This book guides readers through conventional statistical concepts and how tot interpret them in GLM terms, treating the main single- and multi-factor designs as they relate to ANOVA and ANCOVA.
This textbook describes both the conventional and less common uses of linear regression in the practical context of today's mathematical and scientific research. It blends both theory and application to equip the reader with an understanding of the basic principles necessary to …
Updated and expanded edition of a text for graduate and advanced undergraduate students of applied statistics. Differs most conspicuously from the 1983 edition in that exercises can now be found at the end of each of the fifteen chapters.
Updated and expanded edition of a text for graduate and advanced undergraduate students of applied statistics. Differs most conspicuously from the 1983 edition in that exercises can now be found at the end of each of the fifteen chapters.
Regression is the branch of Statistics in which a dependent variable of interest is modelled as a linear combination of one or more predictor variables, together with a random error. The subject is inherently two- or higher- dimensional, thus an understanding of Statistics in on…
This book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models, and it presents an up-to-date account of theory and methods in analysis of these models as well as their applications in various fields. The book offers a systema…
"This book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models, and it presents an up-to-date account of theory and methods in analysis of these models as well as their applications in various fields. The book offers a system…