项目功能差异在跨文化人格问卷分析中的应用

利用IRT的等级模型调查了中日两组被试关于SHIBA简易人格量表中“环境敏感性”的项目功能差异(DIF)的现状。研究发现：（1）量表中DIF的项目比例大(3/4);（2）DIF与项目内容、阈值有关而与区分度大小关系不大;（3）DIF项目间的日方特征曲线较之中方有较强的整合性。该研究利用DIF研究结果对跨文化的人格比较作了新尝试。最后提出了关于深化DIF研究的新课题     

Differential item functioning in an international 360-degree assessment: Evidence of gender stereotype,environmental complexity,and organizational contingency

This research used logistic regression to model item responses from a popular 360-degree-for-development survey used in a leadership development programme given to middle and upper level European managers in Brussels. The survey contained 106 items on 16 scales. The model used gender of ratee and rater group to identify items that exhibited differential item functioning (DIF). The rater groups were self, boss, peer, and direct report. The sample consisted of 356 survey families where a survey family consisted of a matched set of four surveys: one self, one boss, one peer, and one direct report. The sample contained 88% male and 12% female raters. The sample contained 1424 total surveys. The procedure for flagging items exhibiting differential functioning used effect size computed from Wald chi-square statistics rather than statistical significance, resulting in fewer flagged items. One item exhibited rating anomalies due to the gender of the ratee; 55 items exhibited DIF attributable to rater group. The apparent effect of the DIF was small with each item. An examination of the maximum likelihood parameter estimates suggested the rater group DIF was the result of either hierarchical complexity or organizational contingency. The DIF due to gender conformed to prior expectations of gender-related stereotypical interpretations. This research further suggested that DIF due to environmental complexity or organizational contingency could be a naturally occurring phenomenon in some 360-degree assessment, and that the interpretation of some 360-degree feedback could need to include the potential for such DIF to exist.     

A model-based standardization approach that separates true bias/DIF from group ability differences and detects test bias/DTF as well as item bias/DIF

A model-based modification (SIBTEST) of the standardization index based upon a multidimensional IRT bias modeling approach is presented that detects and estimates DIF or item bias simultaneously for several items. A distinction between DIF and bias is proposed. SIBTEST detects bias/DIF without the usual Type 1 error inflation due to group target ability differences. In simulations, SIBTEST performs comparably to Mantel-Haenszel for the one item case. SIBTEST investigates bias/DIF for several items at the test score level (multiple item DIF called differential test functioning: DTF), thereby allowing the study of test bias/DIF, in particular bias/DIF amplification or cancellation and the cognitive bases for bias/DIF.This research was partially supported by Office of Naval Research Cognitive and Neural Sciences Grant N0014-90-J-1940, 4421-548 and National Science Foundation Mathematics Grant NSF-DMS-91-01436. The research reported here is collaborative in every respect and the order of authorship is alphabetical. The assistance of Hsin-hung Li and Louis Roussos in conducting the simulation studies was of great help. Discussions with Terry Ackerman, Paul Holland, and Louis Roussos were very helpful.     

汉语词汇测验中的项目功能差异初探

该文运用两种不同的方法对实际的汉语词汇测验中的３６个词汇进行了ＤＩＦ探测。对于１４００多劬的初三学生分别作了男女生与城郊学生间的比较。在男女组分析中检出７个属于一致性ＤＩＦ的项目;对于城郊学生组经两种方法同时确定的ＤＩＦ项目有７个,其中５个是一致性ＤＩＦ,２个是非一致性ＤＩＦ的项目。该文还讨论了产生ＤＩＦ的可能因素。     

认知诊断测验中基于信息矩阵的多群组DIF检验

基于改进的Wald统计量,将适用于两群组的DIF检测方法拓展至多群组的项目功能差异（DIF）检验;改进的Wald统计量将分别通过计算观察信息矩阵（Obs）和经验交叉相乘信息矩阵（XPD）而得到。模拟研究探讨了此二者与传统计算方法在多个群组下的DIF检验情况,结果表明：（1）Obs和XPD的一类错误率明显低于传统方法,DINA模型估计下Obs和XPD的一类错误率接近理论水平;（2）样本量和DIF量较大时,Obs和XPD具有与传统Wald统计量大体相同的统计检验力。     

