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At last! A comprehensive, applications-oriented mixed models guide for data analysis. Discover the latest capabilities available for a wide range of applications featuring the MIXED procedure in SAS/STAT software. This practical guide integrates the theory underlying the models, the specific forms of the models for various applications, and examples from many different fields of study using appropriate SAS code with interpretation of results. Specific models discussed include: simple random-effect only, simple mixed with a single fixed and random effect, split-plot, multilocation, repeated measures, analysis of covariance, random coefficients, and spatial correlation. With a background in two-way ANOVA and regression and basic knowledge of linear models and matrix algebra, you will benefit from the discussion of basic to advanced topics in this book. A working knowledge of experimental design is also helpful.

Biomathematics. Biometry. Biostatistics --- Programming --- Mathematical statistics --- Data processing. --- SAS (Computer file) --- SAS (Computer file). --- Méthode statistique --- Expérimentation --- experimentation --- Échantillonnage --- Sampling --- Data processing --- Statistical analysis system --- SAS system --- Statistical methods --- design --- experimentation. --- Mathematical statistics - Data processing. --- QA 76.755 - Computer Software. Handbook --- SAS

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This book explains the basics of S-PLUS in a clear style at a level suitable for people with little computing or statistical knowledge. Unlike the manuals, it is not comprehensive, but instead introduces the most important ideas of S-PLUS and R, its companion in implementing the S language. The authors take the reader on a journey into the world of interactive computing, data exploration, and statistical analysis. They explain how to approach data sets and teach the corresponding S-PLUS commands. A collection of exercises summarizes the main ideas of each chapter. The exercises are accompanied by solutions that are worked out in full detail, and the code is ready to use and to be modified. The volume is rounded off with practical hints on how efficient work can be performed in S-PLUS, for example by pointing out how to set up a good working environment and how to integrate S-PLUS with office products. The book is well suited for self-study and as a textbook. It serves as an introduction to S-PLUS as well as R. A separate chapter points out the major differences between R and S-PLUS. Over the last editions, the book has been updated to cover important changes like the inclusion of S Language Version 4, Trellis graphics, a graphical user interface, and many useful tips and tricks. The fourth edition is based on S-PLUS Version 7.0 for Windows and UNIX and has been updated and revised accordingly.

Mathematical statistics --- Data processing --- Programming --- -Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Statistical methods --- Statistics. --- Statistics and Computing/Statistics Programs. --- S-Plus. --- Data processing. --- Mathematical statistics. --- Statistics . --- Statistical analysis --- Statistical data --- Statistical science --- Mathematics --- Econometrics --- Mathematical statistics - Data processing

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S-PLUS is a powerful environment for the statistical and graphical analysis of data. It provides the tools to implement many statistical ideas which have been made possible by the widespread availability of workstations having good graphics and computational capabilities. This book is a guide to using S-PLUS to perform statistical analyses and provides both an introduction to the use of S-PLUS and a course in modern statistical methods. S-PLUS is available for both Windows and UNIX workstations, and both versions are covered in depth. The aim of the book is to show how to use S-PLUS as a powerful and graphical data analysis system. Readers are assumed to have a basic grounding in statistics, and so the book in intended for would-be users of S-PLUS and both students and researchers using statistics. Throughout, the emphasis is on presenting practical problems and full analyses of real data sets. Many of the methods discussed are state-of-the-art approaches to topics such as linear, nonlinear, and smooth regression models, tree-based methods, multivariate analysis and pattern recognition, survival analysis, time series and spatial statistics. Throughout, modern techniques such as robust methods, non-parametric smoothing, and bootstrapping are used where appropriate. This third edition is intended for users of S-PLUS 4.5, 5.0, 2000 or later, although S-PLUS 3.3/4 are also considered. The major change from the second edition is coverage of the current versions of S-PLUS. The material has been extensively rewritten using new examples and the latest computationally intensive methods. The companion volume on S Programming will provide an in-depth guide for those writing software in the S language. The authors have written several software libraries that enhance S-PLUS; these and all the datasets used are available on the Internet in versions for Windows and UNIX. There are extensive on-line complements covering advanced material, user-contributed extensions, further

Statistics --- Mathematical statistics --- Statistique --- Statistique mathématique --- Data processing --- Informatique --- S (Computer system) --- -Mathematical statistics --- -57.087.1 --- 519.6 --- -005.369 --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Probabilities --- Sampling (Statistics) --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Econometrics --- Biometry. Statistical study and treatment of biological data --- Computational mathematics. Numerical analysis. Computer programming --- Statistics as Topic. --- Mathematical Statistics --- Physical Sciences & Mathematics --- Data processing. --- S (Computer system). --- 519.6 Computational mathematics. Numerical analysis. Computer programming --- 57.087.1 Biometry. Statistical study and treatment of biological data --- Statistique mathématique --- 005.369 --- 57.087.1 --- Programming --- Statistics - Data processing --- Mathematical statistics - Data processing --- Acqui 2006 --- Statistique mathematique --- Methodes numeriques --- Programmes informatiques