I appreciated the help on my last post regarding normalizing data. I went ahead and did that, and also ran a factor analysis to reduce some variables in my data. Now I am trying to find a good model, but cannot seem to figure it out because I still have too many variables.
A bit of background on what I am trying to do. I took a survey and distributed it to our employees. Each question in the survey measures a behavior or perception. Now I want to see which behaviors and perceptions are correlated with our high performers. So my independent variable is "PerformanceRating" and my dependent variables are "Cognition", "Initiative", "EmotionalStability", and so on.. (even after my factor analysis and combining 4 variables into 1 factor, I still 19 dependent variables...
I ran a regression model with all of the variables to see if could see any that were significant. I found a few, removed all the other variables, but still my rsquared values were not significant.
Do you perhaps have a suggestion on how optimize my model?
Thanks in advance!