A reader asks:
I haven’t found much on your blog commenting on tools you use to track your data. Any recommendations? Have you tried smart phones? For example, I have tried tracking fifteen variables daily via the iPhone app Moodtracker, the only one I found that can track and graph multiple variables and also give you automated reminders to submit data. There are other variants (Data Logger, Daytum) that will graph one variable (say, miles run per day), but Moodtracker is the only app I’ve found that lets you analyze multiple variables.
I use R on a laptop to track and analyze my data. I write functions for doing this — they are not built-in. This particular reader hadn’t heard of R. It is free and the most popular software among statisticians. It has lots of built-in functions (although not for data collection — apparently statisticians rarely collect data) and provides lots of control over the graphs you make, which is very important. R also has several programs for fitting loess curves to your data. Loess is a kind of curve-fitting. There is a vast amount of R-related material, including introductory stuff, here.
To give an example, after I weigh myself each morning (I have three scales), I enter the three weights into R, which stores them and makes a graph. That’s on the simple side. At the other extreme are the various mental tests I’ve written (e.g., arithmetic) to measure how well my brain is working. The programs for doing the test are in R, the data is stored in R, and analyzed with R.
The analysis possibilities (e.g., the graphs you can make, your control over those graphs) I’ve seen on smart phone apps are hopelessly primitive for what I want to do. The people who write the analysis software seem to know almost nothing about data analysis. For example, I use a website called RankTracer to track the Amazon ranking of The Shangri-La Diet. Whoever wrote the software is so clueless the rank versus time graphs don’t even show log ranks.
I don’t know what the future holds. In academic psychology, there is near-total reliance on statistical packages (e.g., SPSS) that are so limited perhaps they can extract only half of the information in the usual data. There are many graphs you’d like to make that it is impossible to make. SPSS may not even have loess, for example. Yet I see no sign of this changing. Will personal scientists want to learn more from their data than psychology professors (and therefore be motivated to go beyond pre-packaged analyses)? I don’t know.
One thing that might help would be if someone could identify a book or resource that would educate work-a-day computer programmers on data analysis. I think we’re special and deserving of a special book just for us. We are capable of implementing analysis if it’s described to us, but woefully incapable of applying it to real data. It’s a painful blind spot for me.
For instance, I find this very interesting:
https://blog.linkibol.com/2010/05/07/how-to-build-a-popularity-algorithm-you-can-be-proud-of/
But the best I could do would be to pick one and implement. I don’t get much insight from reading it.
Painful to admit…
Just wondered if you’re familiar with KXEN and whether they’re making inroads into academic circles.
Also have you tried Tableau for going over the data visually? It’s my personal favourite.
Hi Seth,
I am learning R now, and finding that having a Google form synced to my iphone, which I can then read into R is a flexible way to collect data.
What tools or publications would you recommend for learning more about data analysis and visualization. I’ve been reading the R blogs. In my psych education I received the SPSS approach you critique.
Thanks,
Brian
Seth: Exploratory Data Analysis by John Tukey is pretty good. It is a strange subject, data analysis: Those who do it all the time (practicing scientists) don’t write about it — they don’t write statistics books or even articles — and those who write about it (the authors of statistics books) appear to do not much of it. For a long time statistics textbooks used made-up examples, presumably because their authors had so little contact with actual examples. Psychology professors don’t seem to entirely realize their advantage (considerable experience with actual data) because when they write about statistics they often imitate statistics professors — e.g., most intro stats texts written by psych professors imitate intro stats texts written by stats professors.
Off-topic: They’re only testing drugs they think they can understand, and that’s part of why we aren’t getting miracle drugs.
It would be nice if there was an effective simple way to track and analyze our brain function data for those of us who aren’t computer programmers. Has anyone come up with good simple methods other than Moodtracker?