I get a lot of questions along the lines of “I want to learn R, can you help me?” or “Where can I learn more about R?” or some other variation. These questions are usually from people who are total beginners or who have just started with R. I don’t have a good answer for them, because learning anything new is hard. But let me try here to outline a few things you can do. Some of these, I have no personal experience with, but have heard recommendations. Continue reading
Tag Archives: R software
PMean: Examining relationships in R
I’m giving a talk for the Kansas City R Users Group on how to get a preliminary impression of relationships between pairs of variables. Here is the R code and output that I will use. Continue reading
PMean: Missing values in R talk
I’m talking a bit about missing values in R this afternoon for the Kansas City R Users Group. Here is what I’ll be talking about. Continue reading
Recommended: New R Package: cdcfluview
I work a lot with secondary datasets and I’m always looking for new and interesting resources. There is a CDC site that tracks flu reports and with a bit of effort, you can get the raw data behind these reports. A blogger, hrbrmstr (Bob Rudis, if you dig long enough to find his real name), developed an R package that makes it easy to import this data into R. He illustrates the use of this package with a graph that shows some interesting trend lines across several major cities. Continue reading
Recommended: Tessera. Open source environment for deep analysis of large complex data
I have not had time to preview this software, but it looks very interesting, It takes large problems and converts them to a form for parallel processing, not by changing the underlying algorithm, which would be very messy, but by splitting the data into subsets, analyzing each subset, and recombining these results. Such a method “Divide and Recombine” should work well for some analysis, but perhaps not so well for others. It is based on the R programming language. If I get a chance to work with this software, I’ll let you know what I think. Continue reading
PMean: Cox regression in R
I wanted to show a couple of Cox proportional hazards regression models in R for a talk I am giving for the R users group. Continue reading
PMean: More Kaplan-Meier curves in R
I found a larger data set and wanted to show how you could use the Kaplan Meier curves as a preliminary screen of some categorical and continuous variables in a larger and more complex data set. Continue reading
PMean: Kaplan-Meier curves in R
I am giving a talk about using R for survival analysis and I wanted to talk first about the Kaplan-Meier curve and how you might draw it in R. Continue reading
Recommended: FDA: R OK for drug trials
This blog post reviews a presentation by Jae Brodowsky, a statistician with the U.S. Food and Drug Administration that put to bed the rumor that FDA will only accept submissions where the data analysis was done by SAS. The summary does mention that FDA has certain regulatory requirements for R (or any other statistical package, including SAS). Continue reading
PMean: History of R
I’m helping to put together three separate classes, Basic data management and analysis with R [SAS / SPSS]. As part of these classes, I need to discuss the history of these programs, because understanding that history will help you better understand the strengths and weaknesses of each statistical package. Here’s a brief history of R. Continue reading