Stata is the most flexible and extensible data analysis package available from a commercial vendor. R is a similarly flexible free and open source package for data analysis, with over 3,000 add-on packages available. This book shows you how to extend the power of Stata through the use of R. It introduces R using Stata terminology with which you are already familiar. It steps through more than 30 programs written in both languages, comparing and contrasting the two packages' different approaches. When finished, you will be able to use R in conjunction with Stata, or separately, to import data, manage and transform it, create publication quality graphics, and perform basic statistical analyses.

A glossary defines over 50 R terms using Stata jargon and again using more formal R terminology. The table of contents and index allow you to find equivalent R functions by looking up Stata commands and vice versa. The example programs and practice datasets for both R and Stata are available for download.

Read data from various types of text files and Stata data sets Manage your data through transformations, recodes, and combining data sets from both the add-cases and add-variables approaches and restructuring data from wide to long formats and vice versa Create publication quality graphs Perform the basic types of analyses to measure strength of association and group differences and be able to know where to turn to cover much more complex methods Includes supplementary material: sn.pub/extras

Autorentext
Joseph M. Hilbe, is Chair of both the International Astrostatistics Network, and ISI astrostatistics committee. ISI is the International Statistical Institute, the world association of statisticians. Prof. Hilbe is also editor-in-chief of the Springer Series in Astrostatistics and chaired the World Statistics Congress invited and special topics sessions from which eight of the book's monographs originated. An elected Fellow of the American Statistical Association and Elected Member of the ISI, Professor Hilbe is author of several leading texts in statistical modeling.

Inhalt
Installing and Updating R.- Running R.- Help and Documentation.- Programming Language Basics.- Data Acquisition.- Selecting Variables.- Selecting Observations.- Selecting Variables and Observations.- Data Management.- Enhancing Your Output.- Generating Data.- Managing Your Files and Workspace.- Graphics Overview.- Traditional Graphics.- Graphics with ggplot2.- Statistics.- Conclusion.