Using R for Data Management, Statistical Analysis, and Graphics
Crc Press Inc (Verlag)
978-1-4398-2755-0 (ISBN)
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Quick and Easy Access to Key Elements of Documentation
Includes worked examples across a wide variety of applications, tasks, and graphics
Using R for Data Management, Statistical Analysis, and Graphics presents an easy way to learn how to perform an analytical task in R, without having to navigate through the extensive, idiosyncratic, and sometimes unwieldy software documentation and vast number of add-on packages. Organized by short, clear descriptive entries, the book covers many common tasks, such as data management, descriptive summaries, inferential procedures, regression analysis, multivariate methods, and the creation of graphics.
Through the extensive indexing, cross-referencing, and worked examples in this text, users can directly find and implement the material they need. The text includes convenient indices organized by topic and R syntax. Demonstrating the R code in action and facilitating exploration, the authors present example analyses that employ a single data set from the HELP study. They also provide several case studies of more complex applications. Data sets and code are available for download on the book’s website.
Helping to improve your analytical skills, this book lucidly summarizes the aspects of R most often used by statistical analysts. New users of R will find the simple approach easy to understand while more sophisticated users will appreciate the invaluable source of task-oriented information.
Nicholas J. Horton is an associate professor in the Department of Mathematics and Statistics at Smith College in Northampton, Massachusetts. His research interests include longitudinal regression models and missing data methods, with applications in psychiatric epidemiology and substance abuse research. Ken Kleinman is an associate professor in the Department of Population Medicine at Harvard Medical School in Boston, Massachusetts. His research deals with clustered data analysis, surveillance, and epidemiological applications in projects ranging from vaccine and bioterrorism surveillance to observational epidemiology to individual-, practice-, and community-randomized interventions.
Introduction to R
Installation
Running R and sample session
Using the R Commander graphical interface
Learning R and getting help
Fundamental structures: Objects, classes, and related concepts
Built-in and user-defined functions
Add-ons: Libraries and packages
Support and bugs
Data Management
Input
Output
Structure and meta-data
Derived variables and data manipulation
Merging, combining, and subsetting datasets
Date and time variables
Interactions with the operating system
Mathematical functions
Matrix operations
Probability distributions and random number generation
Control flow, programming, and data generation
Further resources
HELP examples
Common Statistical Procedures
Summary statistics
Contingency tables
Bivariate statistics
Two sample tests for continuous variables
Further resources
HELP examples
Linear Regression and ANOVA
Model fitting
Model comparison and selection
Tests, contrasts, and linear functions of parameters
Model diagnostics
Model parameters and results
Further resources
HELP examples
Regression Generalizations and Multivariate Statistics
Generalized linear models
Models for correlated data
Survival analysis
Further generalizations to regression models
Multivariate statistics and discriminant procedures
Further resources
HELP examples
Graphics
A compendium of useful plots
Adding elements
Options and parameters
Saving graphs
Further resources
HELP examples
Advanced Applications
Power and sample size calculations
Simulations and data generation
Data management and related tasks
Read geocoded data and draw maps
Data scraping and visualization
Account for missing data using multiple imputation
Propensity score modeling
Empirical problem solving
Further resources
Appendix: The HELP Study Dataset
Subject Index
R Index
| Erscheint lt. Verlag | 2.8.2010 |
|---|---|
| Zusatzinfo | 8 Tables, black and white; 35 Illustrations, black and white |
| Verlagsort | Bosa Roca |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Gewicht | 431 g |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Computerprogramme / Computeralgebra |
| Naturwissenschaften ► Biologie | |
| ISBN-10 | 1-4398-2755-9 / 1439827559 |
| ISBN-13 | 978-1-4398-2755-0 / 9781439827550 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
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