Causal inferences with cross-sectional large scale assessment data
Edited by Leslie Rutkowski, University of Oslo, Norway
In this special issue of Large-Scale Assessments in Education, we offer several papers on the topic of causal inferences with international large-scale assessment (ILSA) data. The papers here are primarily empirical analyses of ILSA data that feature different methods, all with an aim toward estimating the effect of some cause. Each paper also includes a brief introduction to the method at hand along with a discussion of the important statistical assumptions that underpin each method and whether or not the assumptions are plausible in the given circumstance. Although the treatment is selective, the methods featured here are commonly used in practice and serve as a useful introduction to specific methods of data analysis applied in a quasi-experimental context. Important to keep in mind is that the implemented methods are applied to observational data, most of which are also cross-sectional. The paper by Rutkowski and Delandshere balances the empirical offerings by taking a critical perspective on drawing causal inferences through the lens of a validity framework.