Right on. I keep working on this... Thanks for the feedback to everyone. C.
Thom Baguley wrote: > Carlos J. Vilalta y Perdomo wrote: > > > > Would you please give me some advice in the following problem? > > Problem: > > Pearson correlation of x1 with y is n.s. > > Yet, when y = x1 + x2 + x3... + x6 + e, then x1 becomes a significant > > predictor of y > > Questions: > > 1. Would this be effect of an intervining/mediating variable? > > 2. What would you do? Include or exclude x1 from the analysis? > > I appreciate your comments and suggestions. > > Carlos > > x1 is more highly correlated with the residuals of the model with the other > variables included than with y on its own. I believe this a type of supression > effect. Whether to include x1 depends on many other factors. For example, what > is x1, why did you correlate it with and so forth. In a large data set you are > bound to find such effects, so simply trawling through different models is not > a good strategy. OTOH if there is theory to suggest x1 might influence y it > might be sensible to have it in the model. > > Thom > . > . > ================================================================= > Instructions for joining and leaving this list, remarks about the > problem of INAPPROPRIATE MESSAGES, and archives are available at: > . http://jse.stat.ncsu.edu/ . > ================================================================= . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
