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1.
Measurement specialists routinely assume examinee responses to test items are independent of one another. However, previous research has shown that many contemporary tests contain item dependencies and not accounting for these dependencies leads to misleading estimates of item, test, and ability parameters. The goals of the study were (a) to review methods for detecting local item dependence (LID), (b) to discuss the use of testlets to account for LID in context-dependent item sets, (c) to apply LID detection methods and testlet-based item calibrations to data from a large-scale, high-stakes admissions test, and (d) to evaluate the results with respect to test score reliability and examinee proficiency estimation. Item dependencies were found in the test and these were due to test speededness or context dependence (related to passage structure). Also, the results highlight that steps taken to correct for the presence of LID and obtain less biased reliability estimates may impact on the estimation of examinee proficiency. The practical effects of the presence of LID on passage-based tests are discussed, as are issues regarding how to calibrate context-dependent item sets using item response theory.  相似文献   

2.
In the presence of test speededness, the parameter estimates of item response theory models can be poorly estimated due to conditional dependencies among items, particularly for end‐of‐test items (i.e., speeded items). This article conducted a systematic comparison of five‐item calibration procedures—a two‐parameter logistic (2PL) model, a one‐dimensional mixture model, a two‐step strategy (a combination of the one‐dimensional mixture and the 2PL), a two‐dimensional mixture model, and a hybrid model‐–by examining how sample size, percentage of speeded examinees, percentage of missing responses, and way of scoring missing responses (incorrect vs. omitted) affect the item parameter estimation in speeded tests. For nonspeeded items, all five procedures showed similar results in recovering item parameters. For speeded items, the one‐dimensional mixture model, the two‐step strategy, and the two‐dimensional mixture model provided largely similar results and performed better than the 2PL model and the hybrid model in calibrating slope parameters. However, those three procedures performed similarly to the hybrid model in estimating intercept parameters. As expected, the 2PL model did not appear to be as accurate as the other models in recovering item parameters, especially when there were large numbers of examinees showing speededness and a high percentage of missing responses with incorrect scoring. Real data analysis further described the similarities and differences between the five procedures.  相似文献   

3.
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   

4.
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5.
The usefulness of item response theory (IRT) models depends, in large part, on the accuracy of item and person parameter estimates. For the standard 3 parameter logistic model, for example, these parameters include the item parameters of difficulty, discrimination, and pseudo-chance, as well as the person ability parameter. Several factors impact traditional marginal maximum likelihood (ML) estimation of IRT model parameters, including sample size, with smaller samples generally being associated with lower parameter estimation accuracy, and inflated standard errors for the estimates. Given this deleterious impact of small samples on IRT model performance, use of these techniques with low-incidence populations, where it might prove to be particularly useful, estimation becomes difficult, especially with more complex models. Recently, a Pairwise estimation method for Rasch model parameters has been suggested for use with missing data, and may also hold promise for parameter estimation with small samples. This simulation study compared item difficulty parameter estimation accuracy of ML with the Pairwise approach to ascertain the benefits of this latter method. The results support the use of the Pairwise method with small samples, particularly for obtaining item location estimates.  相似文献   

6.
When tests are administered under fixed time constraints, test performances can be affected by speededness. Among other consequences, speededness can result in inaccurate parameter estimates in item response theory (IRT) models, especially for items located near the end of tests (Oshima, 1994). This article presents an IRT strategy for reducing contamination in item difficulty estimates due to speededness. Ordinal constraints are applied to a mixture Rasch model (Rost, 1990) so as to distinguish two latent classes of examinees: (a) a "speeded" class, comprised of examinees that had insufficient time to adequately answer end-of-test items, and (b) a "nonspeeded" class, comprised of examinees that had sufficient time to answer all items. The parameter estimates obtained for end-of-test items in the nonspeeded class are shown to more accurately approximate their difficulties when the items are administered at earlier locations on a different form of the test. A mixture model can also be used to estimate the class memberships of individual examinees. In this way, it can be determined whether membership in the speeded class is associated with other student characteristics. Results are reported for gender and ethnicity.  相似文献   

7.
Item response theory (IRT) procedures have been used extensively to study normal latent trait distributions and have been shown to perform well; however, less is known concerning the performance of IRT with non-normal latent trait distributions. This study investigated the degree of latent trait estimation error under normal and non-normal conditions using four latent trait estimation procedures and also evaluated whether the test composition, in terms of item difficulty level, reduces estimation error. Most importantly, both true and estimated item parameters were examined to disentangle the effects of latent trait estimation error from item parameter estimation error. Results revealed that non-normal latent trait distributions produced a considerably larger degree of latent trait estimation error than normal data. Estimated item parameters tended to have comparable precision to true item parameters, thus suggesting that increased latent trait estimation error results from latent trait estimation rather than item parameter estimation.  相似文献   

