Top 11 post-game redux: assessing the model

The model was somewhat vindicated last night after a disastrous first week. I made significant improvements to the way it considered the data, and it correctly predicted the bottom 3. As I said, Naima was a sure thing, with Paul and Thia in a dead-heat. In the end, Thia was eliminated. What’s interesting to me is just how far off Dialidol was:

The bottom 6 according to Dialidol

On the one hand, Dialidol got 2/3 of the bottom 3. However, it significantly overestimated Naima, which my model had by a factor of 4 the most likely to be eliminated. I also get no sense that Lauren was possibly at risk, but Dialidol ranked her as fourth worst. Does anybody really believe that?

The WNTS approval ratings were quite different: Continue reading

A logistical model of the Top 11

I’ve been playing around with the numbers, and am able to get a decent projection model with relatively few assumptions. The model is not yet amazingly statistically significant. Nevertheless, the predictions are interesting.

The model assumes that the primary indicators of elimination are Gender, Slot, and whether or not the contestant scored in the bottom 3 on Dialidol and WNTS. You can download the full data set for Top 11 episodes (S4-S9; male is coded as 1, female as 0, and bottom 3 is 1 for yes, 0 for no). Now, we can use R to get a logistical fit Continue reading