This book provides an overview of the theory and application of linear and nonlinear mixed-effects models in the analysis of grouped data, such as longitudinal data, repeated measures, and multilevel data. Over 170 figures are included in the book.

Based on the authors Robert Johnson and Douglas Bate's thirty-two years of experience consulting to major organizations, The Power of Strategy Innovation contains tools and tricks to help companies excel in dynamic markets and provide groundbreaking products and services. You'll learn how to apply innovative thinking to your company's business model to bridge the gap between strategy and product development; how to remain flexible, future-oriented, and responsive to market changes and your clients' changing needs; and how to create a perpetual flow of viable new business opportunities. The authors refer to this as "innovation" rather than "strategic planning," but the truth is somewhere in-between: through a proven five-phase discovery process --for staging, aligning, exploring, creating, and mapping--strategic innovation will become a company-wide competency. The book's latest edition, updated in 2013, includes a new preface and epilogue describing the emergence of enterprise innovation and its impact on both companies' day-to-day planning and focuses on the future. Informative interviews with corporate leaders dispersed throughout the book provide further insight into different industries and the ways they have committed to taking a more innovative approach. To that end, through these shared methodologies, The Power of Strategy Innovation will forever transform the way you do business--and help you rise to become a leader in your industry.

An overview of the theory and application of linear and nonlinear mixed-effects models in the analysis of grouped data, such as longitudinal data, repeated measures, and multilevel data. The authors present a unified model-building strategy for both models and apply this to the analysis of over 20 real datasets from a wide variety of areas, including pharmacokinetics, agriculture, and manufacturing. Much emphasis is placed on the use of graphical displays at the various phases of the model-building process, starting with exploratory plots of the data and concluding with diagnostic plots to assess the adequacy of a fitted model. The NLME library for analyzing mixed-effects models in S and S-PLUS, developed by the authors, provides the underlying software for implementing the methods presented. This balanced mix of real data examples, modeling software, and theory makes the book a useful reference for practitioners who use, or intend to use, mixed-effects models in their data analyses. It can also be used as a text for a one-semester graduate-level applied course.