8.
In structural equation modeling software, either limited-information (bivariate proportions) or full-information item parameter estimation routines could be used for the 2-parameter item response theory (IRT) model. Limited-information methods assume the continuous variable underlying an item response is normally distributed. For skewed and platykurtic latent variable distributions, 3 methods were compared in Mplus: limited information, full information integrating over a normal distribution, and full information integrating over the known underlying distribution. Interfactor correlation estimates were similar for all 3 estimation methods. For the platykurtic distribution, estimation method made little difference for the item parameter estimates. When the latent variable was negatively skewed, for the most discriminating easy or difficult items, limited-information estimates of both parameters were considerably biased. Full-information estimates obtained by marginalizing over a normal distribution were somewhat biased. Full-information estimates obtained by integrating over the true latent distribution were essentially unbiased. For the a parameters, standard errors were larger for the limited-information estimates when the bias was positive but smaller when the bias was negative. For the d parameters, standard errors were larger for the limited-information estimates of the easiest, most discriminating items. Otherwise, they were generally similar for the limited- and full-information estimates. Sample size did not substantially impact the differences between the estimation methods; limited information did not gain an advantage for smaller samples.  相似文献   

9.
In test development, item response theory (IRT) is a method to determine the amount of information that each item (i.e., item information function) and combination of items (i.e., test information function) provide in the estimation of an examinee's ability. Studies investigating the effects of item parameter estimation errors over a range of ability have demonstrated an overestimation of information when the most discriminating items are selected (i.e., item selection based on maximum information). In the present study, the authors examined the influence of item parameter estimation errors across 3 item selection methods—maximum no target, maximum target, and theta maximum—using the 2- and 3-parameter logistic IRT models. Tests created with the maximum no target and maximum target item selection procedures consistently overestimated the test information function. Conversely, tests created using the theta maximum item selection procedure yielded more consistent estimates of the test information function and, at times, underestimated the test information function. Implications for test development are discussed.  相似文献   

10.
The graded response model can be used to describe test-taking behavior when item responses are classified into ordered categories. In this study, parameter recovery in the graded response model was investigated using the MULTILOG computer program under default conditions. Based on items having five response categories, 36 simulated data sets were generated that varied on true θ distribution, true item discrimination distribution, and calibration sample size. The findings suggest, first, the correlations between the true and estimated parameters were consistently greater than 0.85 with sample sizes of at least 500. Second, the root mean square error differences between true and estimated parameters were comparable with results from binary data parameter recovery studies. Of special note was the finding that the calibration sample size had little influence on the recovery of the true ability parameter but did influence item-parameter recovery. Therefore, it appeared that item-parameter estimation error, due to small calibration samples, did not result in poor person-parameter estimation. It was concluded that at least 500 examinees are needed to achieve an adequate calibration under the graded model.  相似文献   

11.
Six procedures for combining sets of IRT item parameter estimates obtained from different samples were evaluated using real and simulated response data. In the simulated data analyses, true item and person parameters were used to generate response data for three different-sized samples. Each sample was calibrated separately to obtain three sets of item parameter estimates for each item. The six procedures for combining multiple estimates were each applied, and the results were evaluated by comparing the true and estimated item characteristic curves. For the real data, the two best methods from the simulation data analyses were applied to three different-sized samples and the resulting estimated item characteristic curves were compared to the curves obtained when the three samples were combined and calibrated simultaneously. The results support the use of covariance matrix-weighted averaging and a procedure that involves sample-size-weighted averaging of estimated item characteristic curves at the center of the ability distribution  相似文献   

12.
A critical component of test speededness is the distribution of the test taker’s total time on the test. A simple set of constraints on the item parameters in the lognormal model for response times is derived that can be used to control the distribution when assembling a new test form. As the constraints are linear in the item parameters, they can easily be included in a mixed integer programming model for test assembly. The use of the constraints is demonstrated for the problems of assembling a new test form to be equally speeded as a reference form, test assembly in which the impact of a change in the content specifications on speededness is to be neutralized, and the assembly of test forms with a revised level of speededness.  相似文献   

13.
The presence of nuisance dimensionality is a potential threat to the accuracy of results for tests calibrated using a measurement model such as a factor analytic model or an item response theory model. This article describes a mixture group bifactor model to account for the nuisance dimensionality due to a testlet structure as well as the dimensionality due to differences in patterns of responses. The model can be used for testing whether or not an item functions differently across latent groups in addition to investigating the differential effect of local dependency among items within a testlet. An example is presented comparing test speededness results from a conventional factor mixture model, which ignores the testlet structure, with results from the mixture group bifactor model. Results suggested the 2 models treated the data somewhat differently. Analysis of the item response patterns indicated that the 2-class mixture bifactor model tended to categorize omissions as indicating speededness. With the mixture group bifactor model, more local dependency was present in the speeded than in the nonspeeded class. Evidence from a simulation study indicated the Bayesian estimation method used in this study for the mixture group bifactor model can successfully recover generated model parameters for 1- to 3-group models for tests containing testlets.  相似文献   

