Brian Sandle <[EMAIL PROTECTED]> wrote in message 
news:<[EMAIL PROTECTED]>...
> I have also put this on sci.stat.edu for any comment. I am not sure if 
> that is the right group.
> 
> Szasz <[EMAIL PROTECTED]> wrote:
> > Brian Sandle <[EMAIL PROTECTED]> wrote in message 
>news:<[EMAIL PROTECTED]>...
>  [...]
> >> Rank each subject 
> >> in order for social factors, extent of cocaine use in pregnancy, extent of 
> >> hyperactivity at age four or more of resulting child. Then go to some 
> >> source like Castellan (recent edition) which  gives a formula for partial 
> >> rank correlation with significance. It may not be a certain result, but if 
> >> it shows something, then think out other means of investigation.
>  
> >    At some point, Brian, you have to consider the possibility that the
> > people who did these studies used the best statistical methods
> > available,
> 
> Understanding of statistics is not very good, even at PhD level, 
> yourself, szasz:

   I understand what is necessary. We'll see how much you know,
yourself, Brian:

> 
>  and simply re-doing the study in different ways until they
> > get a result you agree with is not the way scientists do business.

   Which is what you suggested.

>  
> >    By the way, a partial rank correlation (AKA Pearson product-moment
> > correlation) is generally considered the basis of all multivariate
> > statistical techniques.
> 
> A partial rank correlation is _not_ also known as Pearson product-moment 
> correlation.

   The basic point is that the Pearson product-moment correlation is
what the partial rank correlation, regression techniques, factor
analysis, and a whole host of multivariate statistics is based upon.
The individual differences between techniques within the multivariate
family of techniques is irrelevant for the purposes of this
discussion, as I will explain:

> 
> First mistake: The Pearson product-moment correlation is not a rank 
> correlation.

   A rank correlation is a form of a regression technique, which is
related to the Pearson product-moment correlation. In fact, *all*
multivariate techniques are to a certain degree based on the Pearson R
squared.

> 
> The Pearson product-moment correlation would be used for linear data,

   Yes indeed. There are also techniques related to the Pearson R that
can be used to analyze data with non-linear models.

> which are given scores and are found to be symmetrically spread above and
> below an average value. So it very often should not be used.

   Your mistake, among many: and yet a partial rank correlation is
simply a more complicated version of the same technique, except that
simply you're proposing to add in more variables to the model (to be
"partialled out", hence the term "partial" correlation), and of course
variables that already are obviously irrelevant and contaminating
variables for the purposes of drawing valid conclusions from the crack
baby study.

   The fact that you're suggesting a technique that is vague to many
doesn't fool me: you're simply arguing that since you disagreed with
the conclusions drawn and the results the conclusions were drawn from,
you complain that the study essentially didn't allow for contaminating
variables to swing the results towards your predetermined conclusion,
i.e., that drugs are panapathogens.

> 
> Second mistake: The Pearson product-moment correlation is not a partial 
> correlation.

   Again, Sandle, the Partial Rank Correlation and the Pearson
product-moment correlation are based on the same math, and are the
same family of techniques.

   The basic point, and your towering and continuing mistake: simply
arguing for another, closely related statistical technique, and one
less suited for drawing valid conclusions from the data, is not good
science.

> Though a table can be written up showing how the various  
> variables correlate to one another, nothing is done mathematically to hold 
> variables constant, which is the essence of partial correlation.

   Again, the basic point, and your basic mistake: there is nothing to
suggest anything except that current research suggests that the "crack
baby" syndrome is a myth. You standing here and using piss-poor
amateur statistical  jargon and bluster to argue against the raw
empirical data is simply ludicrous.

> 
> 
> When data are not evenly spread a _rank_ correlation is thought to be more 
> robust.

   So, in essence, we began with a study that wanted to isolate the
effects of crack on prenatal development. They isolate (e.g.,
empirically and/or statistically control for) the effects of
socio-economic variables, so that these variables do not contaminate
whatever results they get regarding the "crack baby" effect after
extraneous variables (i.e., variables not related to the
pharmacological effects of the crack) are controlled for.

   So, they do that, and now you want to argue for adding in
additional extraneous variables that these trained scientists knew
enough to control for, as these extraneous variables would naturally
detract from their ability to draw conclusions from the data.

   Follow me so far? OK. So, we know they've done this (based on the
abstract, and some second-hand info from Dr. Proctor), and yet you
(Brian) want to argue that they massage the statistics by using
partial rank correlations (for reasons you still haven't made clear),
in the hopes that they get a result you might agree with.

   Do you understand why I jeer at you?

> Data are not given scores, but just put in order from biggest to 
> littlest. The Spearman rank correlation might then be used. That is not 
> however a partial correlation. Its table shows hows how various things are 
> correlated but does not hold mathematically hold any variable constant and 
> so look deeper.

   Again, you have given no rationale whatsoever for having
researchers use this kind of technique. Whether correlated variables
are ranked, held fixed or rotated, it doesn't matter. The researchers
knew which variables to control for in their statistical modelling,
and you do not.

> 
> The next step, a _partial_ rank correlation, was dealt with in Siegel's
> work on statistical method. But the technique was not advanced 
> sufficiently to calculate any _significance_ figure.

   This is all very nice and makes you sound very learned, but is
essentially irrelevant jargon (again) to the basic point I am
continuing to raise: the consensus of scientific data is that crack
baby syndrome in any form is a myth. Your inane bloviating about
multivariate techniques you visibly know little about how to apply
does not detract from a simple fact about science: if you don't like
the results, do your own studies.

> 
> Later, Castellan re-did Siegel's book and introduced a significance 
> calculation for partial rank correlation. He said it was not totally to 
> be trusted, I think.
 
   And yet you suggest this technique with no visible rationale!
Fascinating.

> 
> When I was interested in the work of an MA psychology student I was
> provided through the newsgroups with a VAX based program which would do
> the calculations, though I did not find out how to use it on the VAX at
> that stage.
> 
> What is available now? Linux or anything?

   SPSS is the standard in social sciences here in the United States.

> 
>  The idea that your suggestion is anything more
> > than a distraction from the main point (e.g., that 'crack baby'
> > syndrome is essentially a made-up syndrome) is laughable. March on.
> 
> I said `crack _baby_' is made up.

   That's funny, you seem to be arguing for a very similar version of
the crack baby syndrome, below. A cheap semantic-rhetorical ploy, I
suppose. Anyways, I suppose its only a matter of time until science
catches up with your advanced thinking on this matter and discovers
all the things you appear to be so certain of.

> I am waiting for Proctor's reply. The 
> problems do not show till _after_ babyhood, when the developing executive 
> funcitoning is trying to call up the releveant areas of the brain for that 
> time.

   I've never heard of "developing executive functioning call(ing)
up... areas of the brain." I'm sure you're trying to say something
that appears intelligent, here.

> --
> Brian Sandle.
> 
> please remove `shell' from between @ and caverock to reply by e-mail.
> 
> 
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