Hi Ted, I have read the paper. I understand the "Likelihood Ratio for Binomial Distributions" part. However, I cannot make a connection with this part and the contingency table.
In order to calculate Likelihood Ratio for two Binomial Distributions you need the values: p, p1, p2, k1, k2, n1, n2. But the information contained in the contingency table are different from these values. So, again, I do not understand how the information contained in the contingency table is linked with Likelihood Ratio for Binomial Distributions. In order to find the similarity between two users I tend to think of the boolean preferences of user1 as a sample from a binomial distribution and the boolean preferences of user2 as another sample from a binomial distribution. Then use the LLR to assess how likely these distributions are the same. But I don't think this is correct since this calculation does not use the contingency table. I hope my question is clear. Thanks. On Mon, Apr 28, 2014 at 2:41 AM, Ted Dunning <[email protected]> wrote: > Excellent. Look forward to hearing your reactions. > > On Mon, Apr 28, 2014 at 1:14 AM, Mario Levitin <[email protected] > >wrote: > > > Not yet, but I will. > > > > > > > > Have you read my original paper on the topic of LLR? It explains the > > > connection with chi^2 measures of association. > > >
