This book provides an integrated introduction to multivariate multiple regression analysis (MMR) and multivariate analysis of variance (MANOVA). Beginning with an overview of the univariate general linear model, this volume defines the key steps in analyzing linear model data and introduces multivariate linear model analysis as a generalization of the univariate model. Richard F. Haase focuses on multivariate measures of association for four common multivariate test statistics, presents a flexible method for testing hypotheses on models, and emphasizes the multivariate procedures attributable to Wilks, Pillai, Hotelling, and Roy. The volume concludes with a discussion of canonical correlation analysis that is shown to subsume all the multivariate procedures discussed in previous chapters. The analyses are illustrated throughout the text with three running examples drawing from several disciples, including personnel psychology, anthropology, environmental epidemiology, and neuropsychology.
An Introduction to Basic and Advanced Multilevel Modeling
The classic text in multilevel analysis, dealing with everything you need to know, has been hugely revised and added to and is supported by all the software. A must-have for modellers.
How do you present or organize your statistical or numerical data so that it is accessible and meaningful for your readers or audience? Graphing Statistics & Data introduces the technique and art of producing good charts. Carefully written with many examples and illustrations, the book begins with an introduction to the building blocks of ......
The focus in this Second Edition is on logistic regression models for individual level (but aggregate or grouped) data. Multiple cases for each possible combination of values of the predictors are considered in detail and examples using SAS and SPSS are included. New to this edition: * more detailed consideration of grouped as opposed to casewise ......
This is the ideal textbook for any course in statistical methods across the health and social sciences and a perfect starter book for students, researchers and professionals alike.
Designed to engage students and lower their "fear factor", Integrative Statistics for the Social and Behavioral Sciences is a concise, user-friendly text that prepares students to use statistics in the real world. Providing depth and breadth of statistical tests, the text focuses on choosing the appropriate statistical analysis, and shows how to interpret the output and present the results.
`If you encounter a research student for whom the very word LISREL induces feelings of fear, quietly recommend that they read this book. They will thank you for it. With increasingly user-friendly versions of LISREL being released and guide books such as this published, LISREL really should be accessible to all' - European Journal of Marketing ......
This practical guide teaches nonstatisticians how to analyze and interpret loglinear models using the multigraph The Association Graph and the Multigraph for Loglinear Models will help students, particularly those studying the analysis of categorical data, to develop the ability to evaluate and unravel even the most complex loglinear models without heavy calculations or statistical software. This supplemental text reviews loglinear models, explains the association graph, and introduces the multigraph to students who may have little prior experience of graphical techniques, but have some familiarity with categorical variable modeling. The author presents logical step-by-step techniques from the point of view of the practitioner, focusing on how the technique is applied to contingency table data and how the results are interpreted.
