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1.
This study investigates the comparability of two item response theory based equating methods: true score equating (TSE), and estimated true equating (ETE). Additionally, six scaling methods were implemented within each equating method: mean-sigma, mean-mean, two versions of fixed common item parameter, Stocking and Lord, and Haebara. Empirical test data were examined to investigate the consistency of scores resulting from the two equating methods, as well as the consistency of the scaling methods both within equating methods and across equating methods. Results indicate that although the degree of correlation among the equated scores was quite high, regardless of equating method/scaling method combination, non-trivial differences in equated scores existed in several cases. These differences would likely accumulate across examinees making group-level differences greater. Systematic differences in the classification of examinees into performance categories were observed across the various conditions: ETE tended to place lower ability examinees into higher performance categories than TSE, while the opposite was observed for high ability examinees. Because the study was based on one set of operational data, the generalizability of the findings is limited and further study is warranted.  相似文献   

2.
Equating test forms is an essential activity in standardized testing, with increased importance with the accountability systems in existence through the mandate of Adequate Yearly Progress. It is through equating that scores from different test forms become comparable, which allows for the tracking of changes in the performance of students from one year to the next. This study compares three different item response theory scaling methods (fixed common item parameter, Stocking & Lord, and Concurrent Calibration) with respect to examinee classification into performance categories, and estimation of the ability parameter, when the content of the test form changes slightly from year to year, and the examinee ability distribution changes. The results indicate that calibration methods, especially concurrent calibration, produced more stable results than the transformation method.  相似文献   

3.
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   

4.
Reading and Mathematics tests of multiple-choice items for grades Kindergarten through 9 were vertically scaled using the three-parameter logistic model and two different scaling procedures: concurrent and separate by grade groups. Item parameters were estimated using Markov chain Monte Carlo methodology while fixing the grade 4 population abilities to have a standard normal distribution. For the separate grade-groups scaling, grade groupings were linked using the Stocking and Lord test characteristic curve procedure. Abilities were estimated using the maximum-likelihood method. In either content area, scatterplots of item difficulty, discrimination, and ability estimates from the two methods showed consistently strong linear relationships. However, as grade deviated from the base grade of four, the best-fit linear line through the pairs of item discriminations started to rotate away from the identity line. This indicated the discrimination estimates from the separate grade-groups procedure for extreme grades to be, on average, higher than those from the concurrent analysis. The study also observed some systematic change in score variability across grades. In general, the two vertical scaling approaches yielded similar results at more grades in Reading than in Mathematics.  相似文献   

5.
In order to equate tests under Item Response Theory (IRT), one must obtain the slope and intercept coefficients of the appropriate linear transformation. This article compares two methods for computing such equating coefficients–Loyd and Hoover (1980) and Stocking and Lord (1983). The former is based upon summary statistics of the test calibrations; the latter is based upon matching test characteristic curves by minimizing a quadratic loss function. Three types of equating situations: horizontal, vertical, and that inherent in IRT parameter recovery studies–were investigated. The results showed that the two computing procedures generally yielded similar equating coefficients in all three situations. In addition, two sets of SAT data were equated via the two procedures, and little difference in the obtained results was observed. Overall, the results suggest that the Loyd and Hoover procedure usually yields acceptable equating coefficients. The Stocking and Lord procedure improves upon the Loyd and Hoover values and appears to be less sensitive to atypical test characteristics. When the user has reason to suspect that the test calibrations may be associated with data sets that are typically troublesome to calibrate, the Stocking and Lord procedure is to be preferred.  相似文献   

6.
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   

7.
Preequating is in demand because it reduces score reporting time. In this article, we evaluated an observed‐score preequating method: the empirical item characteristic curve (EICC) method, which makes preequating without item response theory (IRT) possible. EICC preequating results were compared with a criterion equating and with IRT true‐score preequating conversions. Results suggested that the EICC preequating method worked well under the conditions considered in this study. The difference between the EICC preequating conversion and the criterion equating was smaller than .5 raw‐score points (a practical criterion often used to evaluate equating quality) between the 5th and 95th percentiles of the new form total score distribution. EICC preequating also performed similarly or slightly better than IRT true‐score preequating.  相似文献   

