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Siena in R: RSiena

RSiena can be installed in the usual way from CRAN, but the most recent version of RSiena can be downloaded from GitHub. It is expected that at some moment multiSiena will be integrated into RSiena.

For downloading RSiena and multiSiena, see the Siena downloads page. For differences between the CRAN and GitHub versions of RSiena, see the Siena news page. Note that the GitHub version is updated more frequently than the CRAN version, as explained there.

For requests of new effects or other new features, bug reports, etc. please open an issue at github.

The original development of RSiena, building on the earlier Siena (stand-alone and part of the Stocnet suite) was part of the project Adolescent Peer Social Network Dynamics and Problem Behavior, funded by NIH (Grant Number 1R01HD052887-01A2), Principal Investigator John M. Light (Oregon Research Institute). RSiena was originally programmed by Ruth Ripley and Krists Boitmanis, in collaboration with Tom Snijders. Several others have been contributing since then: Josh Lospinoso, Charlotte Greenan, Christian Steglich, Johan Koskinen, Felix Schönenberger, Mark Ortmann, Natalie Indlekofer, and Nynke Niezink. The maintainer is Tom Snijders. We are continuing with the extension of the package. The fact that R is open source implies that the source is available (most easily from GitHub, see below) and the project is open to contributions by other researchers who know how to program in R and/or C/C++.
RSiena replaces the older Windows-based SIENA version 3, which still is available from the downloads page, but no longer maintained.

RSiena can be operated in several ways. The best (most complete) functionality is obtained by executing RSiena entirely within R, using the R functions supplied by this package.
An alternative option is to access RSiena from visone; a short guide is available at the visone website.

The installation and operation of RSiena are explained in the users' manual. It includes information on how to install RSiena, and help on getting started with operating RSiena in R. In addition, it gives extensive descriptions of the methods available in RSiena. This complements the help pages of the functions that can be consulted within R.

Example scripts are at the RSiena scripts page, and a lot of introductory and advanced material about the methodology is at the literature page. There is news, with information about bugs if any important errors are currently known, at the news page.

RSiena and its manual are being updated rather frequently at GitHub.

Downloads / links

• For downloading RSiena and multiSiena, go to the Siena downloads page.
• You can download the current RSiena users' manual.
• Some websites and resources that can be very helpful for the beginning R user:
  1. Jochem Tolsma and Bas Hofstra, Introduction to R for SNA, Appendix A of Social Network Analysis for Social Scientists ("SNASS").
  2. Self-Learning Resources for R from Princeton.
  3. General information about R from UCLA.
  4. Impatient R, previously Some Hints for the R Beginner, by Patrick Burns with the memorable quote
     "I asked R users what their biggest stumbling blocks were in learning R. A common answer that I was quite surprised by was that the biggest stumbling block was thinking that R was hard".
  5. Introduction to Data Exploration and Analysis with R by Michael Mahoney.
     This book is designed as a crash course in coding with R and data analysis, built for people trying to teach themselves.
  6. icebreakeR by Andrew Robinson.
  7. Quick R website (intended especially for experienced users of other statistical software).
  8. R-bloggers tutorials for learning R by Tal Galili.
  9. The official R intro (always for the current version of R).

• Further general help on R:
  • Course on R and R programming by Ruth Ripley.
  • The "Documentation" links on http://cran.r-project.org
  • R reference card.
  • RStudio, an integrated development environment (IDE) for R, available for all major platforms (like g Windows, Mac OS X, and Linux). This is an alternative to the R gui available for Windows.
  • Another alternative, or rather a convenient complement, is NpptoR, which easily passes on code from the Notepad++ editor (which has nice syntax highlighting) to R.
  • An introductory R script for starting with R, using IMF data collected by David de Jong.
  • An introductory R script to learn R for Social Networks applications, using the Lazega lawyers data , which can also be directly downloaded from this directory with data files.
  • Introduction to Social Network Analysis in R by Michal Bojanowski (ICM, University of Warsaw).
  • R-bloggers, a central hub of content collected from bloggers who write about R (in English).

• The RSiena information at CRAN (the Comprehensive R Archive Network).
  

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