Data Analysis Using SAS Review

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(More customer reviews)This book is a very well-written and well-organized introduction to SAS. Each chapter includes many examples, which are clearly explained. Rather than simply explaining how to write the code, the author guides the reader through interpreting the results. If you have no experience using SAS, this is a great resource, though more intermediate users may wish to look elsewhere for a more advanced book. For me, the most helpful chapter has been 'When Do You Stop Worrying and Start Loving Regression?', which guides you through writing the initial code (including variations for different types of models) as well as interpreting and testing the results. Highly recommended!

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Data Analysis Using SASoffers a comprehensive core text focused on key concepts and techniques in quantitative data analysis using the most current SAS commands and programming language. The coverage of the text is more evenly balanced among statistical analysis, SAS programming, and data/file management than any available text on the market.It provides students with a hands-on, exercise-heavy method for learning basic to intermediate SAS commands while understanding how to apply statistics and reasoning to real-world problems. Designed to be used in order of teaching preference by instructor, the book is comprised of two primary sections: the first half of the text instructs students in techniques for data and file managements such as concatenating and merging files, conditional or repetitive processing of variables, and observations. The second half of the text goes into great depth on the most common statistical techniques and concepts - descriptive statistics, correlation, analysis of variance, and regression - used to analyze data in the social, behavioral, and health sciences using SAS commands. A student studyat www.sagepub.com/pengstudycomes replete with a multitude of computer programs, their output, specific details on how to check assumptions, as well as all data sets used in the book. Data Analysis Using SAS is a complete resource for Data Analysis I and II, Statistics I and II, Quantitative Reasoning, and SAS Programming courses across the social and behavioral sciences and health - especially those that carry a lab component.

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Visualizing Categorical Data Review

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(More customer reviews)This is the best book I've read about methods to visualize categorical data.

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This book offers many new and more easily accessible graphical methods for representing categorical data using SAS software. Graphical methods for quantitative data are well developed and widely used. However, until now with this comprehensive treatment, few graphical methods existed for categorical data. In this innovative book, Friendly presents many aspects of the relationships among variables, the adequacy of a fitted model, and possibly unusual features of the data that can best be seen and appreciated in an informative graphical display. Filled with programs and data sets, this book focuses on the use, understanding, and interpretation of results. Where necessary, the statistical theory with a well-written explanation is also provided. Readers will also appreciate the implementation of these methods in the general macros and programs that are described in the book.

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Step-By-Step Basic Statistics Using SAS: Exercises Review

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(More customer reviews)I have been a SAS programmer for almost 10 years now, mostly doing data cleaning, linking, and simple descriptive statistics for reports. I have recently been given work requiring more complex statistical analysis such as significance testing and logistic regression. I found this book to be a perfect guide for my situation. I have approached learning Stats for SAS via SUGI papers and other web resources which are typically geared towards professional statisticians. It was daunting to say the least. For myself, an experienced programmer needing to get my knowledge of statistics up to par, this book is invaluable. If you have never used SAS before and don't know the basics, try a different starting point like "The Little SAS Book: A Primer."

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With Step-by-Step Basic Statistics Using SAS: Exercises, you apply what you learned in the companion text, Step-by-Step Basic Statistics Using SAS: Student Guide. Using the instruction provided, you soon will be creating data sets and performing statistical analyses to investigate specific research questions. The exercise data is inspired by studies in the social and behavioral sciences, so your analyses and findings mirror real research. Each chapter presents two opportunities to explore the results of the analyses and to practice writing summary reports. For the first exercise, a complete solution is provided, including the SAS program, output, and analysis report, as well as tables and figures. For the second exercise, you supply the solution.

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Applied Longitudinal Data Analysis for Epidemiology: A Practical Guide Review

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(More customer reviews)This book is really useful and handy. It is very well written and easy to read. As the name stated, it provides very practical guides for those who don't have strong background in Statistics but are dealing with longitudinal data. It is written in an example guided format. The outputs from the analysis and guidelines on how to interpret them step by step are included. There is no heavy Statistical notation and you don't need to translate Statistics into English. At the end of the book, there are chapters of how to handle missing data and softwares used in longitudinal data analysis. This book is probably too boring if you are a hardcore Statistician.

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The most important techniques available for longitudinal data analysis are discussed in this book. The discussion includes simple techniques such as the paired t-test and summary statistics, but also more sophisticated techniques such as generalized estimating equations and random coefficient analysis. A distinction is made between longitudinal analysis with continuous, dichotomous, and categorical outcome variables. This practical guide is especially suitable for non-statisticians and all those undertaking medical research or epidemiological studies.

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