Bruce Weaver <[EMAIL PROTECTED]> wrote:
: Paul's post reminded me of something I read in Keppel's Design and
: Analysis. Here's an excerpt from my notes on ANCOVA:
: the analysis of covariance is more precise with correlations greater than
: .6. Since we rarely obtain correlations of this latter magnitude in the
: behavioral sciences, we will not find a unique advantage in the analysis
: of covariance in most research applications.
I've NEVER seen a pre-post correlation less than .4
: Keppel (1982, p. 513) also prefers the Treatments X Blocks design
: to ANCOVA on the grounds that the underlying assumptions are less
: stringent:
He's wrong in the random assignment case; the assumptions are essentially
the same. The ANCOVA estimates are unbiased without any assumptions and
without assumption test exactly the same hypothesis as the simple t test
or the test of change scores (or treatments x blocks) test
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