Abstract
As we have seen, R has many features in common with Stata. Both share rich programming environments optimized for extensibility, functions open for you to see and modify, and flourishing ecosystems of extensions written by their devoted users.
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As we have seen, R has many features in common with Stata. Both share rich programming environments optimized for extensibility, functions open for you to see and modify, and flourishing ecosystems of extensions written by their devoted users.
R also has features that Stata lacks, such as a much wider selection of user-written functions, its rich collection of data structures, functions that optimize their output automatically for different data structures, and a flexibility that extends all the way to the core of the system. You can change anything about it you like.
R’s extreme flexibility may seem daunting to learn at first. However, its many thousands of add-on packages and its free price make it well worth the effort.
This book has covered how R compares to Stata and how you can do the very same things in each. However, what we have not covered literally fills many volumes. We hope this will start you on a long and successful journey with R.
We also hope to improve this book as time goes on, so if there are changes you would like to see in the next edition, please drop us a line at muenchen.bob@gmail.com or jhilbe@aol.com. Negative comments are often the most useful, so do not worry about being critical.
Have fun working with R!
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© 2010 Springer Science+Business Media, LLC
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Muenchen, R.A., Hilbe, J.M. (2010). Conclusion. In: R for Stata Users. Statistics and Computing. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-1318-0_18
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DOI: https://doi.org/10.1007/978-1-4419-1318-0_18
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-1317-3
Online ISBN: 978-1-4419-1318-0
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