> I understand that the default in -qVarCenters is centering across everything, so I
> should centre myself within each level, right?

Yes, that's right: you should center the variable within each level yourself before feeding into the data table.

> what is the gain in adding RT as a random effect? You wrote that it accounts for "RT
> variability across subjects *within* each level" - I think I don't understand the "within
> each level" thing... How does the fact that RT is subdivided by Cond enters into the
> analysis? Doesn't (RT|Subject) mean that the *average* RT is adjusted per subject?

There are two reasons for incorporating a variable (e.g., RT in your case) in a model: 1) you're interested in the effect of the variable, and 2) you would like to account for the variability in the data due to this variable.

For the second reason above, another way to say it is that you want to control the variable at a specific value, which is what centering is about. How you center the variable may have a huge impact on the results as well as the interpretation of the results. For example, if you center the variable at the overall mean in your case, you may face the following problem, which is basically associated with the fact that the two conditions are correlated with the RT values: does it make sense to compare the two conditions if RT is fixed at the overall mean while you already know that the two conditions have different average RT?

Gang