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Aims The Strengths and Difficulties Questionnaire (SDQ) has been used in many epidemiological studies to assess adolescent mental health problems, but cross-country comparisons of the self-report SDQ are scarce and so far failed to find a good-fitting, common, invariant measurement model across countries. The present study aims to evaluate and establish a version of the self-report SDQ that allows for a valid cross-country comparison of adolescent self-reported mental health problems. Methods Using the Health Behaviour in School-aged Children study, the measurement model and measurement invariance of the 20 items of the self-report SDQ measuring adolescent mental health problems were evaluated. Nationally representative samples of 11-, 13- and 15-year old adolescents (n = 33 233) from seven countries of different regions in Europe (Bulgaria, Germany, Greece, the Netherlands, Poland, Romania, Slovenia) were used. Results In order to establish a good-fitting and common measurement model, the five reverse worded items of the self-report SDQ had to be removed. Using this revised version of the self-report SDQ, the SDQ-R, partial measurement invariance was established, indicating that latent factor means assessing conduct problems, emotional symptoms, peer relationships problems and hyperactivity-inattention problems could be validly compared across the countries in this study. Results showed that adolescents in Greece scored relatively low on almost all problem subscales, whereas adolescents in Poland scored relatively high on almost all problem subscales. Adolescents in the Netherlands reported the most divergent profile of mental health problems with the lowest levels of conduct problems, low levels of emotional symptoms and peer relationship problems, but the highest levels of hyperactivity-inattention problems. Conclusions With six factor loadings being non-invariant, partial measurement invariance was established, indicating that the 15-item SDQ-R could be used in our cross-country comparison of adolescent mental health problems. To move the field of internationally comparative research on adolescent mental health forward, studies should test the applicability of the SDQ-R in other countries in- and outside Europe, continue to develop the SDQ-R as a cross-country invariant measure of adolescent mental health, and examine explanations for the found country differences in adolescent mental health problems.

The present paper contrasts two related criteria for the evaluation of prior-data conflict: the Data Agreement Criterion (DAC, Bousquet, 2008) and the criterion of Nott et al. (2016). One aspect that these criteria have in common is that they depend on a distance measure, of which dozens are available, but so far, only the Kullback-Leibler has been used. We describe and compare both criteria to determine whether a different choice of distance measure might impact the results. By means of a simulation study, we investigate how the choice of a specific distance measure influences the detection of prior-data conflict. The DAC seems more susceptible to the choice of distance measure, while the criterion of Nott et al. seems to lead to reasonably comparable conclusions of prior-data conflict, regardless of the distance measure choice. We conclude with some practical suggestions for the user of the DAC and the criterion of Nott et al.

This chapter focuses on a practical analysis of the Bayesian approximate measurement invariance model using standard software. It introduces the concept of approximate measurement invariance and illustrates the use of its most basic variant. The chapter discusses the use of measurement invariance testing in latent variable measurement models. In such models, the response functions are estimated through presumed conditional independence assumptions, and investigation of measurement invariance proceeds through restrictions on the parameters of these estimated functions. The most common model for this test is the confirmatory factor model, but this framework also includes item response theory (IRT) models, latent class models, and generalized multitrait‐multimethod models. The chapter focuses on a multigroup confirmatory factor analysis (MGCFA). The methodological literature on cross‐cultural and cross‐country analysis has recommended testing for measurement equivalence to guarantee that differences across groups are due to substantive true differences and not methodological artifacts

Het 95% betrouwbaarheidsinterval in de verslaglegging van intelligentietests kan grofweg geïnterpreteerd worden als een soort ‘foutenmarge’ rondom de verkregen IQ-score van het kind. De exacte interpretatie ligt ingewikkelder. Genoemd interval staat er dan ook om bekend vaak verkeerd geïnterpreteerd te worden. Daarom bieden Kimberley Lek en collega’s een ‘opfrisser’: hoe wordt een betrouwbaarheidsinterval ook al weer opgesteld ? De WISC-IIInl wordt gebruikt ter illustratie.