I have a situation where two variables when entered into a regression model independently, both predict a third variable, but when I entered both those variables into the model together, neither one significantly predicts the third variable independently, but overall the model is significant.
In other words.
1st regression - A significantly predicts C
2nd regression - B significantly predcits C
3rd regression (both entered together):
- A does not significant predict C
- B does not significantly predict C
- Model overall is significant
What does this mean? Does it just mean they share too much variance (A also significantly predicts B)? How would I interpret this?