Understanding differential item functioning (DIF) is critical for ensuring fairness in assessments across diverse groups. A recent study by Li et al. introduces a method to enhance the interpretability of DIF items by incorporating response process data. This approach aims to improve equity in measurement by examining how participants engage …
Sørensen, Fjell, and Walhovd’s 2023 research introduces Generalized Additive Latent and Mixed Models (GALAMMs), a methodological advancement designed for analyzing complex clustered data. This approach holds particular relevance for cognitive neuroscience, offering robust tools for examining how cognitive and neural traits develop over time. Background Traditional models used in cognitive …
Leifeng Xiao and Kit-Tai Hau’s article, “Performance of Coefficient Alpha and Its Alternatives: Effects of Different Types of Non-Normality,” examines how coefficient alpha and other reliability indices perform under varying conditions of non-normality. The study offers critical insights into how these measures behave across different data structures, providing useful recommendations …
The study by Xiao and Bulut (2020) evaluates how different methods for handling missing data perform when estimating ability parameters from sparse datasets. Using two Monte Carlo simulations, the research highlights the strengths and limitations of four approaches, providing valuable insights for researchers and practitioners in educational and psychological measurement. …
