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?
EDIT === Watching Econometrics Lecture, http://www.youtube.com/watch?v=Kb4LvSguwjg&index=12&list=PLD15D38DC7AA3B737 For Econometrics, people use instrumental variables... which is correlated with true independent variables and uncorrelated with error..