Siegel and Castellan, Nonparametric Statistics for the Behavioral Sciences
(2nd ed., McGraw-Hill, 1988), discuss partitioning the degrees of freedom
and analyzing residuals in r x k contingency tables. They argue that,
because individual cell residuals are not independent, it is safer to
combine the analysis of residuals with a partitioning analysis rather than
to assess significant cell-level differences with standardized residuals
alone.
Michael Willmorth, Ph.D.
Senior Study Director
Clearwater Research, Inc.
Boise, ID, USA
(208) 376-3376, ext. 259
(208) 376-2008 (FAX)
Web site: http://www.clearwater-research.com
"Alan McLean" <[EMAIL PROTECTED]> wrote in message
[EMAIL PROTECTED]">news:[EMAIL PROTECTED]...
> Hi to all,
>
> For some years I have been teaching a technique which I know as testing
> the components of chi square in a standard contingency table problem. If
> you calculate the standardised residual
>
> SR = (fo - fe)/sqrt(fe)
>
> for each cell, these residuals are approximately normally distributed
> with mean zero and standard error given by
>
> SE = sqrt((1 - rowsum/overallsum)*(1-columnsum/overallsum))
>
> provided the expected frequencies are large enough (as for the use of
> chi square itself).
>
> My problem is that I have no source for this technique. I have never
> seen it in a textbook. (I have no doubt about its validity, and frankly
> don't understand why textbooks do not refer to it.)
>
> Can anyone give me a reference to it? Ideally, a reference to its
> original publication.
>
> My thanks in advance.
> Alan
>
>
> --
> Alan McLean ([EMAIL PROTECTED])
> Department of Econometrics and Business Statistics
> Monash University, Caulfield Campus, Melbourne
> Tel: +61 03 9903 2102 Fax: +61 03 9903 2007
>
>
>
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