ASSESSING THE EFFECT OF COHORT,GENDER, AND RACE ON DIFFERENTIAL ITEM FUNCTIONING (DIF) IN AN ADAPTIVE TEST DESIGNED FOR MULTI-AGE GROUPS

Differential item functioning (DIF) statistics were computed using items from the Peabody Individual Achievement Test (PIAT)-Reading Comprehension subtest for children of the same age group (ages 7 through 12 respectively). The pattern of observed DIF items was determined by comparing each cohort across age groups. Differences related to race and gender were also identified within each cohort. Characteristics of DIF items were identified based on sentence length, vocabulary frequency, and density of a sentence. DIF items were more frequently associated with short sentences than with long sentences. This study explored the potential limitation in the longitudinal use of items in an adaptive test.     

Identification of Differential Item Functioning in Multiple-Group Settings: A Multivariate Outlier Detection Approach

We focus on the identification of differential item functioning (DIF) when more than two groups of examinees are considered. We propose to consider items as elements of a multivariate space, where DIF items are outlying elements. Following this approach, the situation of multiple groups is a quite natural case. A robust statistics technique is proposed to identify DIF items as outliers in the multivariate space. For low dimensionalities, up to 2–3 groups, a simple graphical tool is derived. We illustrate our approach with a reanalysis of data from Kim, Cohen, and Park (1995) on using calculators for a mathematics test.     

Improvement in Detection of Differential Item Functioning Using a Mixture Item Response Theory Model

Usually, methods for detection of differential item functioning (DIF) compare the functioning of items across manifest groups. However, the manifest groups with respect to which the items function differentially may not necessarily coincide with the true source of the bias. It is expected that DIF detection under a model that includes a latent DIF variable is more sensitive to this source of bias. In a simulation study, it is shown that a mixture item response theory model, which includes a latent grouping variable, performs better in identifying DIF items than DIF detection methods using manifest variables only. The difference between manifest and latent DIF detection increases as the correlation between the manifest variable and the true source of the DIF becomes smaller. Different sample sizes, relative group sizes, and significance levels are studied. Finally, an empirical example demonstrates the detection of heterogeneity in a minority sample using a latent grouping variable. Manifest and latent DIF detection methods are applied to a Vocabulary test of the General Aptitude Test Battery (GATB).     

Measurement of Depressive Symptoms in Women With Breast Cancer and Women With Clinical Depression: A Differential Item Functioning Analysis

Differential item functioning (DIF) analyses of the Beck Depression Inventory-II (BDI-II) were conducted on samples of 267 women with breast cancer and 294 women with clinical depression. Patterns of items in which there was significant and nonsignificant DIF were identified using statistical tests and measures of DIF effect size. At the most general level, 15 of 21 BDI-II items were associated with nontrivial DIF suggesting that the item responses of these samples do not reflect the same underlying construct. Factor analyses of the BDI-II using a psychometrically defensible method for item level factor analysis supported the conclusions from the DIF analyses. These findings suggest that researchers and practitioners should apply caution when interpreting self-report depression symptoms in breast cancer patients.     

Item-focussed Trees for the Identification of Items in Differential Item Functioning

A novel method for the identification of differential item functioning (DIF) by means of recursive partitioning techniques is proposed. We assume an extension of the Rasch model that allows for DIF being induced by an arbitrary number of covariates for each item. Recursive partitioning on the item level results in one tree for each item and leads to simultaneous selection of items and variables that induce DIF. For each item, it is possible to detect groups of subjects with different item difficulties, defined by combinations of characteristics that are not pre-specified. The way a DIF item is determined by covariates is visualized in a small tree and therefore easily accessible. An algorithm is proposed that is based on permutation tests. Various simulation studies, including the comparison with traditional approaches to identify items with DIF, show the applicability and the competitive performance of the method. Two applications illustrate the usefulness and the advantages of the new method.     

