I am estimating latent curve models (btw, this is my first time using LCM) for multiple indices (n = 6) taken from the same sample of research subjects. For some of these indices, the fit measures TFI and IFI are indicating that the model is overfitted (TFI > 1.2 & IFI > 1.2), but for other indices they are telling me the model fit is quite good (TFI and IFI around 1.0). Also, none of the conditional models (predictors n = 3) indicate overfitting.
Can someone explain why, for some indices, the model is overfitted, yet for others it is not, even though the sample size nor the number of parameters does not change?