On 21 Apr 2000 17:25:01 GMT, [EMAIL PROTECTED] (Wen-Feng
Hsiao) wrote:
> Dear Ulrich,
>
> Thanks for your reply. I have obtained a book of Agresti from library --
> Statistical Methods for the Social Sciences, 2nd edition. I fortunately
> locate Section 7.4 titled 'comments concering nonparametric statistics'
> (p. 186), which explictly addresses the problem of treating ordinal
> variables as interval variables. It mentioned that the scoring system
> assigning scores 1, 2, 3, 4, and 5 to the five categories, say, very
> liberal, slightly liberal, moderate slightly conservative, very
> conservative, is quite dangerous...
>
> But from your text, you incline to deem 5-point scale as an interval
> scale. I wonder if there is any research which explicitly address this
> question? I mean those researches which show that using interval scale
> analysis is all right. If so, how about 3 or 4 points scale?
>
> By the way, I don't find text related to the alternative scorings for
> ties in Agresti book. Could you give me a more specific reference, say
> book name.
See Agresti's "An Introduction to Categorical Data Analysis", section
2.5.2 on alcohol and infant malformation. It includes the computation
of average ranks, and condemnation of those results. It shows you how
badly the ranking can perform. In this example, the scoring of (1-5)
does not work as well as using the midpoint for each category, since
the latter exaggerates the spacing between the upper categories.
The same data are included in his earlier book, "Categorical Data
Analysis", as problem 4.8 on page 125, without direct discussion.
As to your Agresti citation: Are you sure of that? I can't imagine,
right off, how giving scores of 1-5 to an ordinal set can be "quite
dangerous." There are no outliers, which is the usual risk of
disruption of the variance. There are no "in-liers" if I may use
that label, to describe the under-weighting of the responses (3,4,5)
in the alcohol data.
I have never seen that text, but my local library supposedly has it,
so I will try to say more, after I have seen it.
--
Rich Ulrich, [EMAIL PROTECTED]
http://www.pitt.edu/~wpilib/index.html
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