Thanks for all your replies.
And, again, I apologize my vague description about my question. I will
try to rephrase it in another way below.
Suppose I wants to know what kind of combination of products will
attract consumers most. There are five products in my research. Suppose
the preference ordering of these five products has been obtained from a
group of subject as:
product A product B product C product D product E
rank 1 rank 2 rank 3 rank 4 rank 5
Now, the combination of prodcuts will include any two of the five, or per
se twice. So there are 15 combinations. To understand which combination
attracts consumers most, we conduct an paired-comparison experiment
between the 15 combinations. (So, each subject has 105(=15C2)
comparisons.) We particularly desire to know the tie situations, such as
the preference between (product A, product E), (product B, product D),
and (product C, product C).
The subject's preferences are further fed into Multiple Dimensional
Scaling to analyze. The graph shows that the first two dimensions can
explain the data well. Suppose these two dimensions are labeled as: price
and fancy of a combined products. And now we have only the price
information for each product. So, what I tring to do is using
mathematical equations to obtain the degree of fancy for each product. I
assume an aggregation model as the following:
Y(rank of the combined product)
= X11 (1st price) * X12 (1st fancy) + X21 (2nd price) * X22 (2nd fancy).
Where Y, X11, X21 are knowns, and X12 and X22 need to be calculated.
I am sorry for my ignorance about statistics. Please correct me if
anything wrong in the process I am doing.
Wen-Feng
------------
In article <[EMAIL PROTECTED]>,
[EMAIL PROTECTED] says...
> On 13 Apr 2000, Wen-Feng Hsiao wrote:
>
> > Suppose I have an aggregation model which is in the following form:
> > Y = X11 * X12 + X21 * X22.
>
> It may be that you're not getting answers because many of us are not at
> all sure of the question. (For example, the phrase "aggregation model"
> is not familiar to me.) Your "Subject:" question (linear or
> interactive?) suggests that you're thinking in terms of multiple linear
> regression as a means of analyzing your model; but then your example,
> of aggregating the knowledge of two persons, conflicts with my view of
> how "persons" ought to be represented (as cases, not as variables) in a
> multiple regression problem.
<snip>
> ------------------------------------------------------------------------
> Donald F. Burrill [EMAIL PROTECTED]
> 348 Hyde Hall, Plymouth State College, [EMAIL PROTECTED]
> MSC #29, Plymouth, NH 03264 603-535-2597
> 184 Nashua Road, Bedford, NH 03110 603-471-7128
===========================================================================
This list is open to everyone. Occasionally, less thoughtful
people send inappropriate messages. Please DO NOT COMPLAIN TO
THE POSTMASTER about these messages because the postmaster has no
way of controlling them, and excessive complaints will result in
termination of the list.
For information about this list, including information about the
problem of inappropriate messages and information about how to
unsubscribe, please see the web page at
http://jse.stat.ncsu.edu/
===========================================================================
