From the course: Descriptive Healthcare Analytics in R

Choosing R for a BRFSS analysis: More considerations - R Tutorial

From the course: Descriptive Healthcare Analytics in R

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Choosing R for a BRFSS analysis: More considerations

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- This movie builds on my last movie and discusses more items for you to consider when selecting a statistical software to be used for your BRFSS analysis. These other considerations could impact the time and effort needed for the project. For example, while SAS has a popular customer service line well-staffed with experts, R is open source, so it is "do it yourself." There is no tech support line, only the voluminous documentation about R online. The comprehensive R archive network, CRAN, is where you go to download the R program and also access official documentation. R users also provide many helpful webpages, such as blogs from the R bloggers site. Stack Overflow is a popular site where R users post and answer each other's questions. So as you can see, you can usually find what you need on the web for help. But if things go really wrong, you may need to hire consultants. Admittedly, spending time hunting for answers on the web can affect your bottom line. So until you build up a code bank of R code for BRFSS, there will be some overhead. On the other hand, if you actually don't know SAS and you don't know R, starting with R might be advantageous. This is because learning SAS is extremely difficult. R is not as easy as the menu-driven SPSS, but it is much less troublesome to learn than SAS. Further, people tend to learn R from reading documentation posted on the web, while SAS users are accustomed to taking classes and having hands-on seminars. Essentially, these are needed to help users understand the complex SAS program. You can see why it is hard to weigh the pros and cons of not using SAS for a BRFSS analysis. Finally, I want to point out that SPSS is generally not used for a BRFSS analysis, although it can be. The reason I think it is not used is because BRFSS analyses are often done with a group and SPSS is not good with sharing group files and coordinating with a group. It is a software that's more easily used in a single-analyst project. Both SAS and R are equally easy to use in a shared project. I have done shared projects with both of them using Dropbox as the sharing platform. I feel it is important to point out that R's open-source status brings both advantages and disadvantages to the consideration of being used in a BRFSS project. However, I am a big proponent of open-source, so I lean towards trying to overcome the disadvantages. The R Consortium is the group that provides support for R and deserves a shout out for their helpful work supporting researchers who are using their software. In summary, the advantages of choosing R for a BRFSS analysis is that you are making a statement of support for open-source software and also, you are getting the software for free. This may be an advantage if you do not have a SAS analyst available anyway and may give you or another analyst the opportunity to learn a new language. The main disadvantages of R include the time-consuming and often frustrating "do it yourself" approach. It is important to highlight that BRFSS files and resources are not available in R, so that can add to the overhead of using R for a BRFSS analysis. Finally, R expertise is not as common as SAS expertise, so there may be a learning curve involved if you choose to adopt R for a BRFSS analysis. In conclusion, the purpose of this course is to teach how to analyze the BRFSS in R, so hopefully, if you are used to using another software and you don't have any background in R, that won't matter. You'll be able to get through a BRFSS analysis without the overhead of having to search for code and get it running. You will gain experience using R resources and building R code. This course will help you see the advantages of using R in a BRFSS analysis.

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