First, when you name your factors, you should determine what a high
score means. If your factor is called kinship, then an item which
means greater kinship should have a positive loading.
If that's not the case, you need to either (1) Rename your scale -
don't call it extraversion, call it introversion, (2) Reverse the
items before analyzing, or (3) Reverse the scale when you create it
(multiply it by -1). You should do this before you do any further
analysis, and then interpretation later on is clear.
Jeremy
On 5 June 2012 04:09, Sandi Dheensa <[log in to unmask]> wrote:
> Hi all
>
> I sent a very confused email out the other day about factor scores and
> regression - thanks to those who replied! I have another query now...
>
>
> I did Prinicipal axis factoring (direct oblimin)
>
> I got a 3 factor solution. The three factors were (1) feelings (2) kinship
> and (3) interactions. (I'm looking at father-child relationships)
> Regarding factor loadings, (1) feelings had all positive factor loadings,
> (2) kinship had all negative factor loadings and (3) interactions had all
> negative loadings.
>
> I did a multiple regression analysis using the factor scores, saved as
> regression scores, as outcome variables. I'm not bringing them together to
> form a total scale, so I don't think I need to do a MANOVA instead, or
> adjust the p-value.
>
> For (1) feelings, all of my predictor variables have positive beta weights
>
> For (2) kinship, one of my predictors (participation in healthcare) has a
> negative beta weight
>
> For (3) interactions, again, one of my predictors (participation in
> healthcare) has a negative beta weight
>
>
> I'm confused about whether the predictors with negative beta weights
> actually imply that less participation in healthcare means a lower score on
> kinship and on interactions. Or whether, because those two outcome variables
> have all negative factor loadings, does the negative beta weight actually
> mean a postive beta weight? (i.e. do the negatives cancel each other out?).
>
> If the latter is the case, do the predictors with a positive beta weight for
> outcome variables (2) and (3) actually have a negative beta weights?
>
> THANK YOU!
>
> :) :)
|