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1.
Five methods for equating in a random groups design were investigated in a series of resampling studies with samples of 400, 200, 100, and 50 test takers. Six operational test forms, each taken by 9,000 or more test takers, were used as item pools to construct pairs of forms to be equated. The criterion equating was the direct equipercentile equating in the group of all test takers. Equating accuracy was indicated by the root-mean-squared deviation, over 1,000 replications, of the sample equatings from the criterion equating. The methods investigated were equipercentile equating of smoothed distributions, linear equating, mean equating, symmetric circle-arc equating, and simplified circle-arc equating. The circle-arc methods produced the most accurate results for all sample sizes investigated, particularly in the upper half of the score distribution. The difference in equating accuracy between the two circle-arc methods was negligible.  相似文献   

2.
This article describes a preliminary investigation of an empirical Bayes (EB) procedure for using collateral information to improve equating of scores on test forms taken by small numbers of examinees. Resampling studies were done on two different forms of the same test. In each study, EB and non-EB versions of two equating methods—chained linear and chained mean—were applied to repeated small samples drawn from a large data set collected for a common-item equating. The criterion equating was the chained linear equating in the large data set. Equatings of other forms of the same test provided the collateral information. New-form sample size was varied from 10 to 200; reference-form sample size was constant at 200. One of the two new forms did not differ greatly in difficulty from its reference form, as was the case for the equatings used as collateral information. For this form, the EB procedure improved the accuracy of equating with new-form samples of 50 or fewer. The other new form was much more difficult than its reference form; for this form, the EB procedure made the equating less accurate.  相似文献   

3.
In this study I compared results of chained linear, Tucker, and Levine-observed score equatings under conditions where the new and old forms samples were similar in ability and also when they were different in ability. The length of the anchor test was also varied to examine its effect on the three different equating methods. The three equating methods were compared to a criterion equating to obtain estimates of random equating error, bias, and root mean squared error (RMSE). Results showed that, for most studied conditions, chained linear equating produced fairly good equating results in terms of low bias and RMSE. Levine equating also produced low bias and RMSE in some conditions. Although the Tucker method always produced the lowest random equating error, it produced a larger bias and RMSE than either of the other equating methods. As noted in the literature, these results also suggest that either chained linear or Levine equating be used when new and old form samples differ on ability and/or when the anchor-to-total correlation is not very high. Finally, by testing the missing data assumptions of the three equating methods, this study also shows empirically why an equating method is more or less accurate under certain conditions .  相似文献   

4.
This study investigated the effectiveness of equating with very small samples using the random groups design. Of particular interest was equating accuracy at specific scores where performance standards might be set. Two sets of simulations were carried out, one in which the two forms were identical and one in which they differed by a tenth of a standard deviation in overall difficulty. These forms were equated using mean equating, linear equating, unsmoothed equipercentile equating, and equipercentile equating using two through six moments of log-linear presmoothing with samples of 25, 50, 75, 100, 150, and 200. The results indicated that identity equating was preferable to any equating method when samples were as small as 25. For samples of 50 and above, the choice of an equating method over identity equating depended on the location of the passing score relative to examinee performance. If passing scores were located below the mean, where data were sparser, mean equating produced the smallest percentage of misclassified examinees. For passing scores near the mean, all methods produced similar results with linear equating being the most accurate. For passing scores above the mean, equipercentile equating with 2- and 3-moment presmoothing were the best equating methods. Higher levels of presmoothing did not improve the results.  相似文献   

5.
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   

6.
This study investigated the extent to which log-linear smoothing could improve the accuracy of common-item equating by the chained equipercentile method in small samples of examinees. Examinee response data from a 100-item test were used to create two overlapping forms of 58 items each, with 24 items in common. The criterion equating was a direct equipercentile equating of the two forms in the full population of 93,283 examinees. Anchor equatings were performed in samples of 25, 50, 100, and 200 examinees, with 50 pairs of samples at each size level. Four equatings were performed with each pair of samples: one based on unsmoothed distributions and three based on varying degrees of smoothing. Smoothing reduced, by at least half, the sample size required for a given degree of accuracy. Smoothing that preserved only two moments of the marginal distributions resulted in equatings that failed to capture the curvilinearity in the population equating.  相似文献   

