solutions in polytomous items. Finally, comparison of the single- and mixed-format item pools suggests that the use of polytomous items as the anchor can improve the overall scaling accuracy of the item pools. 相似文献
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Eiji Muraki 《Journal of Educational Measurement》1999,36(3):217-232
Bock, Muraki, and Pfeiffenberger (1988) proposed a dichotomous item response theory (IRT) model for the detection of differential item functioning (DIF), and they estimated the IRT parameters and the means and standard deviations of the multiple latent trait distributions. This IRT DIF detection method is extended to the partial credit model (Masters, 1982; Muraki, 1993) and presented as one of the multiple-group IRT models. Uniform and non-uniform DIF items and heterogeneous latent trait distributions were used to generate polytomous responses of multiple groups. The DIF method was applied to this simulated data using a stepwise procedure. The standardized DIF measures for slope and item location parameters successfully detected the non-uniform and uniform DIF items as well as recovered the means and standard deviations of the latent trait distributions.This stepwise DIF analysis based on the multiple-group partial credit model was then applied to the National Assessment of Educational Progress (NAEP) writing trend data. 相似文献
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《教育实用测度》2013,26(2):199-210
When the item response theory (IRT) model uses the marginal maximum likelihood estimation, person parameters are usually treated as random parameters following a certain distribution as a prior distribution to estimate the structural parameters in the model. For example, both PARSCALE (Muraki &; Bock, 1999) and BILOG 3 (Mislevy &; Bock, 1990) use a standard normal distribution as a default person prior. When the fixed-item linking method is used with an IRT program having a fixed-person prior distribution, it biases person ability growth downward or upward depending on the direction of the growth due to the misspecification of the prior. This study demonstrated by simulation how much biasing impact there is on person ability growth from the use of the fixed prior distribution in fixed-item linking for mixed-format test data. In addition, the study demonstrated how to recover growth through an iterative prior update calibration procedure. This shows that fixed-item linking is still a viable linking method for a fixed-person prior IRT calibration. 相似文献
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Matthias von Davier Kentaro Yamamoto Hyo Jeong Shin Henry Chen Lale Khorramdel Jon Weeks 《Assessment in Education: Principles, Policy & Practice》2019,26(4):466-488
ABSTRACTBased on concerns about the item response theory (IRT) linking approach used in the Programme for International Student Assessment (PISA) until 2012 as well as the desire to include new, more complex, interactive items with the introduction of computer-based assessments, alternative IRT linking methods were implemented in the 2015 PISA round. The new linking method represents a concurrent calibration using all available data, enabling us to find item parameters that maximize fit across all groups and allowing us to investigate measurement invariance across groups. Apart from the Rasch model that historically has been used in PISA operational analyses, we compared our method against more general IRT models that can incorporate item-by-country interactions. The results suggest that our proposed method holds promise not only to provide a strong linkage across countries and cycles but also to serve as a tool for investigating measurement invariance. 相似文献
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When cut scores for classifications occur on the total score scale, popular methods for estimating classification accuracy (CA) and classification consistency (CC) require assumptions about a parametric form of the test scores or about a parametric response model, such as item response theory (IRT). This article develops an approach to estimate CA and CC nonparametrically by replacing the role of the parametric IRT model in Lee's classification indices with a modified version of Ramsay's kernel‐smoothed item response functions. The performance of the nonparametric CA and CC indices are tested in simulation studies in various conditions with different generating IRT models, test lengths, and ability distributions. The nonparametric approach to CA often outperforms Lee's method and Livingston and Lewis's method, showing robustness to nonnormality in the simulated ability. The nonparametric CC index performs similarly to Lee's method and outperforms Livingston and Lewis's method when the ability distributions are nonnormal. 相似文献
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Various applications of item response theory often require linking to achieve a common scale for item parameter estimates obtained from different groups. This article used a simulation to examine the relative performance of four different item response theory (IRT) linking procedures in a random groups equating design: concurrent calibration with multiple groups, separate calibration with the Stocking-Lord method, separate calibration with the Haebara method, and proficiency transformation. The simulation conditions used in this article included three sampling designs, two levels of sample size, and two levels of the number of items. In general, the separate calibration procedures performed better than the concurrent calibration and proficiency transformation procedures, even though some inconsistent results were observed across different simulation conditions. Some advantages and disadvantages of the linking procedures are discussed. 相似文献
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Calibration and equating is the quintessential necessity for most large‐scale educational assessments. However, there are instances when no consideration is given to the equating process in terms of context and substantive realization, and the methods used in its execution. In the view of the authors, equating is not merely an exhibit of the statistical methodology, but it is also a reflection of the thought process undertaken in its execution. For example, there is hardly any discussion in literature of the ideological differences in the selection of an equating method. Furthermore, there is little evidence of modeling cohort growth through an identification and use of construct‐relevant linking items’ drift, using the common item nonequivalent group equating design. In this article, the authors philosophically justify the use of Huynh's statistical method for the identification of construct‐relevant outliers in the linking pool. The article also dispels the perception of scale instability associated with the inclusion of construct‐relevant outliers in the linking item pool and concludes that an appreciation of the rationale used in the selection of the equating method, together with the use of linking items in modeling cohort growth, can be beneficial to the practitioners. 相似文献
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Tihomir Asparouhov 《Structural equation modeling》2013,20(4):495-508
This article presents a new method for multiple-group confirmatory factor analysis (CFA), referred to as the alignment method. The alignment method can be used to estimate group-specific factor means and variances without requiring exact measurement invariance. A strength of the method is the ability to conveniently estimate models for many groups. The method is a valuable alternative to the currently used multiple-group CFA methods for studying measurement invariance that require multiple manual model adjustments guided by modification indexes. Multiple-group CFA is not practical with many groups due to poor model fit of the scalar model and too many large modification indexes. In contrast, the alignment method is based on the configural model and essentially automates and greatly simplifies measurement invariance analysis. The method also provides a detailed account of parameter invariance for every model parameter in every group. 相似文献
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Kyung-Seok Min 《Asia Pacific Education Review》2007,8(1):41-55
Most researchers agree that psychological/educational tests are sensitive to multiple traits, implying the need for a multidimensional
item response theory (MIRT). One limitation of applying a MIRT in practice is the difficulty in establishing equivalent scales
of multiple traits. In this study, a new MIRT linking method was proposed and evaluated by comparison with two existing methods.
