Current Version: 0.8x (Mac, Windows, or Linux)
Listing updated: 4/2018; program updated 4/2018
Cryptographically signed by Apple
Jamovi: A free, open source package, built on top of an R foundation (Thanks, Dr. Kim-Oliver Tietze). Don’t let that put you off: unlike most interfaces for R, Jamovi uses a simple spreadsheet interface with full graphics. You can edit via spreadsheet; and your data, analyses, and options are saved in a single file, so others can reproduce your work. A large number of analyses are easy to find, or you can use R syntax.
Jamovi is in some ways a continuation of JASP. From their web site:
Originally we worked together as (lead) developers and designers of the JASP project, a project that focuses on making Bayesian statistics more accessible. However we found that our goals and ambitions consistently went beyond the scope of JASP, and decided the best way to move forward was to found a new project...
The general look and feel is attractive (see above), with menus that will be familiar to any SPSS users — and with many options. Unlike SPSS, when you add an option, it doesn’t rerun everything and create a huge amount of new output; for example, in the illustration above, we clicked on the “Adjusted R2” option and it was immediately added to the existing screen. That’s a major improvement. If you have long variable labels in imported files (or long variable names in any file), some correlations may not show on the screen.
Data can be imported in numerous ways, including formatted SPSS files and, according to the programmers, SAS and Stata files. (In my brief experimentation, I found that the system would sometimes not open SPSS files, but quitting and restarting resolved the problem.) Variable labels are imported as the variable name; value labels are not imported at all (presumably because they’re not supported as such, and would make some analyses difficult or impossible).
Installation of the software is by “drag-copy” — drag it out of the download image and into the desired folder. The interface is exactly the same, regardless of platform — Windows, Mac, Linux. Speed was quite satisfactory using our survey file.
A “syntax mode” (enable it by clicking on the three dots at the right-side of the blue stripe, then clicking on the appropriate checkbox) shows the generated R syntax for each menu command, helping you to learn R syntax or make scripts to reproduce the same actions over and over. The three-dots-on-the-stripe isn’t particularly intuitive for changing settings, compared with, say, an options menu.
Copying and pasting output is cleverly done, — more cleverly done than in the last version of SPSS I used. Right-click on a section of output, and if you paste it into Word, it will be perfectly formatted, as a table; paste into BBEdit, and it will be plain-text, formatted with spaces. Plots can also be copied and pasted, but seem to be limited to screen resolution
Jamovi is fairly fast, but doesn’t fully use the Mac interface (for example, its menus are kept within its own window instead of at the top of the screen; more annoyingly, the open/save dialogue box is very different, though it does show shortcuts for the documents, downloads, desktop, and home folders.) You can, however, drag and drop data files onto it — saving time.
Developer Jonathon Love pointed us to the huge Jamovi library, which, in the library’s words, is a public space or ‘app store’ where you can download modules important to your work.” He wrote, “Our jamovi library is pretty significant — right at the core of what we do ... creating and empowering the community.”
The program is almost 700 megabytes in size, due largely to the integrated software — R, Electron, Mantle, Python, and ReactiveCoca. We haven’t yet run it with our large sample dataset to compare results with other software, but since it’s based on R, it should be accurate and in line with other packages.