Trying to have it both ways,
on 18 Apr 2000 08:13:08 -0700, [EMAIL PROTECTED] (Paul R
Swank) wrote:
> Depends on whether you consider a lack of item homogeneity as unreliability
> or not. If your content is supposed to be homogeneous then a lack of
> homogeneity implies your test has problems. If your content is not
> necessarily homogeneous then the reduced alpha appears to say that your
> test is unreliable when that's not actually the case. All reliability
> coefficients suffer from the same problem. They are all sensitive to a lack
> of reliability and something else. Test retest is sensitive to trait
> instability, alternate forms is sensitive to a lack of parallelness, split
> half is sensitive to the bad split, and alpha is sensitive to lack of item
> homogeneity. It's like any statistical model. If the model isn't
> appropriate, the result is misleading.
>
So, Paul S. is claiming that split-half is better because it is not
precise? Or, are we supposed to carefully select the two halves so
they will match, for our split-half reliability? -- that is the one
strategy that might be unbeatable, if you really have a directions on
how to split the scale. But Paul does not say that much, so far as I
can tell. If you don't do that, it seems that it *ought* to be
impossible to favor one accidental split-half, compared to,
"Using alpha, which gives an average of all split-half results."
By the way, the standardized item-alpha (provided, for instance, by
SPSS Reliability procedure) is computed STRICTLY from the
correlations, with no reference at all to variances. Usually, that
should be an optimistic estimate.
Paul Gardner laid out most of the relevant questions, quite well.
--
Rich Ulrich, [EMAIL PROTECTED]
http://www.pitt.edu/~wpilib/index.html
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