R has a lot of nice plotting features built in, but this add-on package adds some more, especially the ability to designate a break in one of your axes. Continue reading
Monthly Archives: February 2014
Recommended: A guide to the line style arguments for R graphics
Melissa Clarkson created a very nice two page PDF file that shows very clearly the sometimes subtle difference in how various line style arguments work in R. Highly recommended for any R programmer. Continue reading
PMean: NIH is interested in big data
The National Institutes of Health has shown a recent interest in “big data.” You can define big data in several ways, but a common characteristic is the three V’s. Big data takes up a lot of space (volume) and/or it comes at you very rapidly (velocity) and/or it comes in a wide range of differing formats (variety). One of the recent Requests for Applications (RFAs) from NIH spells out what types of research into big data that they are interested in seeing. I might be interested in applying, and would love to find some collaborators. Here’s a summary of what the RFA is all about. Continue reading
PMean: How many months should you wait before re-testing?
I got a question that I had never heard before, and it sort of is a statistics question and sort of isn’t. A researcher was comparing two methods of training residents in a particular surgical procedure and wanted to know how long you should wait between the training and the evaluation of whether that training was effective. Continue reading
Recommended: Why Coincidences, Miracles And Rare Events Happen Every Day.
This is an interview with David Hand, the author of a new book, The Improbability Principle: Why Coincidences, Miracles and Rare Events Happen Every Day. The discussion raises the issue of events that seem highly improbable based on a simple probability calculation, but which nevertheless, are not that uncommon. Continue reading
PMean: Summary of my research interest in patient accrual in clinical trials.
My boss at UMKC (I’m part-time at UMKC and part-time independent statistical consultant) asked me for one of those “summarize the research you’ve been working on” so she could mention all the work being done by our Department for a talk she’s giving. Recently, I’ve been focused almost exclusively on one thing, and although she knew it very well, I sent her a summary anyway. Then, I thought, why not share the same summary on my blog. Maybe you’re curious or maybe you might be interested in collaborating. So here’s my summary about my work on Bayesian models for patient accrual in clinical trials. Continue reading
Recommended: Why randomized controlled trials fail but needn’t: 2. Failure to employ physiological statistics, or the only formula a clinician-trialist is ever likely to need (or understand!)
This page is moving to a new website.
Quote: Because statistics has too often been presented …
This page is moving to a new website.
Recommended: Troubleshooting Public Data Archiving: Suggestions to Increase Participation
This page has moved to a new website.