A search with Google on keywords "Overdispersion" or "Extra Binomial Variation" results in a number of relevant references for your case.
Jos Jansen "nothanks" <[EMAIL PROTECTED]> wrote in message [EMAIL PROTECTED]">news:[EMAIL PROTECTED]... > Jay Tanzman <[EMAIL PROTECTED]> wrote in message news:<[EMAIL PROTECTED]>... > > nothanks wrote: > > > > > > Hi folks, > > > > > > I am trying to develop a reasonable (not 'perfect') > > > logistic/binary model and would appreciate > > > critiques/suggestions/references. > > > I'll start with an example of data: > > > > > > Suppose I have 10 cases, each with a binomial outcome > > > (with n_1, ..., n_10 trials) and let's say 2 predictors, > > > gender and age. For example case one has n_1=7 trials and > > > 2 successes, case 2 has n_2=1 trial and 0 success, etc. > > > > > > Suppose the binary outcomes are legal decisions (say success > > > is 'guilty') and each of the 10 cases corresponds to 10 judges. > > > > To clarify, "sex" and "age" are characteristics of the judges? > > > > -Jay > > Yes. And there's no jury - think of it as traffic court. > Also, the actual data has many more predictors with a mix > of nominal and continuous variables. So, it is unlikely > another judge will have the exact same covariate pattern. > Which leads me to think, perhaps, that each "judge effect" > is accounted for implicitly by his/her unique covariate > pattern. ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
