Thank you Paige However, I think you are one stage ahead of me. It seems to (statiscally naive!) me that p value in the model you suggest will be strongly dependent on the nature of the 'head-to-head adjustment' and the (highly correlated) ELO Prediction. Am I missing the point here (quite probably...LOL)? Do I have to assume a model first or is there a way to test whether the 'head-to-head' is a reasonable predictor, once the influence of the the ELO ratings difference has already been accounted for?
> Prob of winning = (ELO Prediction) + p * (head-to-head adjustment) > + error > > If this is a reasonable model, then you want to test whether or not > the parameter p is equal to zero (Null hypothesis), or if it is a > positive number (alternative hypothesis). How you perform such a > test depends on what assumptions you want to make about the errors > and the rest of the data. > > However you are closer to the problem and so it may be that you can > write down a better model. If you do so, then the parameter of the > model that you are interested in will be clear, and the hypotheses > should also be clear > > -- > Paige Miller > Eastman Kodak Company > paige dot miller at kodak dot com > http://www.kodak.com > > "It's nothing until I call it!" -- Bill Klem, NL Umpire > "When you get the choice to sit it out or dance, I hope you dance" > -- Lee Ann Womack . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
