Hi there,
I am running a Multiple Linear Regression analysis. I have 2 predictor variables (self-worth and self-acceptance) and 1 criterion variable (self-esteem).
As hypothesized, self-worth and self-acceptance reliably predicted the scores on self-esteem (eg. higher scores on the predictors would equate to higher scores on the criterion).
However, by simply looking at the means for each construct, it is evident that self-worth (predictor) has a higher mean than self-esteem (criterion).
Could this be signifying a different/more complex relationship between this predictor and the criterion? Or perhaps it makes more sense to suggest that self-worth is the criterion and self-esteem is the predictor?
I do hope this makes sense.
Thank you,
Vanessa.
I am running a Multiple Linear Regression analysis. I have 2 predictor variables (self-worth and self-acceptance) and 1 criterion variable (self-esteem).
As hypothesized, self-worth and self-acceptance reliably predicted the scores on self-esteem (eg. higher scores on the predictors would equate to higher scores on the criterion).
However, by simply looking at the means for each construct, it is evident that self-worth (predictor) has a higher mean than self-esteem (criterion).
Could this be signifying a different/more complex relationship between this predictor and the criterion? Or perhaps it makes more sense to suggest that self-worth is the criterion and self-esteem is the predictor?
I do hope this makes sense.
Thank you,
Vanessa.