14.
Detection of differential item functioning (DIF) on items intentionally constructed to favor one group over another was investigated on item parameter estimates obtained from two item response theory-based computer programs, LOGIST and BILOG. Signed- and unsigned-area measures based on joint maximum likelihood estimation, marginal maximum likelihood estimation, and two marginal maximum a posteriori estimation procedures were compared with each other to determine whether detection of DIF could be improved using prior distributions. Results indicated that item parameter estimates obtained using either prior condition were less deviant than when priors were not used. Differences in detection of DIF appeared to be related to item parameter estimation condition and to some extent to sample size.  相似文献   

15.
《教育实用测度》2013,26(2):125-141
Item parameter instability can threaten the validity of inferences about changes in student achievement when using Item Response Theory- (IRT) based test scores obtained on different occasions. This article illustrates a model-testing approach for evaluating the stability of IRT item parameter estimates in a pretest-posttest design. Stability of item parameter estimates was assessed for a random sample of pretest and posttest responses to a 19-item math test. Using MULTILOG (Thissen, 1986), IRT models were estimated in which item parameter estimates were constrained to be equal across samples (reflecting stability) and item parameter estimates were free to vary across samples (reflecting instability). These competing models were then compared statistically in order to test the invariance assumption. The results indicated a moderately high degree of stability in the item parameter estimates for a group of children assessed on two different occasions.  相似文献   

16.
As low-stakes testing contexts increase, low test-taking effort may serve as a serious validity threat. One common solution to this problem is to identify noneffortful responses and treat them as missing during parameter estimation via the effort-moderated item response theory (EM-IRT) model. Although this model has been shown to outperform traditional IRT models (e.g., two-parameter logistic [2PL]) in parameter estimation under simulated conditions, prior research has failed to examine its performance under violations to the model’s assumptions. Therefore, the objective of this simulation study was to examine item and mean ability parameter recovery when violating the assumptions that noneffortful responding occurs randomly (Assumption 1) and is unrelated to the underlying ability of examinees (Assumption 2). Results demonstrated that, across conditions, the EM-IRT model provided robust item parameter estimates to violations of Assumption 1. However, bias values greater than 0.20 SDs were observed for the EM-IRT model when violating Assumption 2; nonetheless, these values were still lower than the 2PL model. In terms of mean ability estimates, model results indicated equal performance between the EM-IRT and 2PL models across conditions. Across both models, mean ability estimates were found to be biased by more than 0.25 SDs when violating Assumption 2. However, our accompanying empirical study suggested that this biasing occurred under extreme conditions that may not be present in some operational settings. Overall, these results suggest that the EM-IRT model provides superior item and equal mean ability parameter estimates in the presence of model violations under realistic conditions when compared with the 2PL model.  相似文献   

17.
Administering tests under time constraints may result in poorly estimated item parameters, particularly for items at the end of the test (Douglas, Kim, Habing, & Gao, 1998; Oshima, 1994). Bolt, Cohen, and Wollack (2002) developed an item response theory mixture model to identify a latent group of examinees for whom a test is overly speeded, and found that item parameter estimates for end-of-test items in the nonspeeded group were similar to estimates for those same items when administered earlier in the test. In this study, we used the Bolt et al. (2002) method to study the effect of removing speeded examinees on the stability of a score scale over an II-year period. Results indicated that using only the nonspeeded examinees for equating and estimating item parameters provided a more unidimensional scale, smaller effects of item parameter drift (including fewer drifting items), and less scale drift (i.e., bias) and variability (i.e., root mean squared errors) when compared to the total group of examinees.  相似文献   

18.
Item response models are finding increasing use in achievement and aptitude test development. Item response theory (IRT) test development involves the selection of test items based on a consideration of their item information functions. But a problem arises because item information functions are determined by their item parameter estimates, which contain error. When the "best" items are selected on the basis of their statistical characteristics, there is a tendency to capitalize on chance due to errors in the item parameter estimates. The resulting test, therefore, falls short of the test that was desired or expected. The purposes of this article are (a) to highlight the problem of item parameter estimation errors in the test development process, (b) to demonstrate the seriousness of the problem with several simulated data sets, and (c) to offer a conservative solution for addressing the problem in IRT-based test development.  相似文献   

19.
Speededness refers to the extent to which time limits affect examinees'test performance, and it is often measured by calculating the proportion of examinees who do not reach a certain percentage of test items. However, when tests are number-right scored (i.e., no points are subtracted for incorrect responses), examinees are likely to rapidly guess on items rather than leave them blank. Therefore, this traditional measure of speededness probably underestimates the true amount of speededness on such tests. A more accurate assessment of speededness should also reflect the tendency of examinees to rapidly guess on items as time expires. This rapid-guessing component of speededness can be estimated by modeling response times with a two-state mixture model, as demonstrated with data from a computer- administered reasoning test. Taking into account the combined effect of unreached items and rapid guessing provides a more complete measure of speededness than has previously been available.  相似文献   

20.
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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