It's not so simple. You have to do matrix-inversion for
that.
If your statistical program is able to spit out "factor scores",
you just take these as your coordinates. For each of your objects
you get values in each factor, which you can use as coordinates
in the factorspace.
Regards -
Gottfried.
Huxley schrieb:
>
> Thank you for explanation. Bu my question was unclear therefore let me ask
> again. I invented an exapmle.
>
> I have 10 questions in a questionnaire. These questions are my 10 variables.
> A consumers fill this questionnaire for each 15 products e.g cars. Because
> 10 variables (X1, X2, ...,X10) are correlated with each other I use factor
> analysis and (for convinence I ordered it) I get
> Factor1: X1,X2,X3,X4,X5,X6,X7
> Factor2: X8,X9,X10
>
> I can e.g put X1 into 2-D space, because I know that
> X1= -1*F1+ (-1*F2). It means that X1 has co-ordinates X1=(-1,-1).
> It's simple. But I'm not interested in positioning X1. For me it's important
> where there are products (cars) in 2-D space. Therefore my question is how
> to do it. I heard (but I do not know) that using e.g variable X1,...X10
> mean and factor loadings I can do it i.e. for car1: I multiple factor
> loadings and variables mean (suitable) and I get this position
> Could you help me verify this?
> I would be very appreciate
>
> Regards
> Huxley
>
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