共查询到20条相似文献，搜索用时 93 毫秒
1.
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
2.
Paul W. Holland Sandip Sinharay Alina A. von Davier Ning Han 《Journal of Educational Measurement》2008,45(1):17-43
Two important types of observed score equating (OSE) methods for the non-equivalent groups with Anchor Test (NEAT) design are chain equating (CE) and post-stratification equating (PSE). CE and PSE reflect two distinctly different ways of using the information provided by the anchor test for computing OSE functions. Both types of methods include linear and nonlinear equating functions. In practical situations, it is known that the PSE and CE methods will give different results when the two groups of examinees differ on the anchor test. However, given that both types of methods are justified as OSE methods by making different assumptions about the missing data in the NEAT design, it is difficult to conclude which, if either, of the two is more correct in a particular situation. This study compares the predictions of the PSE and CE assumptions for the missing data using a special data set for which the usually missing data are available. Our results indicate that in an equating setting where the linking function is decidedly non-linear and CE and PSE ought to be different, both sets of predictions are quite similar but those for CE are slightly more accurate . 相似文献
3.
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
4.
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
5.
Alina A. von Davier Paul W. Holland Dorothy T. Thayer 《Journal of Educational Measurement》2004,41(1):15-32
The Non-Equivalent-groups Anchor Test (NEAT) design has been in wide use since at least the early 1940s. It involves two populations of test takers, P and Q, and makes use of an anchor test to link them. Two linking methods used for NEAT designs are those (a) based on chain equating and (b) that use the anchor test to post-stratify the distributions of the two operational test scores to a common population (i.e., Tucker equating and frequency estimation). We show that, under different sets of assumptions, both methods are observed score equating methods and we give conditions under which the methods give identical results. In addition, we develop analogues of the Dorans and Holland (2000) RMSD measures of population invariance of equating methods for the NEAT design for both chain and post-stratification equating methods. 相似文献
6.
Prior use of the equipercentile method of test equating was based on a graphic procedure which is tedious, subject to smoothing errors, and non-analytical. Recognition of the equipercentile method as a curve-fitting procedure for two cumulative percentage distributions leads to a proposed analytical solution to the problem through use of linear estimates for successive "missing" cumulative percentage points. A complete equipercentile procedure which uses the proposed method and provides linear and quadratic functions for goodness-of-fit and extrapolation is discussed and illustrated with data from a test equating project. 相似文献
7.
Score equating based on small samples of examinees is often inaccurate for the examinee populations. We conducted a series of resampling studies to investigate the accuracy of five methods of equating in a common-item design. The methods were chained equipercentile equating of smoothed distributions, chained linear equating, chained mean equating, the symmetric circle-arc method, and the simplified circle-arc method. Four operational test forms, each containing at least 110 items, were used for the equating, with new-form samples of 100, 50, 25, and 10 examinees and reference-form samples three times as large. Accuracy was described in terms of the root-mean-squared difference (over 1,000 replications) of the sample equatings from the criterion equating. Overall, chained mean equating produced the most accurate results for low scores, but the two circle-arc methods produced the most accurate results, 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
8.
9.
Gary Skaggs 《Journal of Educational Measurement》2005,42(4):309-330
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
10.
《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
11.
Gautam Puhan 《Journal of Educational Measurement》2011,48(3):274-292
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
12.
Test equating might be affected by including in the equating analyses examinees who have taken the test previously. This study evaluated the effect of including such repeaters on Medical College Admission Test (MCAT) equating using a population invariance approach. Three-parameter logistic (3-PL) item response theory (IRT) true score and traditional equipercentile equating methods were used under the random groups equating design. This study also examined whether or not population sensitivity of equating by repeater status varies depending on other background variables (gender and ethnicity). The results indicated that there was some evidence of repeaters' effect on equating with varying amounts of such effect by gender. 相似文献
13.
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
14.
It is a widely held belief that anchor tests should be miniature versions (i.e., minitests), with respect to content and statistical characteristics, of the tests being equated. This article examines the foundations for this belief regarding statistical characteristics. It examines the requirement of statistical representativeness of anchor tests that are content representative. The equating performance of several types of anchor tests, including those having statistical characteristics that differ from those of the tests being equated, is examined through several simulation studies and a real data example. Anchor tests with a spread of item difficulties less than that of a total test seem to perform as well as a minitest with respect to equating bias and equating standard error. Hence, the results demonstrate that requiring an anchor test to mimic the statistical characteristics of the total test may be too restrictive and need not be optimal. As a side benefit, this article also provides a comparison of the equating performance of post-stratification equating and chain equipercentile equating. 相似文献
15.
Four equating methods (3PL true score equating, 3PL observed score equating, beta 4 true score equating, and beta 4 observed score equating) were compared using four equating criteria: first-order equity (FOE), second-order equity (SOE), conditional-mean-squared-error (CMSE) difference, and the equipercentile equating property. True score equating more closely achieved estimated FOE than observed score equating when the true score distribution was estimated using the psychometric model that was used in the equating. Observed score equating more closely achieved estimated SOE, estimated CMSE difference, and the equipercentile equating property than true score equating. Among the four equating methods, 3PL observed score equating most closely achieved estimated SOE and had the smallest estimated CMSE difference, and beta 4 observed score equating was the method that most closely met the equipercentile equating property. 相似文献
16.
Samuel A. Livingston 《Journal of Educational Measurement》1993,30(1):23-39
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
17.
18.
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
19.
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
20.
Bjrn Andersson 《Journal of Educational Measurement》2016,53(4):459-477
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