Figure 2.

The probabilities of showing a significant hypothesis test that two coefficients are equal when one is measured with error.

Note. ${\rho }_{\mathrm{XW}}$ is the correlation between the two predictors had they been measured without error. $R^2$ is the proportion of variance in the outcome explained by the two predictors if both had been measured without error.