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1.
A Monte Carlo simulation technique for generating dichotomous item scores is presented that implements (a) a psychometric model with different explicit assumptions than traditional parametric item response theory (IRT) models, and (b) item characteristic curves without restrictive assumptions concerning mathematical form. The four-parameter beta compound-binomial (4PBCB) strong true score model (with two-term approximation to the compound binomial) is used to estimate and generate the true score distribution. The nonparametric item-true score step functions are estimated by classical item difficulties conditional on proportion-correct total score. The technique performed very well in replicating inter-item correlations, item statistics (point-biserial correlation coefficients and item proportion-correct difficulties), first four moments of total score distribution, and coefficient alpha of three real data sets consisting of educational achievement test scores. The technique replicated real data (including subsamples of differing proficiency) as well as the three-parameter logistic (3PL) IRT model (and much better than the 1PL model) and is therefore a promising alternative simulation technique. This 4PBCB technique may be particularly useful as a more neutral simulation procedure for comparing methods that use different IRT models.  相似文献   

2.
以概化理论和项目反应理论为代表的现代测验理论是在克服经典测验理论缺陷的基础上产生的。概化理论是在经典测验理论的基础上,引入实验设计和方差分析技术,对测评情境中的各类误差进行分解和控制的一种现代测量理论,其发展主要经历了一元概化理论和多元概化理论两个阶段。目前,其应用主要集中在评价、考试和评定量表编制三个领域。项目反应理论是在克服经典测验理论题目参数等指标的变异性基础上发展起来的一种现代测验理论,其发展经历了早期理论探索、理论初步形成和理论逐渐完善三个阶段。它主要用于处理分数等值和测验项目参数、测验和项目的质量的分析,剥离测验情境中评委特征对测验结果的影响,以及测查项目功能差异、编制适应性测验等。  相似文献   

3.
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   

4.
In classical test theory, a test is regarded as a sample of items from a domain defined by generating rules or by content, process, and format specifications, l f the items are a random sample of the domain, then the percent-correct score on the test estimates the domain score, that is, the expected percent correct for all items in the domain. When the domain is represented by a large set of calibrated items, as in item banking applications, item response theory (IRT) provides an alternative estimator of the domain score by transformation of the IRT scale score on the test. This estimator has the advantage of not requiring the test items to be a random sample of the domain, and of having a simple standard error. We present here resampling results in real data demonstrating for uni- and multidimensional models that the IRT estimator is also a more accurate predictor of the domain score than is the classical percent-correct score. These results have implications for reporting outcomes of educational qualification testing and assessment.  相似文献   

5.
In this article we present a general approach not relying on item response theory models (non‐IRT) to detect differential item functioning (DIF) in dichotomous items with presence of guessing. The proposed nonlinear regression (NLR) procedure for DIF detection is an extension of method based on logistic regression. As a non‐IRT approach, NLR can be seen as a proxy of detection based on the three‐parameter IRT model which is a standard tool in the study field. Hence, NLR fills a logical gap in DIF detection methodology and as such is important for educational purposes. Moreover, the advantages of the NLR procedure as well as comparison to other commonly used methods are demonstrated in a simulation study. A real data analysis is offered to demonstrate practical use of the method.  相似文献   

6.
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7.
In this article, linear item response theory (IRT) observed‐score equating is compared under a generalized kernel equating framework with Levine observed‐score equating for nonequivalent groups with anchor test design. Interestingly, these two equating methods are closely related despite being based on different methodologies. Specifically, when using data from IRT models, linear IRT observed‐score equating is virtually identical to Levine observed‐score equating. This leads to the conclusion that poststratification equating based on true anchor scores can be viewed as the curvilinear Levine observed‐score equating.  相似文献   

8.
This article considers psychometric properties of composite raw scores and transformed scale scores on mixed-format tests that consist of a mixture of multiple-choice and free-response items. Test scores on several mixed-format tests are evaluated with respect to conditional and overall standard errors of measurement, score reliability, and classification consistency and accuracy under three item response theory (IRT) frameworks: unidimensional IRT (UIRT), simple structure multidimensional IRT (SS-MIRT), and bifactor multidimensional IRT (BF-MIRT) models. Illustrative examples are presented using data from three mixed-format exams with various levels of format effects. In general, the two MIRT models produced similar results, while the UIRT model resulted in consistently lower estimates of reliability and classification consistency/accuracy indices compared to the MIRT models.  相似文献   

9.
The focus of this article is on scale score transformations that can be used to stabilize conditional standard errors of measurement (CSEMs). Three transformations for stabilizing the estimated CSEMs are reviewed, including the traditional arcsine transformation, a recently developed general variance stabilization transformation, and a new method proposed in this article involving cubic transformations. Two examples are provided and the three scale score transformations are compared in terms of how well they stabilize CSEMs estimated from compound binomial and item response theory (IRT) models. Advantages of the cubic transformation are demonstrated with respect to CSEM stabilization and other scaling criteria (e.g., scale score distributions that are more symmetric).  相似文献   

10.
This article illustrates five different methods for estimating Angoff cut scores using item response theory (IRT) models. These include maximum likelihood (ML), expected a priori (EAP), modal a priori (MAP), and weighted maximum likelihood (WML) estimators, as well as the most commonly used approach based on translating ratings through the test characteristic curve (i.e., the IRT true‐score (TS) estimator). The five methods are compared using a simulation study and a real data example. Results indicated that the application of different methods can sometimes lead to different estimated cut scores, and that there can be some key differences in impact data when using the IRT TS estimator compared to other methods. It is suggested that one should carefully think about their choice of methods to estimate ability and cut scores because different methods have distinct features and properties. An important consideration in the application of Bayesian methods relates to the choice of the prior and the potential bias that priors may introduce into estimates.  相似文献   

