It is a long time since I used any kind of standard statistical analysis,
including Path Analysis, so I may be a bit rusty on this, but I do not think
that the inference of causality is necessarily based on a priori
assumptions. In one case (Silvert, William. 1982. Top-down modeling of
multispecies fisheries. In "Multispecies Approaches to Fisheries Management
Advice," M. C. Mercer, ed. Can. Spec. Publ. Fish. Aquat. Sci. 59:24-27.)
where I was investigating the role of environmental factors in fisheries I
tested a model based on the hypothesis that both effort and temperature
affected fish catches. But something seemed wrong, and when I tackled the
problem with Path Analysis I came up with the surprising result that catch
determined effort, and not the other way around. This seemed like nonsense,
but I happened to meet the authors of the data report I was using, and they
were greatly upset that I was analysing their data. Finally they confessed
that they had been told to collect effort data, but since they were unable
to do this they made up the numbers by assuming that whatever fish a boat
caught most of must have been what they were fishing for. Thus Path Analysis
led me kicking and screaming to the right result - catch really did
determine effort!
Bill Silvert
----- Original Message -----
From: "Ned Dochtermann" <[email protected]>
To: "William Silvert" <[email protected]>
Cc: <[email protected]>
Sent: sábado, 5 de Dezembro de 2009 20:04
Subject: Re: [ECOLOG-L] an example of a false correlation
It is interesting that so many researchers bring up the issue of
"correlation
doesn't demonstrate causality" and yet are more than happy to argue
causation
based on regression, which usually relies on the same sort of data as used
for
standard correlational analyses.
Regression analyses are not typically used for experimental data and thus
are
asserting causation based on correlation. The practical difference between
regression and correlation is the a priori hypothesizing of causation (how
many
regressions are really conducted post hoc after examining scatter plots is
a
whole other can of worms). The exact same statistical results in terms of
"F's", "P's" and R^2 will be obtained if you switch which variables are
dependent and independent in a linear analysis (of course intercepts and
coefficients would differ).
I mention this in relation to the below post because when discussing path
analysis with a colleague awhile back the comment was made that
"correlation=/=causation" to which my reply was "that's what you do with
regression". Although path analysis does use correlation matrices (or
covariance matrices) in its analysis I consider it to be more akin to
multiple
regression as you're testing a priori causal hypotheses.
Next time someone asserts correlation doesn't demonstrate causation ask
them
when the last time was that they used regression. The ensuing argument can
be
quite amusing.
Ned Dochtermann
--
Ned Dochtermann
Department of Biology
University of Nevada, Reno
775-784-6781
[email protected]
www.unr.nevada.edu/~dochterm/
--
Quoting William Silvert <[email protected]>:
Since I think that Mao Tse Tung and Pol Pot were heavy smokers, to say
nothing of Fidel Castro, I guess that where Malcolm is going is to show
that
by selecting your data you can obtain any correlation you want.
The point that correlation alone does not prove causality is one that
statisticians are always making, but mention should be made of Path
Analysis, a technique based on multiple correlation, that is effective in
establishing causal pathways. It is used extensively in the social
sciences,
but only rarely in ecology. I think that it deserves more attention, I
have
certainly found it of value.
However a benthic ecologist I know who used Path Analysis died young, so
although that is only one data point, perhaps Path Analysis should be
avoided!
Bill Silvert
----- Original Message -----
From: "malcolm McCallum" <[email protected]>
To: <[email protected]>
Sent: sexta-feira, 4 de Dezembro de 2009 18:13
Subject: [ECOLOG-L] an example of a false correlation
> Anyone who teaches stats might be interested in this false correlation
> I
> just stumbled on.
>
> 1) Stalin did not smoke
> 2) Hitler did not smoke
> 3) Mussolini (sp?) did not smoke.
> 4) Roosevelt smoked
> 5) Churchill smoked
>
> I guess you can see where I'm going with that!
> :)
>
> --
> Malcolm L. McCallum
