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Aug 6, 2011 at 5:29 comment added Iterator Btw, for the stratification, you can use coplot().
Aug 6, 2011 at 5:09 comment added Iterator By stratify by post #, I am suggesting that you bin the posts. It can be on an interval scale, such as 0-100 posts, 101-200, etc. Or on a quantile scale: split the users by those in the bottom 10%ile of total posts, 20%ile, etc. Because Skeet has so many posts, it is best to compare him to his peer group, but it's hard to compare him to a peer group of those with precisely the same # of posts - binning the data may help.
Aug 6, 2011 at 5:07 comment added Iterator The idea behind the competing posts is exploratory in nature. Motivation to answer has nothing to do with it. Regarding modeling, it's not that I'm against modeling per se, but that you're not yet ready to do it until you have a better understanding of the data. If you don't understand the data, you won't understand the models.
Aug 6, 2011 at 3:55 comment added Andy W Also I highly doubt competing posts has anything to do with the observed relationships. Do you think people whom have high reputation posted in threads with more competing answers earlier in their history? Your suggestions about including other covariates seem to be conflicting with the suggestion to avoid modelling and focus on plots.
Aug 6, 2011 at 3:50 comment added Andy W (+1) After letting the post sit for awhile, I realized that visualizing the density of the points appears to be a much better solution than trying to visualize the points themselves (although I'm not quite sure what you mean by "stratify by the post #"). I also think plotting the estimated quantiles sounds like a good idea, although for plot 1 & 2 it will likely just be in the massive cloud. Again I don't know what "stratify by time" in this context means either, see Brad Larson's comment on the blog post and my response in regards to this.
Aug 6, 2011 at 2:47 history answered Iterator CC BY-SA 3.0