So long Vanderbilt, and thanks for all the fish!

After finishing the final revisions on my dissertation I was reminded of this spot-on graphical guide to what a Ph.D. is really all about.

Now that I'm finished, I'm leaving Vanderbilt to start a postdoc in genetic epidemiology with Dr. Loic Le Marchand at the University of Hawaii Cancer Center. Posts may be sparse over the next few weeks, but I plan on blogging as usual once I'm set up at my postdoc. Because I won't have the same level of statistical and bioinformatics support in Hawaii that I have now, I'll have much to figure out on my own, so I'll have even more to write about here. But for now, enjoy this Illustrated guide to a Ph.D., reproduced with permission from Matt Might, and follow me on Twitter (@genetics_blog).

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Imagine a circle that contains all of human knowledge:

By the time you finish elementary school, you know a little:

By the time you finish high school, you know a bit more:

With a bachelor's degree, you gain a specialty:

A master's degree deepens that specialty:

Reading research papers takes you to the edge of human knowledge:

Once you're at the boundary, you focus:

You push at the boundary for a few years:

Until one day, the boundary gives way:

And, that dent you've made is called a Ph.D.:

Of course, the world looks different to you now:

So, don't forget the bigger picture:

Keep pushing!

R function for extracting F-test P-value from linear model object

I thought it would be trivial to extract the p-value on the F-test of a linear regression model (testing the null hypothesis R²=0). If I fit the linear model: fit<-lm(y~x1+x2), I can't seem to find it in names(fit) or summary(fit). But summary(fit)$fstatistic does give you the F statistic, and both degrees of freedom, so I wrote this function to quickly pull out the p-value from this F-test on a lm object, and added it to my R profile. If there's a built-in R function to do this, please comment!