This two-volume work provides a comprehensive overview of ANOVA models with random effects, essential for various fields such as agriculture, biology, and engineering. It covers point and interval estimation, and hypothesis testing, accessible to readers with basic statistical knowledge, making it suitable for students and researchers alike.
This two-volume work on ANOVA models with random effects is essential for experimental design across various fields. Volume I focuses on balanced data, covering estimation methods and hypothesis tests, while Volume II addresses unbalanced data. It's suitable for graduate students and practitioners with a basic math background.
Volume I: Balanced Data Theory, Methods, Applications and Data Analysis
Focusing on ANOVA models with random effects, this volume provides an in-depth exploration of point estimation, interval estimation, and hypothesis testing for linear models. It specifically addresses balanced data scenarios, offering comprehensive methodologies and techniques applicable across various fields like biology and engineering. The work is structured into two volumes, with the second volume dedicated to unbalanced data models, ensuring a thorough understanding of both orthogonal and non-orthogonal approaches in experimental design.