Differential item functioning by sex and race in the Hogan Personality Inventory

The authors examined measurement bias in the Hogan Personality Inventory by investigating differential item functioning (DIF) across sex and two racial groups (Caucasian and Black). The sample consisted of 1,579 Caucasians (1,023 men, 556 women) and 523 Blacks (321 men, 202 women) who were applying for entry-level, unskilled jobs in factories. Although the group mean differences were trivial, more than a third of the items showed DIF by sex (38.4%) and by race (37.3%). A content analysis of potentially biased items indicated that the themes of items displaying DIF were slightly more cohesive for sex than for race. The authors discuss possible explanations for differing clustering tendencies of items displaying DIF and some practical and theoretical implications of DIF in the development and interpretation of personality inventories.     

Optimal Items for Assessing Parental Involvement across Different Groups During Middle Childhood

Various definitions and different approaches for assessing the complex construct of parental involvement (PI) have led to inconsistent findings regarding the impact of PI on child development. To date, limited information is available regarding the measurement invariance of PI measures across time and groups (e.g., children’s gender, ethnicity, and socio-economic status), leaving a concern that group differences in PI might reflect item bias instead of true differences in PI. The present study aimed to obtain a set of optimal items for measuring PI from kindergarten through the elementary school years and investigate whether they could be used for parents from different groups. A Rasch measurement model was implemented to investigate item difficulty, step calibrations, and measurement invariance (differential item functioning; DIF, here). The results from the Early Childhood Longitudinal Study, Kindergarten Class of 1998–1999 data set showed that 20 items can be used to measure three dimensions of PI—namely school/home involvement, family educational investment, and family routines—across four time points. Administrative time, children’s gender, ethnicity, and social economic status showed different levels of effect on item difficulty for half of these items. Practitioners and researchers should be cautious when using these items and are suggested to freely estimate the item parameters of DIF items as well as add more items to the PI scale to improve reliability.     

Enhancing measurement validity in diverse populations: Modern approaches to evaluating differential item functioning

When developing and evaluating psychometric measures, a key concern is to ensure that they accurately capture individual differences on the intended construct across the entire population of interest. Inaccurate assessments of individual differences can occur when responses to some items reflect not only the intended construct but also construct-irrelevant characteristics, like a person's race or sex. Unaccounted for, this item bias can lead to apparent differences on the scores that do not reflect true differences, invalidating comparisons between people with different backgrounds. Accordingly, empirically identifying which items manifest bias through the evaluation of differential item functioning (DIF) has been a longstanding focus of much psychometric research. The majority of this work has focused on evaluating DIF across two (or a few) groups. Modern conceptualizations of identity, however, emphasize its multi-determined and intersectional nature, with some aspects better represented as dimensional than categorical. Fortunately, many model-based approaches to modelling DIF now exist that allow for simultaneous evaluation of multiple background variables, including both continuous and categorical variables, and potential interactions among background variables. This paper provides a comparative, integrative review of these new approaches to modelling DIF and clarifies both the opportunities and challenges associated with their application in psychometric research.     

经济法试题DIF的参数法检测研究

该研究基于项目反应理论的Samejima等级反应模型(GRM),在MULTILOG软件支持下,应用参数检测方法,对某年度全国性资格考试的某科目试卷中经济法部分的21个项目做了DIF检测分析。结果如下:存在性别DIF的项目一个,存在民族DIF的项目四个,存在工作性质DIF的项目一个。其中项目68在民族层面上表现为一致性DIF,项目64既存在民族DIF又存在工作性质DIF。通过对项目统计量、反应曲线的分析和专家的讨论,文章最后还分析了产生这些DIF的几个可能的原因。     

A new approach for differential item functioning detection using Mantel-Haenszel methods. The GMHDIF program

To date, the statistical software designed for assessing differential item functioning (DIF) with Mantel-Haenszel procedures has employed the following statistics: the Mantel-Haenszel chi-square statistic, the generalized Mantel-Haenszel test and the Mantel test. These statistics permit detecting DIF in dichotomous and polytomous items, although they limit the analysis to two groups. On the contrary, this article describes a new approach (and the related software) that, using the generalized Mantel-Haenszel statistic proposed by Landis, Heyman, and Koch (1978), permits DIF assessment in multiple groups, both for dichotomous and polytomous items. The program is free of charge and is available in the following languages: Spanish, English and Portuguese.     

