Which term refers to a situation in which two or more variables are very closely linearly related?

Which term refers to a situation in which two or more variables are very closely linearly related?

• A. Multiple regression
• B. Multivariate
• C. Multicollinearity
• D. Multilevel linear model (MLM)

Answer: (C)

When several predictor variables in a regression are highly correlated with each other, it becomes hard to separate each one’s individual effect. This situation is known as multicollinearity. It specifically describes multiple variables being very closely linearly related, which inflates standard errors, makes coefficient estimates unstable, and complicates significance testing. The other terms describe different ideas: multiple regression is the method of using more than one predictor, multivariate refers to analyses with multiple dependent variables, and a multilevel linear model handles nested or hierarchical data.

When several predictor variables in a regression are highly correlated with each other, it becomes hard to separate each one’s individual effect. This situation is known as multicollinearity. It specifically describes multiple variables being very closely linearly related, which inflates standard errors, makes coefficient estimates unstable, and complicates significance testing. The other terms describe different ideas: multiple regression is the method of using more than one predictor, multivariate refers to analyses with multiple dependent variables, and a multilevel linear model handles nested or hierarchical data.