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Titlebook: R for Stata Users; Robert A. Muenchen,Joseph M. Hilbe Book 2010 Springer Science+Business Media, LLC 2010 STATISTICA.Stata.data acquisitio

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发表于 2025-3-21 17:45:42 | 显示全部楼层 |阅读模式
书目名称R for Stata Users
编辑Robert A. Muenchen,Joseph M. Hilbe
视频video
概述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 restr
丛书名称Statistics and Computing
图书封面Titlebook: R for Stata Users;  Robert A. Muenchen,Joseph M. Hilbe Book 2010 Springer Science+Business Media, LLC 2010 STATISTICA.Stata.data acquisitio
描述.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..
出版日期Book 2010
关键词STATISTICA; Stata; data acquisition; data analysis; statistics
版次1
doihttps://doi.org/10.1007/978-1-4419-1318-0
isbn_softcover978-1-4614-2596-0
isbn_ebook978-1-4419-1318-0Series ISSN 1431-8784 Series E-ISSN 2197-1706
issn_series 1431-8784
copyrightSpringer Science+Business Media, LLC 2010
The information of publication is updating

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Installing and Updating R,Stata and R are somewhat similar in that both are modular. Each comes with a single “binary” executable file and a large number of individual functions or commands. These are text files that users can modify in a text editor. Both applications come with their own built-in text editors, and both allow the use of outside text editors as well.
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Programming Language Basics,R is an object-oriented language. Everything that exists in it — variables, data sets, functions (commands) — are all objects.
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Data Acquisition,R can read or import data from a wide range of sources. It includes a data editor for manual input, and it can access files in text as well as Stata format. For other topics, such as reading importing data from relational databases, see the R Data Import/Export manual [39].
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Selecting Variables,In Stata, selecting variables for an analysis is simple, while selecting observations is often a bit more complicated. In R, these two processes can be almost identical. As a result, variable selection in R can at times be somewhat more complex. However, since you need to learn that complexity to select observations, it is not much added effort.
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Data Management,There is an old rule of thumb that says 80% of your data analysis time is spent transforming, reshaping, merging, and otherwise managing your data. Stata has a reputation of being more flexible than R for data management. However, as you will see in this chapter, R can do everything that Stata can do on these important tasks.
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Enhancing Your Output,As we have seen, R output is quite sparse and not nicely formatted for word processing. As in Stata, you can improve R’s output by adding value and variable labels. You can also format the output to make beautiful tables to use with word processors, web pages, and document preparation systems.
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