I've just posted the data and problem description for Project #2. You'll find the link on the lecture detail page for tomorrow.
As promised (threatened?), you're going to have to fire up WinBUGS again for the solution. That's the bad news. The good news is that you can take the full-sib, half-sib code that I posted when we were talking about variance partitioning on Monday, change the numbers for the number of individual, the number of sires, and the number of dams, and find yourself most of the way to the solution.
Strictly speaking, you wouldn't have to fire up WinBUGS. You could fire up R, SAS, SPPS, or another statistical package and estimate variance components there. But if you do, you'll also need to figure out how to bootstrap over full-sib families to get confidence intervals for your results. While that's possible, it may not be very easy, and I'm afraid you'll be on your own if you try it that way. We won't be able to offer any advice. (Now if you wanted to combine mcmcsamp() with lmer() results in R, I could help you, but (a) you'd need to understand what mcmcsamp() does and you'd need to be familiar enough with R to write your own code to analyze the results it gives you.)
As promised (threatened?), you're going to have to fire up WinBUGS again for the solution. That's the bad news. The good news is that you can take the full-sib, half-sib code that I posted when we were talking about variance partitioning on Monday, change the numbers for the number of individual, the number of sires, and the number of dams, and find yourself most of the way to the solution.
Strictly speaking, you wouldn't have to fire up WinBUGS. You could fire up R, SAS, SPPS, or another statistical package and estimate variance components there. But if you do, you'll also need to figure out how to bootstrap over full-sib families to get confidence intervals for your results. While that's possible, it may not be very easy, and I'm afraid you'll be on your own if you try it that way. We won't be able to offer any advice. (Now if you wanted to combine mcmcsamp() with lmer() results in R, I could help you, but (a) you'd need to understand what mcmcsamp() does and you'd need to be familiar enough with R to write your own code to analyze the results it gives you.)
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