A new method for detecting differential item functioning in the Rasch model

Differential item functioning (DIF) can lead to an unfair advantage or disadvantage for certain subgroups in educational and psychological testing. Therefore, a variety of statistical methods has been suggested for detecting DIF in the Rasch model. Most of these methods are designed for the comparison of pre-specified focal and reference groups, such as males and females. Latent class approaches, on the other hand, allow to detect previously unknown groups exhibiting DIF. However, this approach provides no straightforward interpretation of the groups with respect to person characteristics. Here we propose a new method for DIF detection based on model-based recursive partitioning that can be considered as a compromise between those two extremes. With this approach it is possible to detect groups of subjects exhibiting DIF, which are not prespecified, but result from combinations of observed covariates. These groups are directly interpretable and can thus help understand the psychological sources of DIF. The statistical background and construction of the new method is first introduced by means of an instructive example, and then applied to data from a general knowledge quiz and a teaching evaluation

Anchor methods for DIF detection: A comparison of the iterative forward, backward, constant and all-other anchor class

In the analysis of differential item functioning (DIF) using item response theory (IRT), a common metric is necessary to compare item parameters between groups of test-takers. In the Rasch model, the same restriction is placed on the item parameters in each group in order to define a common metric. However, the question how the items in the restriction - termed anchor items - are selected appropriately is still a major challenge. This article proposes a conceptual framework for categorizing anchor methods: The anchor class to describe characteristics of the anchor methods and the anchor selection strategy to guide how the anchor items are determined. Furthermore, a new anchor class termed the iterative forward anchor class is proposed. Several anchor classes are implemented with two different anchor selection strategies (the all-other and the single-anchor selection strategy) and are compared in an extensive simulation study. The results show that the newly proposed anchor class combined with the single-anchor selection strategy is superior in situations where no prior knowledge about the direction of DIF is available. Moreover, it is shown that the proportion of DIF items in the anchor - rather than the fact whether the anchor includes DIF items at all (termed contamination in previous studies) - is crucial for suitable DIF analysis

Anchor selection strategies for DIF analysis: Review, assessment, and new approaches

Differential item functioning (DIF) indicates the violation of the invariance assumption for instance in models based on item response theory (IRT). For item-wise DIF analysis using IRT, a common metric for the item parameters of the groups that are to be compared (e.g. for the reference and the focal group) is necessary. In the Rasch model, therefore, the same linear restriction is imposed in both groups. Items in the restriction are termed the anchor items. Ideally, these items are DIF-free to avoid artificially augmented false alarm rates. However, the question how DIF-free anchor items are selected appropriately is still a major challenge. Furthermore, various authors point out the lack of new anchor selection strategies and the lack of a comprehensive study especially for dichotomous IRT models. This article reviews existing anchor selection strategies that do not require any knowledge prior to DIF analysis, offers a straightforward notation and proposes three new anchor selection strategies. An extensive simulation study is conducted to compare the performance of the anchor selection strategies. The results show that an appropriate anchor selection is crucial for suitable item-wise DIF analysis. The newly suggested anchor selection strategies outperform the existing strategies and can reliably locate a suitable anchor when the sample sizes are large enough

A new method for detecting differential item functioning in the Rasch model

Differential item functioning (DIF) can lead to an unfair advantage or disadvantage for certain subgroups in educational and psychological testing. Therefore, a variety of statistical methods has been suggested for detecting DIF in the Rasch model. Most of these methods are designed for the comparison of pre-specified focal and reference groups, such as males and females. Latent class approaches, on the other hand, allow to detect previously unknown groups exhibiting DIF. However, this approach provides no straightforward interpretation of the groups with respect to person characteristics. Here we propose a new method for DIF detection based on model-based recursive partitioning that can be considered as a compromise between those two extremes. With this approach it is possible to detect groups of subjects exhibiting DIF, which are not prespecified, but result from combinations of observed ovariates. These groups are directly interpretable and can thus help understand the psychological sources of DIF. The statistical background and construction of the new method is first introduced by means of an instructive example, and then applied to data from a general knowledge quiz and a teaching evaluation.item response theory, IRT, Rasch model, di erential item functioning, DIF, structural change, multidimensionality.

Geotechnical characterization of trench- and slope sediments off Southern Chile: preliminary results

To understand seismogenesis in shallow parts of subduction zones, it is vital to know about strength and frictional parameters of subducted sediment. For this purpose, PETROTEC, as part of the TIPTEQ-Project, gathers geotechnical data for sediments deposited on the incoming Nazca Plate, the trench and the slope off the southern Chilean coast during the last 5 Ma, and whose equivalents are now being underthrusted into the seismogenic zone beneath South America. Material comes from gravity cores collected during R/V SONNE Cruises SO181 (Flüh E. & Grevemeyer I (Editors) 2005), SO102 (Hebbeln D, Wefer G, et al. 1995) and SO156 (Hebbeln D, et al. 2001), as well as from ODP Leg 141 (Behrmann JH, et al. 1992) drill cores. Sediment strength and frictional properties are determined by triaxial testing, ring shear testing and direct shear testing...conferenc

The role of compaction contrasts in sediments in décollement initiation in an accretionary prism

International audienceTo understand how décollements develop into the pristine sedimentary succession entering subduction zones, we have performed mechanical tests on samples from the sediment column entering the Nankai accretionary prism, Japan (ODP site 1173). Both poroelastic compliance and plastic shrinkage upon application of a large effective pressure sharply decrease with depth in a ~ 100 m-thick domain in the upper section of the Lower Shikoku Basin unit, i.e. in a domain stratigraphically close to the actual location of the décollement near the toe of the prism. These property contrasts provide a potential explanation for the outward migration of the décollement into the incoming sediments. When approaching the deformation front, a given material particle is affected by an increase in stress, which has a component of vertical loading due to the deposition of overburden trench sediment, and also a component of lateral compression transmitted from the accretionary wedge. Depending on its initial mechanical state, the amount of lateral shortening in the incoming Nankai sediment column varies with depth and causes horizontal velocity gradients that concentrate into the mechanical transition zone (upper section of the Lower Shikoku Basin at appx. 450-550 m depth) into which the décollement eventually propagates. Future work has to assess the role of this plastic deformation relative to other governing factors such as friction coefficient and excess pore pressure, both at Nankai and along other active margins