In the field of international educational surveys, equivalence of achievement scale scores across countries has received substantial attention in the academic literature; however, only a relatively recent emphasis on scale score equivalence in nonachievement education surveys has emerged. Given the current state of research in multiple-group models, findings regarding these recent measurement invariance investigations were supported with research that was limited in scope to few groups and relatively small sample sizes. To that end, this study uses data from one large-scale survey as a basis for examining the extent to which typical fit measures used in multiple-group confirmatory factor analysis are suitable for detecting measurement invariance in a large-scale survey context. Using measures validated in a smaller scale context and an empirically grounded simulation study, our findings indicate that many typical measures and associated criteria are either unsuitable in a large group and varied sample-size context or should be adjusted, particularly when the number of groups is large. We provide specific recommendations and discuss further areas for research.

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The technical complexities and sheer size of international large-scale assessment (LSA) databases often cause hesitation on the part of the applied researcher interested in analyzing them. Further, inappropriate choice or application of statistical methods is a common problem in applied research using these databases. This article serves as a primer for researchers on the issues and methods necessary for obtaining unbiased results from LSA data. The authors outline the issues surrounding the analysis and reporting of LSA data, with a particular focus on three prominent international surveys. In addition, they make recommendations targeted at applied researchers regarding best analysis and reporting practices when using these databases.

As part of its flagship educational study -the Programme for International Student Assessment (PISA) -the Organisation for Economic Co-operation and Development (OECD) has undertaken extensive work to create an internationally relevant composite indicator aimed at measuring socioeconomic background. However, the degree to which a single measure of socioeconomic background is reliable and valid for all participating countries is not widely discussed. To fill this gap, the authors examine the home possessions index, which is a key component of PISA's socioeconomic indicator, and highlight a number of issues surrounding this index. In particular, they take a psychometric approach to investigating the reliability and some facets of the validity of the home possessions index in a number of participating PISA countries. Their findings suggest that there are notable concerns with the current index, including highly variable reliability by country, poor modelto-data consistency on a number of subscales, and evidence of poor cultural comparability. They couch their discussion in the context of educational and policy research and propose one possible method for improving these measures for participating countries.