Posted by
Willbaileyz @ E on
Jun 25, 2012; 2:58pm
URL: http://spssx-discussion.165.s1.nabble.com/Interpretation-of-principal-component-regression-results-tp5713752p5713780.html
Getting in on the end of this thread so perhaps my question isn't
appropriate but .... You said:
"I changed my dependent for one that didn't correlate so high with the
independent variables and results are good."
This sounds to me that you changed your hypothesis so as to get the results
you are looking for or at least to get 'better' results? Not a viable
research approach so do explain more as to the reasoning and soundness
W
On 6/25/2012 10:45:33 AM, RuudM123 (
[hidden email]) wrote:
> Dear All,
>
> Thank you for all your explanatory comments. I changed my dependent for
> one
> that
> didn't correlate so high with the independent variables and results are
> good.
>
> For illustration purposes I would like to make sure that I don't
> do anything
> wrong, therefore I wanted to ask the following question based on PCR:
>
> Results:
> Factor 1 - beta coefficient of .452 which is significant at p < 0,001
> IV1 - factor loading of .985
> IV3 - factor loading of -.952
>
> Factor 2 - beta coefficient of -.456 which is significant at p < 0,001
> IV5 (interaction of IV1*IV3) - factor loading of .854
>
> Conclusions:
> - IV1 (in factor 1) has a significant beta coefficient of .452 (for the
> factor) and a factor loading of .985 (for the variable) = which means
> that
> IV1 has a positive linear relation on the dependent.
>
> - IV3 (in factor 1) has a significant beta coefficient of .452 (for the
> factor) and a factor loading of -.952 (for the variable) = which means
> that
> IV2 has a negative linear relation on the dependent.
>
> - And IV5, which is the interaction term of IV1*IV3, (in factor 2) has a
> significant
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