--E3C0CED54969B0D3D4798656
Content-Type: text/plain; charset=us-ascii
Content-Transfer-Encoding: 7bit
David A. Heiser wrote:
> First Gautam Sethi used the term "convolution" for the product to
> two (uniform) densities. Aniko responded with a definition of
> convolution as the s
Hello,
Does anyone know of any software that conducts reliability analyses using
the generalizability approach of Cronbach et al?
Bill Chambers
===
This list is open to everyone. Occasionally, less thoughtful
people se
Ellen,
It amazes me to read the self-righteous judgements of people on this
thread.. a number of whom have made incompetent criticisms of corresponding
correlations with the same arrogance and stupidity that they attribute to
the data mining boys, When the purpose becomes making money and not
pu
Horst,
Get your shit together, What do you think about the polarization effect in
the model y=x1+x2.
Bill Chambers
Horst Kraemer wrote in message <[EMAIL PROTECTED]>...
>On Sun, 27 Feb 2000 19:17:13 -0600, "William Chambers"
><[EMAIL PROTECTED]> wrote:
>
>
&
Once again Rubin is being a pompous jerk, Let's look at the details,
>As normally used, hypothesis testing is just plain WRONG.
>That lower-dimensional null hypothesis is rarely tenable,
>and even if it is, such as the speed of light in vacuum
>being constant, it is never directly tested. Also,
Rubin said:
>
>As someone who has worked on the foundations, I suggest you
>look at the real problem. In principle, you start out by
>considering every possible theoretical model, and you use
>the data to combine with your outlook to produce results.
No. I do not look at every possible model.
Bill said earlier:
>> Yes, we do this so that we will have examples of all combinations of x1
and
>> x2,as we would do when using a factorial anova design. But such uniform
>> sampling does not make the variables into causes, Adding x1 to x2 causes
y,
>
Gus responded:
>Here you are using a ver
Guss said:
>
>No. You said yourself that you are _selecting_ the x1 and x2 to be
>uniform.
Yes, we do this so that we will have examples of all combinations of x1 and
x2,as we would do when using a factorial anova design. But such uniform
sampling does not make the variables into causes, Addin
Gus said:
>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
> o
Gottfried said:
>
>Here you focus the crux of the normal-distributed variables.
>If there is a reality with n1 and n2 as normal distributed causes and
>y as effect like y<-n1+n2, you have measured standardized z1 and z2 (not
knowing
>which represents y and which represents n1 of the model)
>then y
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 l
Jerry,
You are correct that the same data set can support a number of SEM models.
This is not the case with corresponding correlations/regressions, however,
CR discloses THE causal model for a given set of data, To debate whether or
not this disclosure is provable or not when we model phenomena
12 matches
Mail list logo
