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Large-Scale Assessments in Germany have shown that language-minority students as well as students with special educational needs (SEN) perform significantly less well than language-majority students or students without SEN. This performance gap may be related to a limited accessibility of the tests. One way to test whether assessments allow all students to demonstrate their knowledge in a comparable way is the analysis of differential item functioning (DIF). In this chapter, we evaluate DIF coefficients in order to examine group-specific difficulties in reading comprehension for language-minority students and students with SEN in the German National Educational Assessment.

In the first study, we investigate the assessment of reading literacy of language-minority learners and German monolinguals from low-SES families. We found only a few items with moderate DIF and no items with large DIF. This indicates that the reading assessment was equally valid for second-language learners and German monolingual students.

In our second study, we report about the psychometrically successful development of easy and more accessible reading tasks for students with SEN. Further analyses showed that DIF predominantly occurred in items that captured contents that are not necessarily covered in literacy instruction targeted at students with SEN.

The purpose of this chapter is to provide researchers a summary of some of the latest developments in item response theory (IRT), and to help these groups realize that psychometric tools can now be used for theory testing in addition to the traditional role of improving construct measurement. The author first reviews some of the fundamental tenets of classical test theory to contrast with IRT. He then describes recent advances in goodness-of-fit tests that have helped turn IRT into a model-testing tool. Finally, the author reviews several new test models that provide new flexibilities, summarizing summarize several examples of research that has used these new models in organizational research. At the end of this review, the author provides suggestions to help researchers better use these new IRT tools. Although there have been significant advances in IRT in the past decade, there has not been a systematic review of these developments. This review places those developments in context to provide readers a real appreciation of these breakthroughs.

Measures are comparable if and only if measurement equivalence has been demonstrated. Although comparability and equivalence of measures are sometimes used interchangeably, we advocate a subtle but important difference in meaning. Comparability implies that measures from one group can be compared with measures from another group. It is a property of the measures, which is given or not. In particular, comparability presumes valid measures within each group compared. Measurement equivalence, by contrast, refers to the way measures are derived and estimated. It is intrinsically tied to the underlying theory of measurement. Thus, measurement equivalence cannot be dealt with in isolation. Its assessment has to be incorporated into the theoretical framework of measurement. Measurement equivalence is closely connected to construct validity for it refers to the way manifest indicators are related to the latent variable, within a particular culture and across different cultures. From this it follows that equivalence cannot, or should not, be treated as a separate issue but as a constitutive element of validity. A discussion of measurement equivalence without addressing validity would be incomplete.

Economic globalization is leading large companies to focus on international strategic management. Nowadays, the assets referred to as “corporate intangibles,” such as corporate reputation, are becoming increasingly important because they are considered a key factor for the viability of an organization, and companies therefore need to incorporate them into their scorecards for management. The problem is that their measurement is subjective and latent. These two characteristics impede direct international comparison and require demonstrating the accuracy of comparison via a minimum of two tests – construct equivalence and metric equivalence. As regards corporate reputation, construct equivalence was verified by Naomi Gardberg (2006). However, the subsequent studies did not address metric equivalence. Based on the results of a survey provided by the Reputation Institute (n = 5,950, 50 firms evaluated in 17 countries in the Americas, Europe, Asia and Australia), the degree of RepTrak metric equivalence has been tested, using two different methodologies, multigroup analysis (structural equation model), and a new technique from 2016, the Measurement Invariance of Composite Model procedure from the Partial Least Square Path Modeling family. As one would expect from other cross-cultural studies, reputation metrics do not meet the full metric equivalence, which is why they require standardization processes to ensure international comparability. Both methodologies have identified the same correction parameters, which have allowed validation of the mean and variance of response style by country.

This chapter reviews key research on the similarities and differences in leadership and management across different regions of the world. It also looks at similarities and differences on other relevant aspects, that is, commitment, work values, personality and emotional intelligence. Research has tended to focus on drawing out the differences as that appears to be worthy of news and attracts interest. We also report on the types of errors in research which might actually make real differences appear much larger. The reality is that what we find is a great deal of similarity in leadership and management behaviour across the different regions of the world. Given these similarities, can we develop a management level Situational Judgment Test (SJT) that can be used effectively across different world regions? We believe this can be achieved by identifying SJT items that work consistently across world regions and then assembling a bias-free test with robust psychometric properties.