Mayo Clinic Announces Move from SAS’ JMP to BlueSky Statistics
This article is originally published at https://r4stats.com
At the useR! 2022 Conference, the world-renowned Mayo Clinic announced that after 20 years of using SAS Institute’s JMP software, they have migrated to the BlueSky Statistics user interface for R. Ross Derkheising, a principal biostatistician with the Clinic, described the process. They reviewed 16 commercial statistical software packages and none met their needs as well as JMP. Then they investigated three graphical user interface for the powerful R language: BlueSky Statistics, jamovi, and JASP.
They found BlueSky meet their needs as well as JMP, for significantly less cost. Then Mayo’s staff added over 40 new dialogs to BlueSky, including things that JMP did not offer. Derkheising said, “I have nothing but the highest respect [for] the BlueSky development team and how they worked with us.” Among others, the Mayo’s additions to BlueSky include:
- Kaplan-Meier, one group and compare groups
- Competing risks, one group, and compare groups
- Cox models, single model, and advanced single model
- Stratified cox model
- Fine-Gray Cox model
- Cox model, with binary time-dependent covariate
- Large-scale data/model summaries via the arsenal package
- Frequency table in list format
- Compare datasets like SAS’ compare procedure
- Single tables of multiple model fits
- Bland-Altman plots
- Cohen’s and Fleiss’ kappa
- Concordance correlation coefficients
- Intraclass correlation coefficients
- Diagnostic testing with a gold standard
Although Derkheising said BlueSky included a “ton” of data wrangling methods, the Mayo team added a dozen more. The result was “gigantic” cost savings, and a tool that, in the end, did things that JMP could not do.
Anyone can download a free and open source copy of BlueSky statistics from the company website. You can read my detailed review of BlueSky here, and see how it compares to other graphical user interfaces to R here. The BlueSky User Guide is online here.
You can watch Ross Derkheising’s entire 17 minute presentation here:
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This article is originally published at https://r4stats.com
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