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1.
Many statistics used in the assessment of differential item functioning (DIF) in polytomous items yield a single item-level index of measurement invariance that collapses information across all response options of the polytomous item. Utilizing a single item-level index of DIF can, however, be misleading if the magnitude or direction of the DIF changes across the steps underlying the polytomous response process. A more comprehensive approach to examining measurement invariance in polytomous item formats is to examine invariance at the level of each step of the polytomous item, a framework described in this article as differential step functioning (DSF). This article proposes a nonparametric DSF estimator that is based on the Mantel-Haenszel common odds ratio estimator ( Mantel & Haenszel, 1959 ), which is frequently implemented in the detection of DIF in dichotomous items. A simulation study demonstrated that when the level of DSF varied in magnitude or sign across the steps underlying the polytomous response options, the DSF-based approach typically provided a more powerful and accurate test of measurement invariance than did corresponding item-level DIF estimators.  相似文献   

2.
A widely used approach for categorizing the level of differential item functioning (DIF) in dichotomous items is the scheme proposed by Educational Testing Service (ETS) based on a transformation of the Mantel-Haeszel common odds ratio. In this article two classification schemes for DIF in polytomous items (referred to as the P1 and P2 schemes) are proposed that parallel the criteria set forth in the ETS scheme for dichotomous items. The theoretical equivalence of the P1 and P2 schemes to the ETS scheme is described, and the results of a simulation study conducted to examine the empirical equivalence of the P1 and P2 schemes to the ETS scheme are presented.  相似文献   

3.
4.
This article defines and demonstrates a framework for studying differential item functioning (DIF) and differential test functioning (DTF) for tests that are intended to be multidimensional The procedure introduced here is an extension of unidimensional differential functioning of items and tests (DFIT) recently developed by Raju, van der Linden, & Fleer (1995). To demonstrate the usefulness of these new indexes in a multidimensional IRT setting, two-dimensional data were simulated with known item parameters and known DIF and DTE The DIF and DTF indexes were recovered reasonably well under various distributional differences of Os after multidimensional linking was applied to put the two sets of item parameters on a common scale. Further studies are suggested in the area of DIF/DTF for intentionally multidimensional tests.  相似文献   

5.
Several studies have shown that the linguistic complexity of items in achievement tests may cause performance disadvantages for second language learners. However, the relative contributions of specific features of linguistic complexity to this disadvantage are largely unclear. Based on the theoretical concept of academic language, we used data from a state-wide test in mathematics for third graders in Berlin, Germany, to determine the interrelationships among several academic language features of test items and their relative effects on differential item functioning (DIF) against second language learners. Academic language features were significantly correlated with each other and with DIF. While we found text length, general academic vocabulary, and number of noun phrases to be unique predictors of DIF, substantial proportions of the variance in DIF were explained by confounded combinations of several academic language features. Specialised mathematical vocabulary was neither related to DIF nor to the other academic language features.  相似文献   

6.
Traditional methods for examining differential item functioning (DIF) in polytomously scored test items yield a single item‐level index of DIF and thus provide no information concerning which score levels are implicated in the DIF effect. To address this limitation of DIF methodology, the framework of differential step functioning (DSF) has recently been proposed, whereby measurement invariance is examined within each step underlying the polytomous response variable. The examination of DSF can provide valuable information concerning the nature of the DIF effect (i.e., is the DIF an item‐level effect or an effect isolated to specific score levels), the location of the DIF effect (i.e., precisely which score levels are manifesting the DIF effect), and the potential causes of a DIF effect (i.e., what properties of the item stem or task are potentially biasing). This article presents a didactic overview of the DSF framework and provides specific guidance and recommendations on how DSF can be used to enhance the examination of DIF in polytomous items. An example with real testing data is presented to illustrate the comprehensive information provided by a DSF analysis.  相似文献   

7.
In typical differential item functioning (DIF) assessments, an item's DIF status is not influenced by its status in previous test administrations. An item that has shown DIF at multiple administrations may be treated the same way as an item that has shown DIF in only the most recent administration. Therefore, much useful information about the item's functioning is ignored. In earlier work, we developed the Bayesian updating (BU) DIF procedure for dichotomous items and showed how it could be used to formally aggregate DIF results over administrations. More recently, we extended the BU method to the case of polytomously scored items. We conducted an extensive simulation study that included four “administrations” of a test. For the single‐administration case, we compared the Bayesian approach to an existing polytomous‐DIF procedure. For the multiple‐administration case, we compared BU to two non‐Bayesian methods of aggregating the polytomous‐DIF results over administrations. We concluded that both the BU approach and a simple non‐Bayesian method show promise as methods of aggregating polytomous DIF results over administrations.  相似文献   

