Andy's Brain Blog Needs Your Help!

To be more specific, I (Andy) need your help; but what's good for Andy's Brain Blog is good for America - and you're all patriots, right?

As I mentioned before, I am currently applying for jobs and putting together my research and teaching portfolios, playing up all the sexy studies currently in the works, and what I plan to do for the next few years; how I can attract students to the university, students to the department, secure money, funding, recognition, and all that good stuff necessary for the vitality of the university.

However, as all of you know, this right here is one of my dearest, most ambitious projects - to make statistics, neuroimaging, and computational modeling available to everyone in straightforward, simple terms. To use online repositories to get at data unavailable to the majority of smaller, liberal arts institutions, so that students from all parts of the globe, researchers anywhere, and quite literally anyone with a computer can get a piece of the action. To make the information in dense, unreadable technical manuals accessible and easy to understand through hands-on, no-nonsense tutorials. And - perhaps most importantly - I wear a suit when I do it.

I want to continue doing this. I want to continue building, expanding, and teaching, both here and in the classroom. I will not rest: I will drink life to the lees. Heck, maybe I'll even drink the lees too.

But to do that I need your help.

Through both the comments here, on the YouTube channel, and in private correspondence, I've talked with many researchers, students, and professors around the country and around the world. Most of you I've never seen, but I've had the privilege to help out professors and scholars all the way from Italy to China; I've freelanced for PET researchers at Michigan State, schizophrenia experimenters at Indiana, designed experiments for primates in New York. The AFNI tutorials created here have been used as class material at the University of Pittsburgh, and my code for Hodgkin-Huxley simulations have been used for demonstrations at Claremont McKenna College in California. My recipe for homemade granola is used by several hungry researchers to keep them going throughout those long afternoons. The list could go on.

What I ask for is if you have ever used the materials here in an educational setting, be it for the researchers in your lab or the students in your classroom, please let me know by sending an email to ajahn [at] indiana [dot] edu. I am trying to compile a list of where it is used, to demonstrate its use and effectiveness.

Lastly - allow me to get real here for a moment - I've thought of all of you, each person that I've conversed with or replied to or Skyped with, as my children. And not as "children" in the sense of putting you all down on my tax returns as dependents; although, if the IRS isn't too strict about metaphors, I think I could get away with that. No, I've thought of you as real children: Shorter than I am, a little incoherent at times maybe, often trying to get my attention, and playing with Legos and Gak.

Regardless, it's been one of my great pleasures to help you all out. Now get away from that electrical socket.

Bayesian Inference, Step 2: Running Bayesian Inference with Your Data

If you've had the opportunity to install R Studio and JAGS, and to download the associated programs needed to run Bayesian inference, it is a small step to actually getting your parameter estimates. Two of the programs from the BEST folder - BESTExample.R, and BEST1G.R - allow you to run independent-samples and one-sample t-tests, respectively. All that's required is changing the input in the "y1" and "y2" strings with your data, separate each observation with a comma, and then run the program. Other options can be changed, such as which value you are comparing against in the one-sample t-test, but everything else can essentially remain the same.

I realize it's been a while between posts, but right now I'm currently in the process of applying for jobs; this should start to pick up again in mid-October once the deadlines pass, but in the meantime, wish me luck!

Bayesian Inference, Step 1: Installing JAGS On Your Machine

Common complaint: "Bayesian analysis is too hard! Also, I have kidney stones."
Solution: Make Bayesian analysis accessible and efficient through freeware that anyone can use!

These days, advances in technology, computers, and lithotripsy have made Bayesian analysis easy to implement on any personal computer. All it requires is a couple of programs and a library of scripts to run the actual process of Bayesian inference; all that needs to be supplied by you, the user, is the data you have collected. Conceptually, this is no more difficult then entering in data into SAS or SPSS, and, I would argue, is easier in practice.

This can be done in R, statistical software that can interface with a variety of user-created packages. You can download one such package, JAGS, to do the MCMC sampling for building up distributions of parameter estimates, and then use those parameter estimates to brag to your friends about how you've "Gone Bayes."

All of the software and steps you need to install R, JAGS, and rjags (a program allowing JAGS to talk to R) can be found on John Kruschke's website here. Once you have that, it's simply a matter of entering in your own data, and letting the program do the nitty-gritty for you.