As I am testing a number of models, I notice that none of my demographic variables are ever signficant. For example, I am testing a model to predict the dependent variable 'perceived substitutability'. The independent variables are contentment about the content on traditional television and contentment about the content on online television. I run this model together with gender, age, professional status, income (yes/no), family composition and marital status. I used a hierarchical method where I used the demographic variables in the first block and the other variables in the second block. As I run the regression, all demographic variables were not significant (p>0,05). This is of course due to correlations between the independent variables.
If I use one demographic variable at a time to explain the dependent variable (so six times a simple regression where no other demographic variables are used), professional status and income become significant in the simple regression (not together because of course they correlate). Can I use this in my result-section: that in the simple regressions (1 dependent, 1 independent) they are significant while in the multiple they were not?
I am using SPSS