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…

The field of qualitative comparative analysis (QCA) is witnessing a heated debate on which one of the QCA's main solution types should be at the center of substantive interpretation. This article argues that the different QCA solutions have complementary strengths. Therefore, researchers should interpret the three solution types in an integrated…

In order to better grasp the needs of library users and provide them with more accurate knowledge services, combining the characteristics of university libraries, this article applies library small data to personalized recommendation and proposes a small data fusion algorithm model for library personalized recommendation. This model combines the…

In the context of higher education's growing significance and the persistence of inequalities in it, the article aims to further develop the understanding of higher education as a public good and to explore its association with social cohesion in a European comparative perspective. It shifts the focus from the content of higher education as a…

As data are 'numbers with context' (Cobb & Moore, 1997), contextual knowledge plays a prominent role in dealing with statistics. While insights about a specific context can further the depth of interpreting and evaluating outcomes of data analysis, research shows how it can also hinder relying on data especially if results differ from…

In the current study, we compare propensity score (PS) matching methods for data with a cross-classified structure, where each individual is clustered within more than one group, but the groups are not hierarchically organized. Through a Monte Carlo simulation study, we compared sequential cluster matching (SCM), preferential within cluster…

The synthetic control method (SCM) is a popular approach for estimating the impact of a treatment on a single unit with panel data. Two challenges arise with higher frequency data (e.g., monthly versus yearly): (1) achieving excellent pre-treatment fit is typically more challenging; and (2) overfitting to noise is more likely. Aggregating data…

Meta-analysts often encounter missing covariate values when estimating meta-regression models. In practice, ad hoc approaches involving data deletion have been widely used. The current study investigates the performance of different methods for handling missing covariates in meta-regression, including complete-case analysis (CCA), shifting-case…

We examine four important considerations in the development of covariate adjustment methodologies for indirect treatment comparisons. First, we consider potential advantages of weighting versus outcome modeling, placing focus on bias-robustness. Second, we outline why model-based extrapolation may be required and useful, in the specific context of…

Schools are frequently seen as the hubs of the community, providing resources and a gathering place for members of the community. The process of surveying the community in order to identify unique needs within the community, and then intentionally forging partnerships capable of ameliorating the specific needs, are strategies used by community…

To develop competency in science practices, such as data analysis and interpretation, chemistry learners must develop an understanding of what makes an analysis and interpretation "good" (i.e., the criteria for success). One way that individuals extract the criteria for success in a novel situation is through making social comparisons,…

Mixed-mode surveys are popular as they can save costs and maintain (or improve) response rates relative to single-mode surveys. Nevertheless, it is not yet clear how design decisions like survey mode or questionnaire length impact measurement quality. In this study, we compare measurement quality in an experiment of three distinct survey designs…

A commonly used metric for measuring college costs, drawn from data in the Integrated Postsecondary Education Data System (IPEDS), is expenditure per full-time equivalent (FTE) student. This article discusses an error in this per FTE calculation when using IPEDS data, especially with regard to community colleges. The problem is that expenditures…

Systematic reviews are vital for guiding practice, research and policy, although they are often slow and labour-intensive. Large language models (LLMs) could speed up and automate systematic reviews, but their performance in such tasks has yet to be comprehensively evaluated against humans, and no study has tested Generative Pre-Trained…

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…