7.
Tucker and chained linear equatings were evaluated in two testing scenarios. In Scenario 1, referred to as rater comparability scoring and equating, the anchor‐to‐total correlation is often very high for the new form but moderate for the reference form. This may adversely affect the results of Tucker equating, especially if the new and reference form samples differ in ability. In Scenario 2, the new and reference form samples are randomly equivalent but the correlation between the anchor and total scores is low. When the correlation between the anchor and total scores is low, Tucker equating assumes that the new and reference form samples are similar in ability (which, with randomly equivalents groups, is the correct assumption). Thus Tucker equating should produce accurate results. Results indicated that in Scenario 1, the Tucker results were less accurate than the chained linear equating results. However, in Scenario 2, the Tucker results were more accurate than the chained linear equating results. Some implications are discussed.  相似文献   

8.
Combinations of five methods of equating test forms and two methods of selecting samples of students for equating were compared for accuracy. The two sampling methods were representative sampling from the population and matching samples on the anchor test score. The equating methods were the Tucker, Levine equally reliable, chained equipercentile, frequency estimation, and item response theory (IRT) 3PL methods. The tests were the Verbal and Mathematical sections of the Scholastic Aptitude Test. The criteria for accuracy were measures of agreement with an equivalent-groups equating based on more than 115,000 students taking each form. Much of the inaccuracy in the equatings could be attributed to overall bias. The results for all equating methods in the matched samples were similar to those for the Tucker and frequency estimation methods in the representative samples; these equatings made too small an adjustment for the difference in the difficulty of the test forms. In the representative samples, the chained equipercentile method showed a much smaller bias. The IRT (3PL) and Levine methods tended to agree with each other and were inconsistent in the direction of their bias.  相似文献   

9.
This study investigates a sequence of item response theory (IRT) true score equatings based on various scale transformation approaches and evaluates equating accuracy and consistency over time. The results show that the biases and sample variances for the IRT true score equating (both direct and indirect) are quite small (except for the mean/sigma method). The biases and sample variances for the equating functions based on the characteristic curve methods and concurrent calibrations for adjacent forms are smaller than the biases and variances for the equating functions based on the moment methods. In addition, the IRT true score equating is also compared to the chained equipercentile equating, and we observe that the sample variances for the chained equipercentile equating are much smaller than the variances for the IRT true score equating with an exception at the low scores.  相似文献   

10.
This study addressed the sampling error and linking bias that occur with small samples in a nonequivalent groups anchor test design. We proposed a linking method called the synthetic function, which is a weighted average of the identity function and a traditional equating function (in this case, the chained linear equating function). Specifically, we compared the synthetic, identity, and chained linear functions for various‐sized samples from two types of national assessments. One design used a highly reliable test and an external anchor, and the other used a relatively low‐reliability test and an internal anchor. The results from each of these methods were compared to the criterion equating function derived from the total samples with respect to linking bias and error. The study indicated that the synthetic functions might be a better choice than the chained linear equating method when samples are not large and, as a result, unrepresentative.  相似文献   

11.
This article presents a method for evaluating equating results. Within the kernel equating framework, the percent relative error (PRE) for chained equipercentile equating was computed under the nonequivalent groups with anchor test (NEAT) design. The method was applied to two data sets to obtain the PRE, which can be used to measure equating effectiveness. The study compared the PRE results for chained and poststratification equating. The results indicated that the chained method transformed the new form score distribution to the reference form scale more effectively than the poststratification method. In addition, the study found that in chained equating, the population weight had impact on score distributions over the target population but not on the equating and PRE results.  相似文献   

12.
The synthetic function is a weighted average of the identity (the linking function for forms that are known to be completely parallel) and a traditional equating method. The purpose of the present study was to investigate the benefits of the synthetic function on small-sample equating using various real data sets gathered from different administrations of tests from a licensure testing program. We investigated the chained linear, Tucker, Levine, and mean equating methods, along with the identity and the synthetic functions with small samples (N = 19 to 70). The synthetic function did not perform as well as did other linear equating methods because test forms differed markedly in difficulty; thus, the use of the identity function produced substantial bias. The effectiveness of the synthetic function depended on the forms' similarity in difficulty.  相似文献   

