I've added a quadratic effect of a latent predictor to a survival model and am getting a strange result. When the linear effect of the latent variable is entered without the quadratic effect, it is significant with a parameter estimate of .871 and a SE of .184. When both the linear effect and the quadratic effect are in the model, neither is significant and they both have parameter estimates of .000. This suggests to me that the linear and quadratic effects are highly collinear but as latent variables are centered in Mplus, I don't understand how that can be possible. Any thoughts you might have would be most appreciated. Thanks!
Thanks Bengt - I just checked the Tech4 output and the f and f-square variables are indeed uncorrelated. But why then should including the f-square as a predictor wipe out the effect of the f variable?