On 10 Apr 2004 19:41:22 -0700, [EMAIL PROTECTED] (Roger Levy) wrote: > Richard Ulrich <[EMAIL PROTECTED]> wrote in message news:<[EMAIL PROTECTED]>... > > On 10 Apr 2004 09:37:16 -0700, [EMAIL PROTECTED] (Roger Levy) > > wrote: [ snip, some] > > > > "There is no precise answer to this question, but the more > > independents, the more likelihood of multicollinearity. > > Also, if you have 20 independents, at the .05 level of > > significance you would expect one to be found to be > > significant just by chance. A rule of thumb is that there > > should be no more than 1 independent for each 10 cases in > > the sample. In applying this rule of thumb, keep in mind > > that if there are categorical independents, such as > > dichotomies, the number of cases should be considered to > > be the lesser of the groups (ex., in a dichotomy with > > 500 0's and 10 1's, effective size would be 10). " > > ---- end of extract from Garson. > > Thanks for the reference, but unfortunately it doesn't seem to use the > term "non-case" at all so this doesn't really answer my question.
Once again, I wonder at how this communication is missing. It seems clear to me that I am talking about the dichotomy of the criterion, the 0s and 1s, and the extract is, too. We can call them Cases/Non-cases, or something else. The total N is the sum; but the effective N, for looking at power and robustness, is the smaller of the two numbers. > > > > > You might find the whole document interesting to scan. > > [snip, more of mine] > > > > > > By a "distinct covariate vector" I mean the following: with n > > > covariates (i.e., predictors) X_1,...,X_n, a covariate vector is a > > > value [x_1,...,x_n] for a given data point. So, for example, if I > > > have a half-dozen binary covariates, there are 2^6=64 logically > > > possible covariate vectors. > > > > Now I wonder what computer program you are using. > > I'm sorry, but I fail to see how that is relevant at all. The idea of > a covariate vector is high-level and theoretical and has nothing to do > with implementation. As a term, incidentally, "covariate vector" is > quite widespread (try searching for it in "Books" on Amazon) and I > don't see where the confusion is arising. I know about the ordinary covariate vectors. But I think ML Logistic packages of the last decade have not worried about them, the 2^6 set. Maybe I need to re-read some documentation, but that is why I wonder if you are working with old documentation. -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
