Posted by
Rose, Fred on
Nov 15, 2006; 3:18pm
URL: http://spssx-discussion.165.s1.nabble.com/PCA-factor-score-uses-tp1072110p1072112.html
This was very helpful. To answer your question: Participants viewed images
of couples that were/were not interracial and answered several questions.
The first factor seemed related to a situational interpretation (e.g.,
judgments about the couple's happiness, etc.) while the second was about
more innate racist attitudes (willingness to have the couple over for
dinner, etc).
The questions were mixed in wording but we reversed scored several so that
higher scores always meant more positive attitudes.
I have two questions:
1. How can I find out what "end" of the scale my groups are on? Just look
at the group means of the scales? What is interesting is that the groups
who viewed same-race couples (white-white or black-black) had the negative
scores on factor 1, while the mixed race groups had positive scores. I'm
curious to know if this means the same race groups reported LESS positive
attitudes towards the couples than the mixed race groups.
2. When you say " it is traditional to calculate scale scores by
summing items, reflecting those items that have negative weights" what did
you mean by reflecting those items that have negative weights? Reverse
score items that load negatively on that factor?
Thanks for your explanation. Most of the readings I have don't say anything
more about factor scores other than they can be used in plots.
Fred
On 11/15/06 6:07 AM, "Art Kendall" <
[hidden email]> wrote:
> You can use the factor scores in any design role.
> Think of the factor scores as z-scores. Mean of zero, SD of 1.
>
> What interpretation did you give to the two factors? Are the factors
> bipolar or unipolar?
>
> If you have 2 groups of respondents, and the mean factor scores you
> mention are for these groups, then group 1 is at one end of the scale
> and group 2 is at the other. The direction of factors is completely
> arbitrary.
>
> When developing scales, it is traditional to calculate scale scores by
> summing items, reflecting those items that have negative weights.
> Since reliability, correlations etc. are not changed by dividing by a
> constant, you might want to work with a mean of the items.
>
> It is also possible that you would want to reflect one or both scales so
> that the high end is meaningful, e.g., high scores mean more racism.
> The choice of direction is usually made to make correlations, etc., with
> other variables have less complex verbal explanations.
>
> Art Kendall
> Social Research Consultants
>
>
> Fredric E. Rose wrote:
>
>> I'm not entirely familiar with PCA and could use some help.
>>
>> I've used PCA w/varimax rotation to reduce 10 variables (answers to a racism
>> attitudes questionnaire) down to 2 factors. I want to know if the
>> calculated factor scores for each participant can then be used as a
>> dependent variable in subsequent analyses, or whether I should simply
>> combine the variables loading on the respective factors and use those? My
>> problem is in interpreting the factor scores: Group 1 has a mean of -2.72
>> and Group 2 has a mean of 2.68. These are significantly different, but I'm
>> not sure what the means represent (the raw data are scores ranging from 1 to
>> 10, so there are no negatives).
>>
>> Thanks for any insight.
>>
>> Fred Rose
>>
>>
>>
>>
>
--
Fredric E. Rose, Ph.D.
Assistant Professor of Psychology
Palomar College
(760) 744-1150 x2344
[hidden email]