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1.
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   

2.
The applications of item response theory (IRT) models assume local item independence and that examinees are independent of each other. When a representative sample for psychometric analysis is selected using a cluster sampling method in a testlet‐based assessment, both local item dependence and local person dependence are likely to be induced. This study proposed a four‐level IRT model to simultaneously account for dual local dependence due to item clustering and person clustering. Model parameter estimation was explored using the Markov Chain Monte Carlo method. Model parameter recovery was evaluated in a simulation study in comparison with three other related models: the Rasch model, the Rasch testlet model, and the three‐level Rasch model for person clustering. In general, the proposed model recovered the item difficulty and person ability parameters with the least total error. The bias in both item and person parameter estimation was not affected but the standard error (SE) was affected. In some simulation conditions, the difference in classification accuracy between models could go up to 11%. The illustration using the real data generally supported model performance observed in the simulation study.  相似文献   

3.
Given the relationships of item response theory (IRT) models to confirmatory factor analysis (CFA) models, IRT model misspecifications might be detectable through model fit indexes commonly used in categorical CFA. The purpose of this study is to investigate the sensitivity of weighted least squares with adjusted means and variance (WLSMV)-based root mean square error of approximation, comparative fit index, and Tucker–Lewis Index model fit indexes to IRT models that are misspecified due to local dependence (LD). It was found that WLSMV-based fit indexes have some functional relationships to parameter estimate bias in 2-parameter logistic models caused by violations of LD. Continued exploration into these functional relationships and development of LD-detection methods based on such relationships could hold much promise for providing IRT practitioners with global information on violations of local independence.  相似文献   

4.
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   

5.
《Educational Assessment》2013,18(2):181-190
Clemans (1993) argued that the use of item response theory (IRT) to vertically scale Form E of the California Achievement Tests produces inappropriate results. In this response we show that (a) Cleman's analysis of school district data was incomplete, inconsistent, and did not follow good measurement practice; (b) the simulation he conducted was unfairly stacked against IRT, was unrealistic, and ignored other realistic published simulations that demonstrated the accuracy of IRT scaling procedures; (c) his "common sense" evaluations of student performance ignored basic facts about the measurement of student achievement; and (d) the concerns expressed in his article were irrelevant to the vast majority of uses of norm-referenced tests.  相似文献   

6.
The present study conducted a systematic review of the item response theory (IRT) literature in language assessment to investigate the conceptualization and operationalization of the dimensionality of language ability. Sixty-two IRT-based studies published between 1985 and 2020 in language assessment and educational measurement journals were first classified into two categories based on a unidimensional and multidimensional research framework, and then reviewed to examine language dimensionality from technical and substantive perspectives. It was found that 12 quantitative techniques were adopted to assess language dimensionality. Exploratory factor analysis was the primary method of dimensionality analysis in papers that had applied unidimensional IRT models, whereas the comparison modeling approach was dominant in the multidimensional framework. In addition, there was converging evidence within the two streams of research supporting the role of a number of factors such as testlets, language skills, subskills, and linguistic elements as sources of multidimensionality, while mixed findings were reported for the role of item formats across research streams. The assessment of reading, listening, speaking, and writing skills was grounded within both unidimensional and multidimensional framework. By contrast, vocabulary and grammar knowledge was mainly conceptualized as unidimensional. Directions for continued inquiry and application of IRT in language assessment are provided.  相似文献   

7.
A mixed‐effects item response theory (IRT) model is presented as a logical extension of the generalized linear mixed‐effects modeling approach to formulating explanatory IRT models. Fixed and random coefficients in the extended model are estimated using a Metropolis‐Hastings Robbins‐Monro (MH‐RM) stochastic imputation algorithm to accommodate for increased dimensionality due to modeling multiple design‐ and trait‐based random effects. As a consequence of using this algorithm, more flexible explanatory IRT models, such as the multidimensional four‐parameter logistic model, are easily organized and efficiently estimated for unidimensional and multidimensional tests. Rasch versions of the linear latent trait and latent regression model, along with their extensions, are presented and discussed, Monte Carlo simulations are conducted to determine the efficiency of parameter recovery of the MH‐RM algorithm, and an empirical example using the extended mixed‐effects IRT model is presented.  相似文献   

