Dear All, I don't know whether this question is appropriate for this list or not. My question is as follows: I am fitting a non-linear mixed model using the SSlogis function. When the parameters xmid and scal are both considered as random (let us say model M1), the p-value for my covariate of interest is greater than 0.05 (non-significant). However, when only the xmid is considered as random (Model M2), the p-value is less than 0.05 and my covariate becomes highly significant. The introduction of random effects of course increases the variability in the fixed effects but does not affect their Bias as I understand. My question is: Is it then legitimate to use the model with only xmid as random effects (model M2 since it gives me significant results)? knowing that the AIC for M1 is lower than that one for M2 meaning that M1 is slightly fitting better the data than M2 Many thanks in advance Bernard, --------------------------------- Une boite mail plus intelligente. [[alternative HTML version deleted]]