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Lois,
=0D
I will post this response- to your request for =
clarification - publically, in case anyone else =
has the same questions. Your questions really =
get to the heart of the issues.
=0D
The actual numbers I put in the grid were
not meant to simulate any type of synthesis.
They were chosen at random and should not be =
interpreted as anything but an illustration of how we =
might set up a grid to study formal causes. With a =
real grid, the correlations that exist would be an =
empirical matter. The illustration is not a real grid.
=0D
Causation is not correlation. Some correlations are =
noncausal.They reflect incidental clumping of =
characteristics. It would be syncretistic to equate =
correlation with cause. =
=0D
Lets say education is PART of wisdom and =
competence, but only part. Wisdom would also =
require being careful and perhaps other constructs. =
=0D
Similarly, Competence is only partly made up of =
education. Talent, motivation, and other constructs =
may go into making up competence. Wisdom and =
competence may be constructed from education ( I am =
not saying this so in reality- just a hypothetical =
example), as well as being constructed from other =
constructs. Thus wisdom and competence would =
be more complex than education. =
=
Wisdom, would, if this model were true, logically =
imply education. Education would not logically =
imply wisdom- even if it has some statistical power =
to predict wisdom. There may be some foolish but =
educated people. Competence would also logically =
entail education. Competent people are educated. =
But education would not logically imply competence. =
Some educated people are incompetent. This =
asymmetry of implication is the core of the issue and =
is what distinquishes corresponding regressions from =
correlations and other correlation based methods like =
LISREL.
=0D
Wisdom and competence would not logically entail one =
another, even if their existences are correlated, =
incidentally. Wisdom could exist without competence, =
competence without wisdom. They are not subsets of =
one another, even though they may both separately
include education as one of their own subsets. They =
do not cause one another just because they share a
common subset. =
=0D
Thus wisdom and competence would not simply be a =
euphemism for education, since they are more than =
education and do not equal one another.. =
=0D
In the real world we do not know what causal model =
the person is using. By using corresponding regressions, =
we can discover what model they are implicitly using
(I think). =
=0D
Bill =
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