The robustness of qualitative comparative analysis (QCA) results features high on the agenda of methodologists and practitioners. This article aims at advancing this debate on several fronts. First, in line with the extant literature, we take a comprehensive view on robustness arguing that decisions on calibration, consistency, and frequency…

Statistical tables associated with named probability distributions and their families, such as the standard normal, Student's t, and chi-square tables, among others, have been utilized for years and are still widely used today, especially for mathematics and statistics education. While such tables can be found in many statistics textbooks and even…

Data visualization enables users to transform data into visually compelling graphics that tell a rich story for effective communication (Vora, 2019). Data visualization's visual and artistic nature has also attracted artists and educators, leading them to explore its application in artistic creation and education (e.g., Bertling et al., 2021; Dean…

Qualitative Comparative Analysis (QCA) is a relatively young method of causal inference that continues to diffuse across the social sciences. However, recent methodological research has found the conservative (QCA-CS) and the intermediate solution type (QCA-IS) of QCA to fail fundamental tests of correctness. Even under conditions otherwise ideal…

Mixed methods, cross-cultural designs are a special case of the more general, mixed methods between-groups designs. The defining feature of mixed methods is the principled integration of qualitative and quantitative approaches, and cross-cultural comparison is premised on the systematic collection and analysis of data from two or more cultural…

While score comparability across test forms typically relies on common (or randomly equivalent) examinees or items, innovations in item formats, test delivery, and efforts to extend the range of score interpretation may require a special data collection before examinees or items can be used in this way--or may be incompatible with common examinee…

Peter Dunn and Margaret Marshman present the second of their data files articles in which they discuss the statistical investigation cycle which describes the whole process of conducting a statistical research study. [For "The Data Files: A Series of Articles to Support Mathematics Teachers to Teach Statistics," see EJ1259108.]

It is widely believed that regression models for binary responses are problematic if we want to compare estimated coefficients from models for different groups or with different explanatory variables. This concern has two forms. The first arises if the binary model is treated as an estimate of a model for an unobserved continuous response and the…

Social research is rich in methods for analysing societal differences. Yet, although qualitative characteristics are a key component to understanding such differences, the analysis of qualitative data remains a major methodological challenge in most social research, particularly when aiming to compare more than a few cases. The article proposes an…

The collection of data by government authorities has a complex history. In Australia, this began with the establishment of British government settlements as a way to account for fiscal viability and social prospects. As the colonies became self-governing entities, the collection of social and economic data increased in importance, and included…

Personalization is crucial for achieving smart learning environments in different lifelong learning contexts. There is a need to shift from one-size-fits-all systems to personalized learning environments that give control to the learners. Recently, learning analytics (LA) is opening up new opportunities for promoting personalization by providing…

There is a need to improve the ways in which Qualitative Comparative Analysis (QCA) handles qualitative data. To this end, we propose to include ideas and routines from Grounded Theory (GT) in QCA. We will first argue that there is a natural fit between the two on the ontological level. On the methodological level, we will demonstrate in what ways…

Posing statistical questions is a fundamental and often overlooked component of statistical inquiry. In this paper, we provide an overview of shared understandings regarding what constitutes a good statistical question. We then describe three approaches--a checklist for improving statistical questions, a three-phase feedback activity, and a…

Basic knowledge of ideas of causal inference can help students to think beyond data, that is, to think more clearly about the data generating process. Especially for (maybe big) observational data, qualitative assumptions are important for the conclusions drawn and interpretation of the quantitative results. Concepts of causal inference can also…

Single-case experimental designs (SCEDs) have proven invaluable in research and practice because they are optimal for asking many experimental questions relevant to the analysis of behavior. The consecutive controlled case series (CCCS) is a type of study in which a SCED is employed in a series of consecutively encountered cases that undergo a…