13.
The impact of log‐linear presmoothing on the accuracy of small sample chained equipercentile equating was evaluated under two conditions . In the first condition the small samples differed randomly in ability from the target population. In the second condition the small samples were systematically different from the target population. Results showed that equating with small samples (e.g., N < 25 or 50) using either raw or smoothed score distributions led to considerable large random equating error (although smoothing reduced random equating error). Moreover, when the small samples were not representative of the target population, the amount of equating bias also was quite large. It is concluded that although presmoothing can reduce random equating error, it is not likely to reduce equating bias caused by using an unrepresentative sample. Other alternatives to the small sample equating problem (e.g., the SiGNET design) which focus more on improving data collection are discussed.  相似文献   

14.
Accurate equating results are essential when comparing examinee scores across exam forms. Previous research indicates that equating results may not be accurate when group differences are large. This study compared the equating results of frequency estimation, chained equipercentile, item response theory (IRT) true‐score, and IRT observed‐score equating methods. Using mixed‐format test data, equating results were evaluated for group differences ranging from 0 to .75 standard deviations. As group differences increased, equating results became increasingly biased and dissimilar across equating methods. Results suggest that the size of group differences, the likelihood that equating assumptions are violated, and the equating error associated with an equating method should be taken into consideration when choosing an equating method.  相似文献   

15.
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   

16.
The study examined two approaches for equating subscores. They are (1) equating subscores using internal common items as the anchor to conduct the equating, and (2) equating subscores using equated and scaled total scores as the anchor to conduct the equating. Since equated total scores are comparable across the new and old forms, they can be used as an anchor to equate the subscores. Both chained linear and chained equipercentile methods were used. Data from two tests were used to conduct the study and results showed that when more internal common items were available (i.e., 10–12 items), then using common items to equate the subscores is preferable. However, when the number of common items is very small (i.e., five to six items), then using total scaled scores to equate the subscores is preferable. For both tests, not equating (i.e., using raw subscores) is not reasonable as it resulted in a considerable amount of bias.  相似文献   

17.
This study examines the effectiveness of three approaches for maintaining equivalent performance standards across test forms with small samples: (1) common‐item equating, (2) resetting the standard, and (3) rescaling the standard. Rescaling the standard (i.e., applying common‐item equating methodology to standard setting ratings to account for systematic differences between standard setting panels) has received almost no attention in the literature. Identity equating was also examined to provide context. Data from a standard setting form of a large national certification test (N examinees = 4,397; N panelists = 13) were split into content‐equivalent subforms with common items, and resampling methodology was used to investigate the error introduced by each approach. Common‐item equating (circle‐arc and nominal weights mean) was evaluated at samples of size 10, 25, 50, and 100. The standard setting approaches (resetting and rescaling the standard) were evaluated by resampling (N = 8) and by simulating panelists (N = 8, 13, and 20). Results were inconclusive regarding the relative effectiveness of resetting and rescaling the standard. Small‐sample equating, however, consistently produced new form cut scores that were less biased and less prone to random error than new form cut scores based on resetting or rescaling the standard.  相似文献   

18.
Equatings were performed on both simulated and real data sets using the common-examinee design and two abilities for each examinee (i.e., two dimensions). Item and ability parameter estimates were found by using the Multidimensional Item Response Theory Estimation (MIRTE) program. The amount of equating error was evaluated by a comparison of the mean difference and the mean absolute difference between the true scores and ability estimates found on both tests for the common examinees used in the equating. The results indicated that effective equating, as measured by comparability o f true scores, was possible with the techniques used in this study. When the stability o f the ability estimates was examined, unsatisfactory results were found.  相似文献   

19.
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   

20.
In the nonequivalent groups with anchor test (NEAT) design, the standard error of linear observed‐score equating is commonly estimated by an estimator derived assuming multivariate normality. However, real data are seldom normally distributed, causing this normal estimator to be inconsistent. A general estimator, which does not rely on the normality assumption, would be preferred, because it is asymptotically accurate regardless of the distribution of the data. In this article, an analytical formula for the standard error of linear observed‐score equating, which characterizes the effect of nonnormality, is obtained under elliptical distributions. Using three large‐scale real data sets as the populations, resampling studies are conducted to empirically evaluate the normal and general estimators of the standard error of linear observed‐score equating. The effect of sample size (50, 100, 250, or 500) and equating method (chained linear, Tucker, or Levine observed‐score equating) are examined. Results suggest that the general estimator has smaller bias than the normal estimator in all 36 conditions; it has larger standard error when the sample size is at least 100; and it has smaller root mean squared error in all but one condition. An R program is also provided to facilitate the use of the general estimator.  相似文献   

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