I have a study with two potential mediators: M1 and M2. I obtain a main effect of my independent variable X on the dependent variable Y. Similarly, I obtain an effect of X on M1, but I do not have an effect of X on M2. Now, I have a mediation effect X - M1 - Y. However, I hypothesised that M1 could impact M2 and that this could, in turn, impact Y i.e. a model where X - M1 - M2 - Y. I did a SEM analysis where I compared the simple mediation model (X - M1 - Y), which was a good fit, with the more complicated model (X - M1 - M2 - Y), which was also a good fit. The models were not statistically different from each other and both were a good fit to the data. I am having trouble interpreting this. Can I conclude that the more complicated model is a good fit and a confirmation of my hypothesis even though a) both models are a good fit and b) I did not obtain an effect of X on M2? Any suggestions would be appreciated.
I have used the lavaan package in R for all the path analyses.