Validity, Reliability, and Significance

Discover the essential insights in Validity, Reliability, and Significance by Stefan Riezler, published by Springer International Publishing AG in 2024. This second edition spans 168 pages and delves into model-based empirical methods, emphasizing the importance of data annotations and model predictions as training data for interpretable probabilistic models. Riezler expertly navigates the well-established families of generalized additive models (GAMs) and linear mixed effects models (LMEMs), making this book a crucial resource for researchers and practitioners alike. Enhance your understanding of statistical modeling with this comprehensive guide that combines theoretical foundations with practical applications. Perfect for anyone looking to deepen their knowledge in the field, this hardback edition is a valuable addition to your professional library.