On 1 Feb 2004 13:19:12 -0800, [EMAIL PROTECTED] (Niko Tiliopoulos) wrote: > Dear all, > > I hope someone can help me out with the following issue, because it is > giving me a headache. > > For practical reasons I will simplify the problem dramatically.
(the answer, in detail, might hide in the simplification.) > > I have a number of manifest variables, some acting as predictors and > some as outcomes. One of those predictors has a behaviour I do not > understand: > > 1. In bivariate correlations it has a positive association with all > outcomes > > 2. In regression models (all predictors) against each of the outcomes, > it still shows positive (standardised) betas > > BUT > > when in a structural equation model (with all predictors making a > single exogenous, and all outcomes a single endogenous variable) its > regression weight sign is minus! > > In addition: > > This predictor does not have high correlations with the rest of the > predictors (approx. max r = .30) > > Frankly I do not understand this behaviour. > > Any ideas will be greatly appreciated The first thing I would do: Be 100% sure about the behavior. Can you confirm that the N is exactly the same in all analyses? Is there ever any problem or question about Missing codes? The second thing: Make sure about the collinearity. Okay, the maximum r is 0.30 with predictors. What about the multiple r? (No dummy variables involved? nothing that makes part-scores, when the total is also around?) Third item: What is the total 'fit'? What is your r-squared, and what *should* it be? What warnings do you have for overfit, or for bad fit? - I don't do structural models, but my understanding is that 'fit' is problematic. I guess that I would expect your problem to arise somewhat-legitimately from a overfitting, maybe as a symptom of odd scaling. I hope this will help -- your point (2) does tell me that you have considered - already ruled out - the most obvious aspects of what I have in mind. -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html "Taxes are the price we pay for civilization." . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
