Interpretation of univariate regression analyses and multiple regression analysis

#1
Univariate regression analyses show that 11 factors are significantly related to the outcome measure. However, the multiple regressions analysis shows that 60% of the variance in the outcome measure could be explained by 5 factors. How should I interpret that some significant factors from the univariate regression analyses do not explain variance in the multiple regression analyses? and how can I explain these results in my discussion?
 
#2
First, I would check the assumptions of regression. But, just because it is significant in the univariate case doesn't mean it will be significant in the multivariate case. Some variables may be highly correlated with one another. You should check this. Is there a reason you chose to include all 11 factors in the first place?
 

Karabiner

TS Contributor
#3
If predictors overlap, the same amount of variance in the dependent variables
could be explained by different variables.Your results state
that variables 6 to 11 do not (significantly) explain variance beyond what
variables1 to 5 were already able to explain.

With kind regards

Karabiner