8.
With known item response theory (IRT) item parameters, Lord and Wingersky provided a recursive algorithm for computing the conditional frequency distribution of number‐correct test scores, given proficiency. This article presents a generalized algorithm for computing the conditional distribution of summed test scores involving real‐number item scores. The generalized algorithm is distinct from the Lord‐Wingersky algorithm in that it explicitly incorporates the task of figuring out all possible unique real‐number test scores in each recursion. Some applications of the generalized recursive algorithm, such as IRT test score reliability estimation and IRT proficiency estimation based on summed test scores, are illustrated with a short test by varying scoring schemes for its items.  相似文献   

9.
《教育实用测度》2013,26(4):383-407
The performance of the item response theory (IRT) true-score equating method is examined under conditions of test multidimensionality. It is argued that a primary concern in applying unidimensional equating methods when multidimensionality is present is the potential decrease in equity (Lord, 1980) attributable to the fact that examinees of different ability are expected to obtain the same test scores. In contrast to equating studies based on real test data, the use of simulation in equating research not only permits assessment of these effects but also enables investigation of hypothetical equating conditions in which multidimensionality can be suspected to be especially problematic for test equating. In this article, I investigate whether the IRT true-score equating method, which explicitly assumes the item response matrix is unidimensional, is more adversely affected by the presence of multidimensionality than 2 conventional equating methods-linear and equipercentile equating-using several recently proposed equity-based criteria (Thomasson, 1993). Results from 2 simulation studies suggest that the IRT method performs at least as well as the conventional methods when the correlation between dimensions is high (³ 0.7) and may be only slightly inferior to the equipercentile method when the correlation is moderate to low (£ 0.5).  相似文献   

10.
Trend estimation in international comparative large‐scale assessments relies on measurement invariance between countries. However, cross‐national differential item functioning (DIF) has been repeatedly documented. We ran a simulation study using national item parameters, which required trends to be computed separately for each country, to compare trend estimation performances to two linking methods employing international item parameters across several conditions. The trend estimates based on the national item parameters were more accurate than the trend estimates based on the international item parameters when cross‐national DIF was present. Moreover, the use of fixed common item parameter calibrations led to biased trend estimates. The detection and elimination of DIF can reduce this bias but is also likely to increase the total error.  相似文献   

11.
This study demonstrated the equivalence between the Rasch testlet model and the three‐level one‐parameter testlet model and explored the Markov Chain Monte Carlo (MCMC) method for model parameter estimation in WINBUGS. The estimation accuracy from the MCMC method was compared with those from the marginalized maximum likelihood estimation (MMLE) with the expectation‐maximization algorithm in ConQuest and the sixth‐order Laplace approximation estimation in HLM6. The results indicated that the estimation methods had significant effects on the bias of the testlet variance and ability variance estimation, the random error in the ability parameter estimation, and the bias in the item difficulty parameter estimation. The Laplace method best recovered the testlet variance while the MMLE best recovered the ability variance. The Laplace method resulted in the smallest random error in the ability parameter estimation while the MCMC method produced the smallest bias in item parameter estimates. Analyses of three real tests generally supported the findings from the simulation and indicated that the estimates for item difficulty and ability parameters were highly correlated across estimation methods.  相似文献   

12.
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   

13.
In some tests, examinees are required to choose a fixed number of items from a set of given items to answer. This practice creates a challenge to standard item response models, because more capable examinees may have an advantage by making wiser choices. In this study, we developed a new class of item response models to account for the choice effect of examinee‐selected items. The results of a series of simulation studies showed: (1) that the parameters of the new models were recovered well, (2) the parameter estimates were almost unbiased when the new models were fit to data that were simulated from standard item response models, (3) failing to consider the choice effect yielded shrunken parameter estimates for examinee‐selected items, and (4) even when the missingness mechanism in examinee‐selected items did not follow the item response functions specified in the new models, the new models still yielded a better fit than did standard item response models. An empirical example of a college entrance examination supported the use of the new models: in general, the higher the examinee's ability, the better his or her choice of items.  相似文献   

14.
Three local observed‐score kernel equating methods that integrate methods from the local equating and kernel equating frameworks are proposed. The new methods were compared with their earlier counterparts with respect to such measures as bias—as defined by Lord's criterion of equity—and percent relative error. The local kernel item response theory observed‐score equating method, which can be used for any of the common equating designs, had a small amount of bias, a low percent relative error, and a relatively low kernel standard error of equating, even when the accuracy of the test was reduced. The local kernel equating methods for the nonequivalent groups with anchor test generally had low bias and were quite stable against changes in the accuracy or length of the anchor test. Although all proposed methods showed small percent relative errors, the local kernel equating methods for the nonequivalent groups with anchor test design had somewhat larger standard error of equating than their kernel method counterparts.  相似文献   

