How bad is the math?
Most of it is downright awful. That's why we will be using "R."
My
ability with arithmetic is notoriously bad. On my first date I
left a chintzy 5% tip because I did the arithmetic wrong... Let's
see... knock off the last digit, take half of that, and then add.
Except I forgot to add back the 10%, so voila, a 5% tip! If
you expect me to add, subtract, divide, or multiply on the spot you
will be bitterly disappointed. It is a frightening thought that I
was the secretary-treasurer of the AAPA for four years, but that is
what spreadsheets and Quicken are for.
And my training in
mathematics has been quite rudimentary. I had a semester of
probability theory as a freshman in college, a semester of statistics,
and a semester of "calculus for those who don't really want to take
calculus but have to anyhow" (the official title was "A Brief Survey of
Calculus"). In graduate school I took a year's worth of
statistics through the anthropology department. But even so, it
was not until I did a postdoc in a genetics department that I became
more than passingly familiar with maximum likelihood estimation.
Download the whole kit and kaboodle
For those of you who will not have wi-fi at the Workshop, you can download all the "stuff" as a *.zip file. Unzip this to a working directory. You will still need to download and install the stuff listed in "Download 'stuff'' ", but then you will be all set to do the Workshop off-line.
Now, on to the "goods" :
- Download "stuff"
- For this workshop we will be using "R" and "OpenBUGS." And when
I say "we" I mean it. You will want to download these packages so
that we can work through material at the workshop.
- A handy-dandy couple of pages about R.
- List
of "R" packages you will need to download and why we need 'em.
See "download stuff" above which shows you how to download and
install packages within R. It is very easy to do.
- coda - This is a package that does handy stuff with the output from a Markov Chain Monte Carlo (MCMC) package such as OpenBUGS.
- Daim - Stands for "Diagnostic accuracy of classification models"
(which seems like it should be Dacm, no?). It does the "old
stuff" (cross validation), but also leave one out bootstrap, 0.632, and
0.632+.
- HDInterval - Does one thing and one thing only - hdi - which means find the highest posterior density interval
- RUE4R
- Get it? Are you red-E for R? I suggest you work through
this on your own ahead of time, unless you are already familiar with R.
- Multivariate summary statistics, pdf (not the Adobe kind), and calculus
- This is a bit of a hodge-podge. The "multivariate summary statistics"
part is my soapbox about either making multivariate data available, or
if not, at least making the summary multivariate statistics avaiable.
The "pdf" is an introduction to using probability density
functions, of which we will use the simplest (the uniform). And
the "calculus" part is just to let you now that help is always
available, either online from SimPy Gamma or from a downloaded package (WxMaxima).
- Perinatal age estimation - Bayes rears his ugly (?) head and our first taste of OpenBUGS.
- Stature - Examples from a dandy recently published book with Dr. Bartelink as one of the co-editors.
- Size & Shape - a la Darroch and Mossiman, which we will use for the discriminant function analysis below.
- Discriminant Function - sans Fordisc