William Chambers wrote:
>
> Gus,
>
> You are making a defense of studying distributions as they are thrown at us
> by nature/circumstances, This seem the way to go to social scientists
> because we tend to believe that our causes are embedded in all sorts of
> complex interactions and can not be isolated from their context, If we look
> however to the physical sciences, we see a very different strategy, The
> chemist tends not to go out and perform experiments on naturally occuring
> clusters of chemicals, Instead, she isolates each chemical and then studies
> their interactions in pure states, so that the fundamental mechanisms of
> causation are revealed, The experimental psychologist does the same thing
> in his lab, Both tend to use manipulation and anova designs, in which equal
> cell sizes are sought across the levels of the factors, By doing so they
> experimentalist progresses systematically by carefully controling his
> research,
>
> I am simply saying that those who wish to pursue causal models without
> manipulation should learn something about the control afforded by isolation
> of variables, Do you think it is wooly minded for a user of an anova design
> to seek out equal cell sizes across the levels of the putative factor?
There is nothing wrong with that, but that hardly qualifies as the
uniform
distribution of the putative independent variables x1 and x2 that you
were
talking about earlier. And the paper of yours that I downloaded
(bug-free)
from the web site you mentioned does not talk about restricting your
attention
to just ANOVA, either. Here is how I interpret what you've said to date:
1. If you take two uniformly distributed random variables x1 and x2 and
form
the sum y = x1 + x2, then y has a distribution that is not uniform.
2. If you have two variables x and y and want to determine whether x
depends
on y or y depends on x, first select the x variable uniformly, then
run
two regressions, one with each of the two variables as the IV. The y
variable is not going to be uniform, of course, but according to you
this proves causality.
What have I got wrong?
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