As a statistician, you’re likely already familiar with SAS and the value it brings to data analysis. But in this ever-evolving world of statistics and data science, relying on your go-to language might not be enough to stay competitive anymore. The open-source language R is gaining traction within the healthcare industry as a powerful tool for analyzing complex datasets.
In this episode, join me while I talk about why learning R can help you stay ahead of the game—and why now is the perfect time to dive into its growing popularity among healthcare and pharma programmers and statisticians alike.
I specifically talk about the following points:
- SAS is no longer focussing on pharma and has shifted the priority into other industries such as finance.
- R offers various benefits, including cost savings, innovative methods, universities shifting towards R, simpler/cheaper training due to its open-source approach, and much more.
- More statisticians are considering transitioning from SAS to R; The Effective Statistician Academy offers a course designed for this purpose.
- Learning R is not meant to replace SAS but supplement it (at least for the mid-term)
Transcript
[00:00:00] Alexander: Welcome to another episode of The Effective Statistician, and this is another of these short episodes. By the way, if you hear some birds in the background, that is because what I’m recording says in my garden is just such a beautiful weather. And I’m taking the opportunity to record it in the garden cuz it’s such a nice weather and the sun is shining and so probably have a little bit of a different atmosphere here.
Today you can actually skip this episode if you are not programming at all. You can also skip this episode if you’re completely fluent in art. But if you are working mostly in SAS, then this is the episode for you.
SAS has been the main part and pretty much the only language that we have programmed in within the pharmaceutical industry for very long time. When I started in the industry in the early 2000’s, there was just SAS SAS , but already at that time there was a new kid on the block.
Ah, this new kid has grown into a real big competition compared to SAS. And from what I can see, SAS has really moved away from the pharma area. I think they are making much more money in finance and all kind of other industries. They are not investing so much and it’s a different statistical tools that we need. And now there are lots of initiatives that drive companies away from SA S to R. There’s companies, and I think the biggest one and the most exciting one in that direction is Roche. They are completely moving into R, for many different reasons. First is of course the cost side. Yeah. So licenses for us are definitely not cheap, and of course licenses are just part of the overall cost structure, but they have looked into it and have overly seen that R, it’s cheaper.
The next thing is I think our will become much more important because all the different innovative methods. Come of with some our packages, but not with SAS packages. CERT is because it’s for free. Look at these different universities. They have moved massively from SAS to R and so all the new people coming into the industry know about R, they don’t know about SAS. So from a training perspective, it is much easier to do something an R for the companies because they don’t need to invest in training and training’s really expensive through the open source, approach of R. There’s also a lot of benefits, and you can scroll back into discussions I had with Thomas Nietman about these kind of different benefits of R. Now, why should you now move to learn R if you are good in SAS? I think because sooner or later you must do, but also because it offers you lots of opportunities, especially on all different sides of data visualization.
If you look into the data visualization that are submitted to the special interest group for visualization within P and SPI, nearly all of them are using R. Lots of things are very easy and fast to do with R. You can try out lots of different things very easily. You can get lots of code on around the internet and the community is growing so fast, so you can work much more effectively using R And if you want to move from fast to R of course there’s, some material on the internet, but very often it is pretty generic. And it is self-learning only, and that’s where the SAS to our course that The Effective Statistician Academy comes in. Thomas Nietman who is an absolute super guru, I would say on the R side, has provided this training quite a lot of time, and now he is providing this through the Effective Statistician Academy, and you can just enroll in it.
Through this program, you will learn directly from Thomas how to move effectively from SAS to R, step by step, and you’ll have the opportunity to ask many different questions. He’ll speak in your language, not in some kind of, generic non-pharma language, but really about all the different needs that you have, all the different concerns that you have.
What about validation? What about packages? What about all these different single steps that you have when you actually program? Yes. Usually it’s the devil in the details, and Thomas has pretty much all the answers to that. So have a look into The Effective Statistician Academy. Look for the SAS to R course with Thomas Nietman, and enroll into it now. We are doing these live sessions over the next months, and you’ll have a very good and fun time learning about R and stepping easily from SAS to R. Improve your own skills and become an effective statistician.
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