8.
An approach called generalizability in item response modeling (GIRM) is introduced in this article. The GIRM approach essentially incorporates the sampling model of generalizability theory (GT) into the scaling model of item response theory (IRT) by making distributional assumptions about the relevant measurement facets. By specifying a random effects measurement model, and taking advantage of the flexibility of Markov Chain Monte Carlo (MCMC) estimation methods, it becomes possible to estimate GT variance components simultaneously with traditional IRT parameters. It is shown how GT and IRT can be linked together, in the context of a single-facet measurement design with binary items. Using both simulated and empirical data with the software WinBUGS, the GIRM approach is shown to produce results comparable to those from a standard GT analysis, while also producing results from a random effects IRT model.  相似文献   

9.
A rapidly expanding arena for item response theory (IRT) is in attitudinal and health‐outcomes survey applications, often with polytomous items. In particular, there is interest in computer adaptive testing (CAT). Meeting model assumptions is necessary to realize the benefits of IRT in this setting, however. Although initial investigations of local item dependence have been studied both for polytomous items in fixed‐form settings and for dichotomous items in CAT settings, there have been no publications applying local item dependence detection methodology to polytomous items in CAT despite its central importance to these applications. The current research uses a simulation study to investigate the extension of widely used pairwise statistics, Yen's Q3 Statistic and Pearson's Statistic X2, in this context. The simulation design and results are contextualized throughout with a real item bank of this type from the Patient‐Reported Outcomes Measurement Information System (PROMIS).  相似文献   

10.
Even though Bayesian estimation has recently become quite popular in item response theory (IRT), there is a lack of works on model checking from a Bayesian perspective. This paper applies the posterior predictive model checking (PPMC) method ( Guttman, 1967 ; Rubin, 1984 ), a popular Bayesian model checking tool, to a number of real applications of unidimensional IRT models. The applications demonstrate how to exploit the flexibility of the posterior predictive checks to meet the need of the researcher. This paper also examines practical consequences of misfit, an area often ignored in educational measurement literature while assessing model fit.  相似文献   

11.
This study proposes a structured constructs model (SCM) to examine measurement in the context of a multidimensional learning progression (LP). The LP is assumed to have features that go beyond a typical multidimentional IRT model, in that there are hypothesized to be certain cross‐dimensional linkages that correspond to requirements between the levels of the different dimensions. The new model builds on multidimensional item response theory models and change‐point analysis to add cut‐score and discontinuity parameters that embody these substantive requirements. This modeling strategy allows us to place the examinees in the appropriate LP level and simultaneously to model the hypothesized requirement relations. Results from a simulation study indicate that the proposed change‐point SCM recovers the generating parameters well. When the hypothesized requirement relations are ignored, the model fit tends to become worse, and the model parameters appear to be more biased. Moreover, the proposed model can be used to find validity evidence to support or disprove initial theoretical hypothesized links in the LP through empirical data. We illustrate the technique with data from an assessment system designed to measure student progress in a middle‐school statistics and modeling curriculum.  相似文献   

12.
Single‐best answers to multiple‐choice items are commonly dichotomized into correct and incorrect responses, and modeled using either a dichotomous item response theory (IRT) model or a polytomous one if differences among all response options are to be retained. The current study presents an alternative IRT‐based modeling approach to multiple‐choice items administered with the procedure of elimination testing, which asks test‐takers to eliminate all the response options they consider to be incorrect. The partial credit model is derived for the obtained responses. By extracting more information pertaining to test‐takers’ partial knowledge on the items, the proposed approach has the advantage of providing more accurate estimation of the latent ability. In addition, it may shed some light on the possible answering processes of test‐takers on the items. As an illustration, the proposed approach is applied to a classroom examination of an undergraduate course in engineering science.  相似文献   

