R statistical software
- The R project for statistical computing is an incredible, free, open source software for statistical analysis and graphics.
- R is underpinned by a multitude of packages that facilitate basic and advanced data and biostatistical analysis, and (very impressive) graphics.
- R is syntax-based – therefore, coding is required to run data manipulations and analysis.
- Although coding may appear to be time consuming, written code can be saved and run over again, or adapted to different projects → this will likely save time in the long run.
- A user friendly wrapper for R is R Studio, which provides graphical user interface (GUI)-type functionality, although coding is still required.
- Key elements include the code editor, R console, workspace and history, and plots and files consoles
- The program is incredibly flexible, catering for a vast suite of data manipulation and analysis techniques, and has excellent static and dynamic graphics and data presentation tools (including apps).
- Probably the most comprehensive statistical analysis software
- R (the programming language) is developed for statistical analysis by practicing statisticians
- Excellent graphical capabilities
- Free and Open Source
- Connects with many software and formats (e.g. CSV files, Microsoft Excel, SPSS, SAS, MySQL, Oracle)
- Extensive library of packages
- Has a fairly steep learning curve to become familiar with programming language, although the language is intuitive and is of a similar level to other statistical program languages
- Documentation (for packages) can sometimes be difficult to follow
Rcommander is a free and very useful Graphical User Interface (GUI) wrapper for R that provides convenient point-and-click functionality for users to run statistical analyses. Based on the powerful R engine, Rcommander enables users a convenient way to select commonly-used R commands, including simple statistical methods and also more complex analyses, using a simple interface (highly similar to SPSS). More information on Rcommander can be obtained from https://www.rcommander.com/ and from the reference manual https://cran.r-project.org/web/packages/Rcmdr/Rcmdr.pdf.
- Data can be imported from a variety of file formats including Microsoft Excel
- A variety of common statistical methods can be selected and run from the pull-down tabs
Installation of Rcommander
As a GUI for R, Rcommander firstly requires the installation of R statistical software. Information about R and its installation can be found at the R homepage: http://www.r-project.org/. To download R, click on the CRAN (download) link and then click on an appropriate secure CRAN mirror URL from Australia (e.g. https://cran.csiro.au/). Download the version of R that suits your operating system. Note, you may have to log a job with the State Wide Service Desk instructing them to download R for you if you do not have administrative rights to download and/or install the software on your work computer.
Once you have downloaded and installed R, you can install Rcommander by simply typing the following command into the R-console:
install.packages(“Rcmdr”) and press the enter button to execute the command
Select a relevant CRAN mirror (Melbourne 1 typically works well) and click OK to install Rcommander.
Once installed, Rcommander can be loaded and run using the following command in the R-console: library(Rcmdr) (again, press the enter button to execute the command)
Zotero [zoh-TAIR-oh] is a free, easy-to-use tool to help you collect, organize, cite, and share your research sources (https://www.zotero.org)
- Zotero allows you to capture and save bibliographic information about items found on the web
- Zotero software works on PC, Mac and Linux systems
- Bibliographic items are easily added to Zotero by clicking on an icon which appears in the browser toolbar once the program is installed
- Multiple item formats can be added to Zotero including library catalogues or databases, journal articles, or generic webpages (e.g. news site)
- If it’s not possible to add an item from content, new items can be created and added manually in a variety of formats (e.g. book, book section, document, journal article).
- Bibliographies can be created from items saved in Zotero by simply selecting them, and clicking “Create Bibliography from Items…”. Bibliographies can be created according to a number of styles.
- In-text citations can also be created (perhaps the most common and useful way to manage references) via the installation of plug-in in word processing software (e.g. Microsoft Word).
Systematic review software
Rayyan, developed by the Qatar Computing Research Institute (Data Analytics), is a free web application designed to support researchers conducting systematic reviews. Rayyan provides a convenient web-based system to upload search results from a variety of databases (e.g. PubMed) for further screening and final selection of studies for inclusion in a systematic review.
Rayyan requires investigators to sign up for individual accounts before the application can be used. Information on signing up for and using Rayyan can be found at the Rayyan homepage: https://rayyan.qcri.org/. There is also a useful guide on how to use Rayyan for systematic reviews, including importing records, on the McGill University Library website at: http://libraryguides.mcgill.ca/rayyan/gettingstarted.