The Programme for International Student Assessment (PISA) introduced creative thinking as an innovative domain in 2022. This paper examines the unique methodological issues in international assessments and the implications of measuring creative thinking within PISA's framework, including stratified sampling, rotated form designs, and a distinct…

While the use of inferential statistics is a nearly universal practice in the social sciences, there are instances where its application is unnecessary and potentially misleading. This is true for a portion of research using administrative data in educational research in the United States. Surveying all research articles using administrative data…

Data transformations have been promoted as a popular and easy-to-implement remedy to address the assumption of normally distributed errors (in the population) in linear regression. However, the application of data transformations introduces non-ignorable complexities which should be fully appreciated before their implementation. This paper adds to…

Null hypothesis significance testing (NHST) has been the subject of debate for decades and alternative approaches to data analysis have been proposed. This article addresses this debate from the perspective of scientific inquiry and inference. Inference is an inverse problem and application of statistical methods cannot reveal whether effects…

Null hypothesis significance testing has dominated quantitative research in education and psychology. However, the statistical significance of a test as indicated by a p-value does not speak to the practical significance of the study. Thus, reporting effect size to supplement p-value is highly recommended by scholars, journal editors, and academic…

Institutional researchers frequently use national datasets such as those provided by the National Center for Education Statistics (NCES). The authors of this chapter explore the adjustments required when analyzing NCES data collected using complex sample designs. (Contains 8 tables.)