8.
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   

9.
The aim of this study is to assess the efficiency of using the multiple‐group categorical confirmatory factor analysis (MCCFA) and the robust chi‐square difference test in differential item functioning (DIF) detection for polytomous items under the minimum free baseline strategy. While testing for DIF items, despite the strong assumption that all but the examined item are set to be DIF‐free, MCCFA with such a constrained baseline approach is commonly used in the literature. The present study relaxes this strong assumption and adopts the minimum free baseline approach where, aside from those parameters constrained for identification purpose, parameters of all but the examined item are allowed to differ among groups. Based on the simulation results, the robust chi‐square difference test statistic with the mean and variance adjustment is shown to be efficient in detecting DIF for polytomous items in terms of the empirical power and Type I error rates. To sum up, MCCFA under the minimum free baseline strategy is useful for DIF detection for polytomous items.  相似文献   

10.
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   

11.
Increasingly, tests are being translated and adapted into different languages. Differential item functioning (DIF) analyses are often used to identify non-equivalent items across language groups. However, few studies have focused on understanding why some translated items produce DIF. The purpose of the current study is to identify sources of differential item and bundle functioning on translated achievement tests using substantive and statistical analyses. A substantive analysis of existing DIF items was conducted by an 11-member committee of testing specialists. In their review, four sources of translation DIF were identified. Two certified translators used these four sources to categorize a new set of DIF items from Grade 6 and 9 Mathematics and Social Studies Achievement Tests. Each item was associated with a specific source of translation DIF and each item was anticipated to favor a specific group of examinees. Then, a statistical analysis was conducted on the items in each category using SIBTEST. The translators sorted the mathematics DIF items into three sources, and they correctly predicted the group that would be favored for seven of the eight items or bundles of items across two grade levels. The translators sorted the social studies DIF items into four sources, and they correctly predicted the group that would be favored for eight of the 13 items or bundles of items across two grade levels. The majority of items in mathematics and social studies were associated with differences in the words, expressions, or sentence structure of items that are not inherent to the language and/or culture. By combining substantive and statistical DIF analyses, researchers can study the sources of DIF and create a body of confirmed DIF hypotheses that may be used to develop guidelines and test construction principles for reducing DIF on translated tests.  相似文献   

12.
The study investigates consequences of eliminating items showing gender-specific differential item functioning (DIF) on the psychometric structure of a standard RIASEC interest inventory. Holland’s hexagonal model was tested for structural invariance using a confirmatory methodological approach (confirmatory factor analysis and randomization tests of hypothesized order relations). Results suggest that eliminating items showing gender-specific DIF had no considerable influence on the instrument’s psychometric structure. Considering DIF as one possibility to improve test fairness when developing interest inventories is discussed.  相似文献   

13.
Inspection of differential item functioning (DIF) in translated test items can be informed by graphical comparisons of item response functions (IRFs) across translated forms. Due to the many forms of DIF that can emerge in such analyses, it is important to develop statistical tests that can confirm various characteristics of DIF when present. Traditional nonparametric tests of DIF (Mantel-Haenszel, SIBTEST) are not designed to test for the presence of nonuniform or local DIF, while common probability difference (P-DIF) tests (e.g., SIBTEST) do not optimize power in testing for uniform DIF, and thus may be less useful in the context of graphical DIF analyses. In this article, modifications of three alternative nonparametric statistical tests for DIF, Fisher's χ 2 test, Cochran's Z test, and Goodman's U test ( Marascuilo & Slaughter, 1981 ), are investigated for these purposes. A simulation study demonstrates the effectiveness of a regression correction procedure in improving the statistical performance of the tests when using an internal test score as the matching criterion. Simulation power and real data analyses demonstrate the unique information provided by these alternative methods compared to SIBTEST and Mantel-Haenszel in confirming various forms of DIF in translated tests.  相似文献   

14.
The purpose of this article is to present logistic discriminant function analysis as a means of differential item functioning (DIF) identification of items that are polytomously scored. The procedure is presented with examples of a DIF analysis using items from a 27-item mathematics test which includes six open-ended response items scored polytomously. The results show that the logistic discriminant function procedure is ideally suited for DIF identification on nondichotomously scored test items. It is simpler and more practical than polytomous extensions of the logistic regression DIF procedure and appears to fee more powerful than a generalized Mantel-Haenszelprocedure.  相似文献   

