[Original post has not appeared in my SPSS mail]
If the testing is apparently being performed on N= 46 million,
and that is what accounts for the results that are not useful,
then the obvious quick-fix is to divide all the weights by 946
so that the testing reflects the (overall) original N of the analysis.
Whether that is what you ought to do is trickier. I have never
liked having tests that are done on weighted data. (And the
more change in cell N's that you introduce by weighting, the more
questionable the tests are.)
--
Rich Ulrich
> Date: Sun, 2 Dec 2012 06:42:25 -0800
> From:
[hidden email]> Subject: Re: Multinomial regression and weighting problem
> To:
[hidden email]>
> Please post your syntax. At the moment, it's not clear, for example, whether
> you are using CSLOGISTIC or NOMREG in conjunction with WEIGHT CASES (or
> something else).
>
> HTH.
>
>
> n90 wrote
> > Hi,
> >
> > I'm conducting a multinomial logistic regression on some British Crime
> > Survey data. For this analysis I need to weight the dataset in order to
> > account for sampling biases.
> >
> > The problem I'm having is when I apply the correct weight and run the
> > multinomial regression, my model fitting criteria for the model fitting
> > information and likelihood ratio test come up with a blank (...). As a
> > consequence, everything in my model is coming out as significant, which I
> > know is wrong.
> >
> > I have run the model before using a different weight, which I now know is
> > wrong for use in my particular analysis, so I believe there is a problem
> > with this new weighting, rather than any of the other inputs into the
> > model.
> >
> > Has anybody else had experience of this? If it's a problem with the
> > weighting is there anything I can do to fix it?
> >
> > If it helps the unweighted sample size is 46,484 and weighted is
> > 43,974,190.
> >
> > Any help would be very much appreciated!
>
> ...