collinearity

collinearity can affect the results of regression analysis.

it is important to check for collinearity among the predictors.

high collinearity can lead to unreliable coefficient estimates.

we used variance inflation factors to assess collinearity.

collinearity diagnostics are essential in multiple regression.

the presence of collinearity can complicate model interpretation.

to address collinearity, we may need to remove some variables.

collinearity can obscure the true relationship between variables.

understanding collinearity is crucial for accurate data analysis.

we found significant collinearity in our data set.