Uncovering Substantive Patterns in Student Responses in International Large-Scale Assessments—Comparing a Latent Class to a Manifest DIF Approach

In this study, we contrast results from two differential item functioning (DIF) approaches (manifest and latent class) by the number of items and sources of items identified as DIF using data from an international reading assessment. The latter approach yielded three latent classes, presenting evidence of heterogeneity in examinee response patterns. It also yielded more DIF items with larger effect sizes and more consistent item response patterns by substantive aspects (e.g., reading comprehension processes and cognitive complexity of items). Based on our findings, we suggest empirically evaluating the homogeneity assumption in international assessments because international populations cannot be assumed to have homogeneous item response patterns. Otherwise, differences in response patterns within these populations may be under-detected when conducting manifest DIF analyses. Detecting differences in item responses across international examinee populations has implications on the generalizability and meaningfulness of DIF findings as they apply to heterogeneous examinee subgroups.     

Do Raven's Colored Progressive Matrices function in the same way in typical and clinical populations? Insights from the intellectual disability field

Standardized tests are used widely in comparative studies of clinical populations, either as dependent or control variables. Yet, one cannot always be sure that the test items measure the same constructs in the groups under study. In the present work, 460 participants with intellectual disability of undifferentiated etiology and 488 typical children were tested using Raven's Colored Progressive Matrices (RCPM). Data were analyzed using binomial logistic regression modeling designed to detect differential item functioning (DIF). Results showed that 12 items out of 36 function differentially between the two groups, but only 2 items exhibit at least moderate DIF. Thus, a very large majority of the items have identical discriminative power and difficulty levels across the two groups. It is concluded that RCPM can be used with confidence in studies comparing participants with and without intellectual disability. In addition, it is suggested that methods for investigating internal bias of tests used in cross-cultural, cross-linguistic or cross-gender comparisons should also be regularly employed in studies of clinical populations, particularly in the field of developmental disability, to show the absence of systematic measurement error (i.e. DIF) affecting item responses.     

Assessing differential functioning in a satisfaction scale

In this study, an item response theory-based differential functioning of items and tests (DFIT) framework (N. S. Raju, W. J. van der Linden, & P. F. Fleer, 1995) was applied to a Likert-type scale. Several differential item functioning (DIF) analyses compared the item characteristics of a 10-item satisfaction scale for Black and White examinees and for female and male examinees. F. M. Lord's (1980) chi-square and the extended signed area (SA) measures were also used. The results showed that the DFIT indices consistently performed in the expected manner. The results from Lord's chi-square and the SA procedures were somewhat varied across comparisons. A discussion of these results along with an illustration of an item with significant DIF and suggestions for future DIF research are presented.     

Effects of Differential Item Functioning on Examinees' Test Performance and Reliability of Test

Simulations were conducted to examine the effect of differential item functioning (DIF) on measurement consequences such as total scores, item response theory (IRT) ability estimates, and test reliability in terms of the ratio of true-score variance to observed-score variance and the standard error of estimation for the IRT ability parameter. The objective was to provide bounds of the likely DIF effects on these measurement consequences. Five factors were manipulated: test length, percentage of DIF items per form, item type, sample size, and level of group ability difference. Results indicate that the greatest DIF effect was less than 2 points on the 0 to 60 total score scale and about 0.15 on the IRT ability scale. DIF had a limited effect on the ratio of true-score variance to observed-score variance, but its influence on the standard error of estimation for the IRT ability parameter was evident for certain ability values.