R for Stata Users

  • Robert A. Muenchen
  • Joseph M. Hilbe

Part of the Statistics and Computing book series (SCO)

Table of contents

  1. Front Matter
    Pages i-xxiv
  2. Robert A. Muenchen, Joseph M. Hilbe
    Pages 1-7
  3. Robert A. Muenchen, Joseph M. Hilbe
    Pages 9-18
  4. Robert A. Muenchen, Joseph M. Hilbe
    Pages 19-35
  5. Robert A. Muenchen, Joseph M. Hilbe
    Pages 37-44
  6. Robert A. Muenchen, Joseph M. Hilbe
    Pages 45-90
  7. Robert A. Muenchen, Joseph M. Hilbe
    Pages 91-117
  8. Robert A. Muenchen, Joseph M. Hilbe
    Pages 119-138
  9. Robert A. Muenchen, Joseph M. Hilbe
    Pages 139-156
  10. Robert A. Muenchen, Joseph M. Hilbe
    Pages 157-166
  11. Robert A. Muenchen, Joseph M. Hilbe
    Pages 167-251
  12. Robert A. Muenchen, Joseph M. Hilbe
    Pages 253-276
  13. Robert A. Muenchen, Joseph M. Hilbe
    Pages 277-290
  14. Robert A. Muenchen, Joseph M. Hilbe
    Pages 291-310
  15. Robert A. Muenchen, Joseph M. Hilbe
    Pages 311-318
  16. Robert A. Muenchen, Joseph M. Hilbe
    Pages 319-384
  17. Robert A. Muenchen, Joseph M. Hilbe
    Pages 385-452
  18. Robert A. Muenchen, Joseph M. Hilbe
    Pages 453-496
  19. Robert A. Muenchen, Joseph M. Hilbe
    Pages 497-497
  20. Back Matter
    Pages 499-529

About this book

Introduction

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.

Robert A. Muenchen is the author of the book, R for SAS and SPSS Users, and is a consulting statistician with 29 years of experience. He has served on the advisory boards of SAS Institute, SPSS Inc., and the Statistical Graphics Corporation. He currently manages Research Computing Support at The University of Tennessee.

Joseph M. Hilbe is Solar System Ambassador with NASA/Jet Propulsion Laboratory, California Institute of Technology, an adjunct professor of statistics at Arizona State, and emeritus professor at the University of Hawaii. He is a Fellow of the American Statistical Association and elected member of the International Statistical Institute. Hilbe was the first editor of the Stata Technical Bulletin, (later named the Stata Journal) and is author of a number of textbooks, including Logistic Regression Models and Negative Binomial Regression.

Keywords

STATISTICA Stata data acquisition data analysis statistics

Authors and affiliations

  • Robert A. Muenchen
    • 1
  • Joseph M. Hilbe
    • 2
  1. 1.Office of Information Technology Statistical Consulting Center, Stokeley Management CenterUniversity of TennesseeKnoxvilleUSA
  2. 2.FlorenceUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4419-1318-0
  • Copyright Information Springer Science+Business Media, LLC 2010
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-1-4419-1317-3
  • Online ISBN 978-1-4419-1318-0
  • Series Print ISSN 1431-8784
  • Series Online ISSN 2197-1706
  • About this book