Dear all, I have the following problem, and I would appreciate very much if someone on this list could give me some insight or reference to orient my search. For example, I have this simple model for lmer(): Y ~ A + B + (1|D) But B is very difficult and expensive to measure, so I want to replace it with another predictors that I can compute automatically (B1, B2, ...). Then, I ran these models, Y ~ A + B1 + (1|D) Y ~ A + B2 + (1|D) ... But when I compared them with the original model, all these models were worse. Thus, I tried these models, Y ~ A + B + B1 + (1|D) Y ~ A + B + B2 + (1|D) ... And in some cases the absolute value of the estimate of B (and the t-value) decreased more than others... But I'm not convinced this could be really conclusive that some replacements are better than others. My intuition is that this should be a common problem in many fields, but I couldn't find the answer in the bibliography (probably I didn't try the good keywords). Thus, I will be very grateful if someone could guide me a little bit. Many thanks in advance, Best, Juan
Juan E Kamienkowski @ Departamento de Fisica, FCEN-UBA http://df.uba.ar/ @ Laboratorio de Neurociencia Integrativa http://neuro.org.ar/ @ Laboratorio de Inteligencia Artificial Aplicada http://liaa.dc.uba.ar/ [[alternative HTML version deleted]]