Question

Suppose the abdominal and subscapular skinfold sites had a high degree of collinearity. What are the implications of this when attempting to predict percentage body fat?

Increased standard errors of the b coefficient.

It limits the R value as the predictor variables account for the same variance in the outcome variable (i.e. percentage body fat).

It becomes difficult to decide which variable to include.

It will not affect the prediction.

Answer 1

Increased standard errors of the b coefficient.

Multicollinearity is a problem because it can increase the variance of the coefficient estimates and make the estimates very sensitive to minor changes in the model. The result is that the coefficient estimates are unstable and difficult to interpret. Multicollinearity saps the statistical power of the analysis, can cause the coefficients to switch signs, and makes it more difficult to specify the correct model.