The results showed that the new method was more acceptable in transforming item parameters and maintaining dimensional structures.
Limitations and cautions in using multidimensional linking techniques were also discussed. 相似文献
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T. C. Oshima Nambury S. Raju Claudia P. Flowers 《Journal of Educational Measurement》1997,34(3):253-272
This article defines and demonstrates a framework for studying differential item functioning (DIF) and differential test functioning (DTF) for tests that are intended to be multidimensional The procedure introduced here is an extension of unidimensional differential functioning of items and tests (DFIT) recently developed by Raju, van der Linden, & Fleer (1995). To demonstrate the usefulness of these new indexes in a multidimensional IRT setting, two-dimensional data were simulated with known item parameters and known DIF and DTE The DIF and DTF indexes were recovered reasonably well under various distributional differences of Os after multidimensional linking was applied to put the two sets of item parameters on a common scale. Further studies are suggested in the area of DIF/DTF for intentionally multidimensional tests. 相似文献
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Kyung T. Han 《Journal of Educational Measurement》2012,49(3):225-246
Successful administration of computerized adaptive testing (CAT) programs in educational settings requires that test security and item exposure control issues be taken seriously. Developing an item selection algorithm that strikes the right balance between test precision and level of item pool utilization is the key to successful implementation and long‐term quality control of CAT. This study proposed a new item selection method using the “efficiency balanced information” criterion to address issues with the maximum Fisher information method and stratification methods. According to the simulation results, the new efficiency balanced information method had desirable advantages over the other studied item selection methods in terms of improving the optimality of CAT assembly and utilizing items with low a‐values while eliminating the need for item pool stratification. 相似文献
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An important assumption of item response theory is item parameter invariance. Sometimes, however, item parameters are not invariant across different test administrations due to factors other than sampling error; this phenomenon is termed item parameter drift. Several methods have been developed to detect drifted items. However, most of the existing methods were designed to detect drifts in individual items, which may not be adequate for test characteristic curve–based linking or equating. One example is the item response theory–based true score equating, whose goal is to generate a conversion table to relate number‐correct scores on two forms based on their test characteristic curves. This article introduces a stepwise test characteristic curve method to detect item parameter drift iteratively based on test characteristic curves without needing to set any predetermined critical values. Comparisons are made between the proposed method and two existing methods under the three‐parameter logistic item response model through simulation and real data analysis. Results show that the proposed method produces a small difference in test characteristic curves between administrations, an accurate conversion table, and a good classification of drifted and nondrifted items and at the same time keeps a large amount of linking items. 相似文献
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This article addresses the issue of how to detect item preknowledge using item response time data in two computer‐based large‐scale licensure examinations. Item preknowledge is indicated by an unexpected short response time and a correct response. Two samples were used for detecting item preknowledge for each examination. The first sample was from the early stage of the operational test and was used for item calibration. The second sample was from the late stage of the operational test, which may feature item preknowledge. The purpose of this research was to explore whether there was evidence of item preknowledge and compromised items in the second sample using the parameters estimated from the first sample. The results showed that for one nonadaptive operational examination, two items (of 111) were potentially exposed, and two candidates (of 1,172) showed some indications of preknowledge on multiple items. For another licensure examination that featured computerized adaptive testing, there was no indication of item preknowledge or compromised items. Implications for detected aberrant examinees and compromised items are discussed in the article. 相似文献
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《Structural equation modeling》2013,20(1):59-72
A non-arbitrary method for the identification and scale setting of latent variables in general structural equation modeling is introduced. This particular technique provides identical model fit as traditional methods (e.g., the marker variable method), but it allows one to estimate the latent parameters in a nonarbitrary metric that reflects the metric of the measured indicators. This technique, therefore, is particularly useful for mean and covariance structures (MACS) analyses, where the means of the indicators and latent constructs are of key interest. By introducing this alternative method of identification and scale setting, researchers are provided with an additional tool for conducting MACS analyses that provides a meaningful and nonarbitrary scale for the estimates of the latent variable parameters. Importantly, this tool can be used with single-group single-occasion models as well as with multiple-group models, multiple-occasion models, or both. 相似文献
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A key consideration when giving any computerized adaptive test (CAT) is how much adaptation is present when the test is used in practice. This study introduces a new framework to measure the amount of adaptation of Rasch‐based CATs based on looking at the differences between the selected item locations (Rasch item difficulty parameters) of the administered items and target item locations determined from provisional ability estimates at the start of each item. Several new indices based on this framework are introduced and compared to previously suggested measures of adaptation using simulated and real test data. Results from the simulation indicate that some previously suggested indices are not as sensitive to changes in item pool size and the use of constraints as the new indices and may not work as well under different item selection rules. The simulation study and real data example also illustrate the utility of using the new indices to measure adaptation at both a group and individual level. Discussion is provided on how one may use several of the indices to measure adaptation of Rasch‐based CATs in practice. 相似文献