I have a regression with 2 predictors: gender (=1 if female, 0 otherwise) and risk attitude (measured on a scale from 0 to 10). When I only include main effects, i.e. run the model
DV = b0 + b1Gender + b2RiskAttitude,
risk attitude is significant and gender insignificant. However, when I include an interaction term, i.e. run the model
DV = b0 + b1Gender + b2RiskAttitude + b3Gender*RiskAttitude,
all predictors become insignificant. What might explain why the main effect of risk attitude is no longer insignificant? Gender and risk attitude is negatively correlated, but there is no multicollinearity.