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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 new edition to the classic book by ggplot2 creator Hadley Wickham highlights compatibility with knitr and RStudio. ggplot2 is a data visualization package for R that helps users create data graphics, including those that are multi-layered, with ease. With ggplot2, it's easy to : (-) produce handsome, publication-quality plots with automatic legends created from the plot specification ; (-) superimpose multiple layers (points, lines, maps, tiles, box plots) from different data sources with automatically adjusted common scales ; (-) add customizable smoothers that use powerful modeling capabilities of R, such as loess, linear models, generalized additive models, and robust regression ; (-) save any ggplot2 plot (or part thereof) for later modification or reuse ; (-) create custom themes that capture in-house or journal style requirements and that can easily be applied to multiple plots ; (-) approach a graph from a visual perspective, thinking about how each component of the data is represented on the final plot. This book will be useful to everyone who has struggled with displaying data in an informative and attractive way. Some basic knowledge of R is necessary (e.g., importing data into R). ggplot2 is a mini-language specifically tailored for producing graphics, and you'll learn everything you need in the book. After reading this book you'll be able to produce graphics customized precisely for your problems, and you'll find it easy to get graphics out of your head and on to the screen or page.

Graphic methods. --- R (Computer program language) --- GNU-S (Computer program language) --- Domain-specific programming languages --- Graphics --- Graphs --- Geometrical drawing --- Least squares --- Mathematics --- Mechanical drawing --- Data Interpretation, Statistical --- Systems Analysis --- Software --- Computer Imaging, Graphics & Vision --- QA 76.755 - Computer Software. Handbook --- Graphic methods --- Statistics --- Computer graphics --- Visualization --- Mathematical statistics --- Statistiques. --- Statistique mathématique. --- Infographie --- Data visualisation. --- Logiciels. --- Statistiques --- Statistique mathématique.