As you will most likely recall, one of the assumptions of regression is that the predictor variables are measured without error. Let's look at a regression using the hsb2 dataset. The predictor read is a standardized test score.
Every test has measurement error.
I don't know the exact reliability of read , but I would say that using .9 for reliability would not be far off. 11.21504 22.57805 Note that the F-ratio and the R 2 increased along with the regression coefficient for read . Additionally, there was an increase in the standard error for read . Now, let's try a model with read math and socst as predictors. First, we will run a standard multiple regression.