I saw a famous review paper about intelligence, and the authors introduced a way to adjust the regression coefficient for predictor error.
As many of you might know, if the predictor has a measurement error or if it has reliability less than 1, the regression coefficient estimate(OLS) is biased towards 0.(less than the true regression coefficient). But I haven't seen the same method applied among the papers published recently.
So, I wonder if it is still valid method to adjust the biased regression coefficient from measurement error(which is using estimates of variance of error term).
If not, why is it not?