Linear Mixed-Effects Models Using R

This textbook for students in the health and social sciences covers the basics of linear model methods with a minimum of mathematics, assuming only a pre-calculus background. Numerous examples drawn from the news and current events with an emphasis on health issues, illustrate the concepts in an immediately accessible way. Methods covered include linear regression models, Poisson regression, logistic regression, proportional hazards regression, survival analysis, and nonparametric regression. The author emphasizes interpretation of computer output in terms of the motivating example. All of the R code is provided and carefully explained, allowing readers to quickly apply the methods to their own data. Plenty of exercises help students think about the issues involved in the analysis and its interpretation. Code and datasets are available for download from the book's website at www.cambridge.org/zelterman

Gain hands-on experience creating, manipulating, and optimizing motion graphics for film, video, the web, and mobile devices. Learn how to animate text and images, customize a wide range of effects, track and sync content, rotoscope, manipulate timing, correct color, and remove unwanted objects. Customize cameras and lighting to create compelling 3D content. Design Motion Graphics templates for editing in Adobe Premiere Pro. Deform and animate objects and video using robust Puppet tools. The fastest, easiest, most comprehensive way to learn Adobe After Effects Classroom in a Book(R), the best-selling series of hands-on software training workbooks, offers what no other book or training program does--an official training series from Adobe, developed with the support of Adobe product experts. Adobe After Effects Classroom in a Book contains 15 lessons that cover the basics and beyond, providing countless tips and techniques to help you become more productive with the program. You can foll

Chunyan Li is a course instructor with many years of experience in teaching about time series analysis. His book is essential for students and researchers in oceanography and other subjects in the Earth sciences, looking for a complete coverage of the theory and practice of time series data analysis using MATLAB. This textbook covers the topic's core theory in depth, and provides numerous instructional examples, many drawn directly from the author's own teaching experience, using data files, examples, and exercises. The book explores many concepts, including time; distance on Earth; wind, current, and wave data formats; finding a subset of ship-based data along planned or random transects; error propagation; Taylor series expansion for error estimates; the least squares method; base functions and linear independence of base functions; tidal harmonic analysis; Fourier series and the generalized Fourier transform; filtering techniques: sampling theorems: finite sampling effects; wavelet