15.
Large‐scale assessments such as the Programme for International Student Assessment (PISA) have field trials where new survey features are tested for utility in the main survey. Because of resource constraints, there is a trade‐off between how much of the sample can be used to test new survey features and how much can be used for the initial item response theory (IRT) scaling. Utilizing real assessment data of the PISA 2015 Science assessment, this article demonstrates that using fixed item parameter calibration (FIPC) in the field trial yields stable item parameter estimates in the initial IRT scaling for samples as small as n = 250 per country. Moreover, the results indicate that for the recovery of the county‐specific latent trait distributions, the estimates of the trend items (i.e., the information introduced into the calibration) are crucial. Thus, concerning the country‐level sample size of n = 1,950 currently used in the PISA field trial, FIPC is useful for increasing the number of survey features that can be examined during the field trial without the need to increase the total sample size. This enables international large‐scale assessments such as PISA to keep up with state‐of‐the‐art developments regarding assessment frameworks, psychometric models, and delivery platform capabilities.  相似文献   

16.
Building on previous works by Lord and Ogasawara for dichotomous items, this article proposes an approach to derive the asymptotic standard errors of item response theory true score equating involving polytomous items, for equivalent and nonequivalent groups of examinees. This analytical approach could be used in place of empirical methods like the bootstrap method, to obtain standard errors of equated scores. Formulas are introduced to obtain the derivatives for computing the asymptotic standard errors. The approach was validated using mean‐mean, mean‐sigma, random‐groups, or concurrent calibration equating of simulated samples, for tests modeled using the generalized partial credit model or the graded response model.  相似文献   

17.
In operational testing programs using item response theory (IRT), item parameter invariance is threatened when an item appears in a different location on the live test than it did when it was field tested. This study utilizes data from a large state's assessments to model change in Rasch item difficulty (RID) as a function of item position change, test level, test content, and item format. As a follow-up to the real data analysis, a simulation study was performed to assess the effect of item position change on equating. Results from this study indicate that item position change significantly affects change in RID. In addition, although the test construction procedures used in the investigated state seem to somewhat mitigate the impact of item position change, equating results might be impacted in testing programs where other test construction practices or equating methods are utilized.  相似文献   

18.
In observed‐score equipercentile equating, the goal is to make scores on two scales or tests measuring the same construct comparable by matching the percentiles of the respective score distributions. If the tests consist of different items with multiple categories for each item, a suitable model for the responses is a polytomous item response theory (IRT) model. The parameters from such a model can be utilized to derive the score probabilities for the tests and these score probabilities may then be used in observed‐score equating. In this study, the asymptotic standard errors of observed‐score equating using score probability vectors from polytomous IRT models are derived using the delta method. The results are applied to the equivalent groups design and the nonequivalent groups design with either chain equating or poststratification equating within the framework of kernel equating. The derivations are presented in a general form and specific formulas for the graded response model and the generalized partial credit model are provided. The asymptotic standard errors are accurate under several simulation conditions relating to sample size, distributional misspecification and, for the nonequivalent groups design, anchor test length.  相似文献   

19.
Local equating (LE) is based on Lord's criterion of equity. It defines a family of true transformations that aim at the ideal of equitable equating. van der Linden (this issue) offers a detailed discussion of common issues in observed‐score equating relative to this local approach. By assuming an underlying item response theory model, one of the main features of LE is that it adjusts the equated raw scores using conditional distributions of raw scores given an estimate of the ability of interest. In this article, we argue that this feature disappears when using a Rasch model for the estimation of the true transformation, while the one‐parameter logistic model and the two‐parameter logistic model do provide a local adjustment of the equated score.  相似文献   

20.
This study investigated differences between two approaches to chained equipercentile (CE) equating (one‐ and bi‐direction CE equating) in nearly equal groups and relatively unequal groups. In one‐direction CE equating, the new form is linked to the anchor in one sample of examinees and the anchor is linked to the reference form in the other sample. In bi‐direction CE equating, the anchor is linked to the new form in one sample of examinees and to the reference form in the other sample. The two approaches were evaluated in comparison to a criterion equating function (i.e., equivalent groups equating) using indexes such as root expected squared difference, bias, standard error of equating, root mean squared error, and number of gaps and bumps. The overall results across the equating situations suggested that the two CE equating approaches produced very similar results, whereas the bi‐direction results were slightly less erratic, smoother (i.e., fewer gaps and bumps), usually closer to the criterion function, and also less variable.  相似文献   

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