13.
Both structural equation modeling (SEM) and item response theory (IRT) can be used for factor analysis of dichotomous item responses. In this case, the measurement models of both approaches are formally equivalent. They were refined within and across different disciplines, and make complementary contributions to central measurement problems encountered in almost all empirical social science research fields. In this article (a) fundamental formal similiarities between IRT and SEM models are pointed out. It will be demonstrated how both types of models can be used in combination to analyze (b) the dimensional structure and (c) the measurement invariance of survey item responses. All analyses are conducted with Mplus, which allows an integrated application of both approaches in a unified, general latent variable modeling framework. The aim is to promote a diffusion of useful measurement techniques and skills from different disciplines into empirical social research.  相似文献   

14.
An approach to essay grading based on signal detection theory (SDT) is presented. SDT offers a basis for understanding rater behavior with respect to the scoring of construct responses, in that it provides a theory of psychological processes underlying the raters' behavior. The approach also provides measures of the precision of the raters and the accuracy of classifications. An application of latent class SDT to essay grading is detailed, and similarities to and differences from item response theory (IRT) are noted. The validity and utility of classifications obtained from the SDT model and scores obtained from IRT models are compared. Validity coefficients were found to be about equal in magnitude across SDT and IRT models. Results from a simulation study of a 5-class SDT model with eight raters are also presented.  相似文献   

15.
Item response theory (IRT) models can be subsumed under the larger class of statistical models with latent variables. IRT models are increasingly used for the scaling of the responses derived from standardized assessments of competencies. The paper summarizes the strengths of IRT in contrast to more traditional techniques as well as in contrast to alternative models with latent variables (e. g. structural equation modeling). Subsequently, specific limitations of IRT and cases where other methods might be preferable are lined out.  相似文献   

16.
In this article, I address two competing conceptions of differential item functioning (DIF) in polytomously scored items. The first conception, referred to as net DIF, concerns between-group differences in the conditional expected value of the polytomous response variable. The second conception, referred to as global DIF, concerns the conditional dependence of group membership and the polytomous response variable. The distinction between net and global DIF is important because different DIF evaluation methods are appropriate for net and global DIF; no currently available method is universally the best for detecting both net and global DIF. Net and global DIF definitions are presented under two different, yet compatible, modeling frameworks: a traditional item response theory (IRT) framework, and a differential step functioning (DSF) framework. The theoretical relationship between the IRT and DSF frameworks is presented. Available methods for evaluating net and global DIF are described, and an applied example of net and global DIF is presented.  相似文献   

17.
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   

18.
Linear factor analysis (FA) models can be reliably tested using test statistics based on residual covariances. We show that the same statistics can be used to reliably test the fit of item response theory (IRT) models for ordinal data (under some conditions). Hence, the fit of an FA model and of an IRT model to the same data set can now be compared. When applied to a binary data set, our experience suggests that IRT and FA models yield similar fits. However, when the data are polytomous ordinal, IRT models yield a better fit because they involve a higher number of parameters. But when fit is assessed using the root mean square error of approximation (RMSEA), similar fits are obtained again. We explain why. These test statistics have little power to distinguish between FA and IRT models; they are unable to detect that linear FA is misspecified when applied to ordinal data generated under an IRT model.  相似文献   

19.
Standard 3.9 of the Standards for Educational and Psychological Testing ( 1999 ) demands evidence of model fit when item response theory (IRT) models are employed to data from tests. Hambleton and Han ( 2005 ) and Sinharay ( 2005 ) recommended the assessment of practical significance of misfit of IRT models, but few examples of such assessment can be found in the literature concerning IRT model fit. In this article, practical significance of misfit of IRT models was assessed using data from several tests that employ IRT models to report scores. The IRT model did not fit any data set considered in this article. However, the extent of practical significance of misfit varied over the data sets.  相似文献   

20.
This article describes an ongoing project to develop a formative, inferential reading comprehension assessment of causal story comprehension. It has three features to enhance classroom use: equated scale scores for progress monitoring within and across grades, a scale score to distinguish among low‐scoring students based on patterns of mistakes, and a reading efficiency index. Instead of two response types for each multiple‐choice item, correct and incorrect, each item has three response types: correct and two incorrect response types. Prior results on reliability, convergent and discriminant validity, and predictive utility of mistake subscores are briefly described. The three‐response‐type structure of items required rethinking the item response theory (IRT) modeling. IRT‐modeling results are presented, and implications for formative assessments and instructional use are discussed.  相似文献   

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