11.
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   

12.
Using a New Statistical Model for Testlets to Score TOEFL   总被引：1，自引：0，他引：1  
Standard item response theory (IRT) models fit to examination responses ignore the fact that sets of items (testlets) often are matched with a single common stimulus (e.g., a reading comprehension passage). In this setting, all items given to an examinee are unlikely to be conditionally independent (given examinee proficiency). Models that assume conditional independence will overestimate the precision with which examinee proficiency is measured. Overstatement of precision may lead to inaccurate inferences as well as prematurely ended examinations in which the stopping rule is based on the estimated standard error of examinee proficiency (e.g., an adaptive test). The standard three parameter IRT model was modified to include an additional random effect for items nested within the same testlet (Wainer, Bradlow, & Du, 2000). This parameter, γ characterizes the amount of local dependence in a testlet.
We fit 86 TOEFL testlets (50 reading comprehension and 36 listening comprehension) with the new model, and obtained a value for the variance of γ for each testlet. We compared the standard parameters (discrimination (a), difficulty (b) and guessing (c)) with what is obtained through traditional modeling. We found that difficulties were well estimated either way, but estimates of both a and c were biased if conditional independence is incorrectly assumed. Of greater import, we found that test information was substantially over-estimated when conditional independence was incorrectly assumed.  相似文献   

13.
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   

14.
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   

15.
A developmental scale for the North Carolina End-of-Grade Mathematics Tests was created using a subset of identical test forms administered to adjacent grade levels. Thurstone scaling and item response theory (IRT) techniques were employed to analyze the changes in grade distributions across these linked forms.Three variations of Thurstone scaling were examined, one based on Thurstone's 1925 procedure and two based on Thurstone's 1938 procedure. The IRT scaling was implemented using both B i M ain and M ultilog .All methods indicated that average mathematics performance improved from Grade 3 to Grade 8, with similar results for the two IRT analyses and one version of Thurstone's 1938 method.The standard deviations of the IRT scales did not show a consistent pattern across grades, whereas those produced by Thurstone's 1925 procedure generally decreased; one version of the 1938 method exhibited slightly increasing variation with increasing grade level, while the other version displayed inconsistent trends.  相似文献   

16.
Functional form misfit is frequently a concern in item response theory (IRT), although the practical implications of misfit are often difficult to evaluate. In this article, we illustrate how seemingly negligible amounts of functional form misfit, when systematic, can be associated with significant distortions of the score metric in vertical scaling contexts. Our analysis uses two‐ and three‐parameter versions of Samejima's logistic positive exponent model (LPE) as a data generating model. Consistent with prior work, we find LPEs generally provide a better comparative fit to real item response data than traditional IRT models (2PL, 3PL). Further, our simulation results illustrate how 2PL‐ or 3PL‐based vertical scaling in the presence of LPE‐induced misspecification leads to an artificial growth deceleration across grades, consistent with that commonly seen in vertical scaling studies. The results raise further concerns about the use of standard IRT models in measuring growth, even apart from the frequently cited concerns of construct shift/multidimensionality across grades.  相似文献   

17.
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   

18.
Sometimes, test‐takers may not be able to attempt all items to the best of their ability (with full effort) due to personal factors (e.g., low motivation) or testing conditions (e.g., time limit), resulting in poor performances on certain items, especially those located toward the end of a test. Standard item response theory (IRT) models fail to consider such testing behaviors. In this study, a new class of mixture IRT models was developed to account for such testing behavior in dichotomous and polytomous items, by assuming test‐takers were composed of multiple latent classes and by adding a decrement parameter to each latent class to describe performance decline. Parameter recovery, effect of model misspecification, and robustness of the linearity assumption in performance decline were evaluated using simulations. It was found that the parameters in the new models were recovered fairly well by using the freeware WinBUGS; the failure to account for such behavior by fitting standard IRT models resulted in overestimation of difficulty parameters on items located toward the end of the test and overestimation of test reliability; and the linearity assumption in performance decline was rather robust. An empirical example is provided to illustrate the applications and the implications of the new class of models.  相似文献   

19.
Wei Tao  Yi Cao 《教育实用测度》2013,26(2):108-121
ABSTRACT

Current procedures for equating number-correct scores using traditional item response theory (IRT) methods assume local independence. However, when tests are constructed using testlets, one concern is the violation of the local item independence assumption. The testlet response theory (TRT) model is one way to accommodate local item dependence. This study proposes methods to extend IRT true score and observed score equating methods to the dichotomous TRT model. We also examine the impact of local item dependence on equating number-correct scores when a traditional IRT model is applied. Results of the study indicate that when local item dependence is at a low level, using the three-parameter logistic model does not substantially affect number-correct equating. However, when local item dependence is at a moderate or high level, using the three-parameter logistic model generates larger equating bias and standard errors of equating compared to the TRT model. However, observed score equating is more robust to the violation of the local item independence assumption than is true score equating.  相似文献   

20.
常蕤 《考试研究》2008,(2):48-70
本文以小学数学科为例,介绍了香港全港性系统评估应用项目反应理论中的Rasch模型进行测验设计和数据分析,以及用改进的Angoff方法和书签法进行水平厘定,获得水平参照分数报告的过程。  相似文献   

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