15.
Heterogeneity within English language learners (ELLs) groups has been documented. Previous research on differential item functioning (DIF) analyses suggests that accurate DIF detection rates are reduced greatly when groups are heterogeneous. In this simulation study, we investigated the effects of heterogeneity within linguistic (ELL) groups on the accuracy of DIF detection. Heterogeneity within such groups may occur for a myriad of reasons including differential lengths of time residing in English-speaking countries, degrees of exposure to English-speaking environments, and amounts of English instruction. Our findings revealed that at high levels of within-group heterogeneity, DIF detection is at the level of chance, implying that a large proportion of DIF items might remain undetected when assessing heterogeneous populations potentially leading to developing biased tests. Based on our findings, we urge test development organizations to consider heterogeneity within ELL and other heterogeneous focus groups in their routine DIF analyses.  相似文献   

16.
There are numerous statistical procedures for detecting items that function differently across subgroups of examinees that take a test or survey. However, in endeavouring to detect items that may function differentially, selection of the statistical method is only one of many important decisions. In this article, we discuss the important decisions that affect investigations of differential item functioning (DIF) such as choice of method, sample size, effect size criteria, conditioning variable, purification, DIF amplification, DIF cancellation, and research designs for evaluating DIF. Our review highlights the necessity of matching the DIF procedure to the nature of the data analysed, the need to include effect size criteria, the need to consider the direction and balance of items flagged for DIF, and the need to use replication to reduce Type I errors whenever possible. Directions for future research and practice in using DIF to enhance the validity of test scores are provided.  相似文献   

17.
In multiple‐choice items, differential item functioning (DIF) in the correct response may or may not be caused by differentially functioning distractors. Identifying distractors as causes of DIF can provide valuable information for potential item revision or the design of new test items. In this paper, we examine a two‐step approach based on application of a nested logit model for this purpose. The approach separates testing of differential distractor functioning (DDF) from DIF, thus allowing for clearer evaluations of where distractors may be responsible for DIF. The approach is contrasted against competing methods and evaluated in simulation and real data analyses.  相似文献   

18.
Identifying the Causes of DIF in Translated Verbal Items   总被引:1,自引:0,他引:1  
Translated tests are being used increasingly for assessing the knowledge and skills of individuals who speak different languages. There is little research exploring why translated items sometimes function differently across languages. If the sources of differential item functioning (DIF) across languages could be predicted, it could have important implications on test development, scoring and equating. This study focuses on two questions: “Is DIF related to item type?”, “What are the causes of DIF?” The data were taken from the Israeli Psychometric Entrance Test in Hebrew (source) and Russian (translated). The results indicated that 34% of the items functioned differentially across languages. The analogy items were the most problematic with 65% showing DIF, mostly in favor of the Russian-speaking examinees. The sentence completion items were also a problem (45% D1F). The main reasons for DIF were changes in word difficulty, changes in item format, differences in cultural relevance, and changes in content.  相似文献   

19.
Even if national and international assessments are designed to be comparable, subsequent psychometric analyses often reveal differential item functioning (DIF). Central to achieving comparability is to examine the presence of DIF, and if DIF is found, to investigate its sources to ensure differentially functioning items that do not lead to bias. In this study, sources of DIF were examined using think-aloud protocols. The think-aloud protocols of expert reviewers were conducted for comparing the English and French versions of 40 items previously identified as DIF (N?=?20) and non-DIF (N?=?20). Three highly trained and experienced experts in verifying and accepting/rejecting multi-lingual versions of curriculum and testing materials for government purposes participated in this study. Although there is a considerable amount of agreement in the identification of differentially functioning items, experts do not consistently identify and distinguish DIF and non-DIF items. Our analyses of the think-aloud protocols identified particular linguistic, general pedagogical, content-related, and cognitive factors related to sources of DIF. Implications are provided for the process of arriving at the identification of DIF, prior to the actual administration of tests at national and international levels.  相似文献   

20.
This study investigated differential item functioning (DIF), differential bundle functioning (DBF), and differential test functioning (DTF) across gender of the reading comprehension section of the Graduate School Entrance English Exam in China. The datasets included 10,000 test-takers’ item-level responses to 6 five-item testlets. Both DIF and DBF were examined by using poly-simultaneous item bias test and item-response-theory-likelihood-ratio test, and DTF was investigated with multi-group confirmatory factor analyses (MG-CFA). The results indicated that although none of the 30 items exhibited statistically and practically significant DIF across gender at the item level, 2 testlets were consistently identified as having significant DBF at the testlet level by the two procedures. Nonetheless, DBF does not manifest itself at the overall test score level to produce DTF based on MG-CFA. This suggests that the relationship between item-level DIF and test-level DTF is a complicated issue with the mediating effect of testlets in testlet-based language assessment.  相似文献   

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