Repeated Measures Workshop now with R and… maybe SAS

by Karen Grace-Martin


I’m happy to announce that our workshop on Analyzing Repeated Measures Data will now offer examples in R (and maybe SAS too—see below). It starts next Friday, January 25th.

The background: When I recommend resources to a researcher who needs to learn and implement a new statistical method, I have always been frustrated by excellent applied statistics books that use only one type of stat software. These aren’t text books with perfect but meaningless data, they’re those fabulous books that explain what matters and what doesn’t and show the actual steps to take when applying the analysis and what it all means.

These are the best books, and it’s the approach I’ve always taken in creating my workshops.

I get frustrated because it’s hard to convince a researcher who uses one software package to read a book about how to implement a technique with examples in another. (Insert the software of your choice—it doesn’t really matter which one).

My goal all along has been to offer all my stat workshops with support for multiple software packages. I’ve gotten further along with some of them than others, but I’m working on it.

So I was pretty happy during the last Repeated Measures workshop when one of the participants, Dan Neal, mentioned he was working out all the exercises in R.

It turns out that Dan is a statistical consultant at the University of Florida, and he uses SPSS, SAS, and R. He has very graciously agreed to share his R code for all my demonstration examples and exercises AND to attend as many of the Q&A sessions as his schedule permits to answer any R questions.

Pretty awesome, huh?

We’ve always had a few participants who use all sorts of software—Stata, Systat, JMP, SAS, etc. They still say this workshop is entirely worthwhile because the focus is on the concepts, the steps, and what it all means.

Even so, it’s nice when it’s laid out for you in the terms you’re used to.

Okay, what about SAS?

As I mentioned, all along I’ve planned on adding SAS examples to this workshop. I actually learned linear mixed models in SAS first and had to teach myself how to do it in SPSS later.

Update on SAS: We did have a lot of interest for including SAS, so we have fully added SAS to the workshop as well.

Get all the details and enroll (and see a nice picture of Dan) here:

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