I am currently analysing data for my Bachelor thesis. I want to find out if people's decision-making ability (X) has a direct and/or indirect effect through their tendency to overeat (M) on their BMI (Y).
I have conducted a simple mediation analysis using the macro PROCESS in SPSS. As far as I have (hopefully rightfully) concluded the effects are not significant.
However, since the age range of the tested participants is very broad, I decided to include the age as a covariate.
I am not sure how to exactly interpret the results now. I have included the SPSS output in a Word document below to make things more visual.
In the part where it says outcome variable “BMI”, “alter” (=Age) has a coefficient of 0.086 with a p value of .0103.
Does that mean that the age has a significant effect on the BMI?
Also in the total effect model found below it says that money_sum (=decision-making ability) has a coefficient of -.0005 (p= .3271)
and age has a coefficient of .0860 (p= .0081).
Again does that mean that age has a significant influence on the BMI?
But how can I interpret then the total (effect = -.0005), direct (-.0005) and indirect models?
Does age not have an effect after all? I am a bit confused now and I really appreciate your answers to help me get rid of this confusion.
Thank you very much!
Kind regards,
Helena
Best Answer
The path a and path b of your model are not significant. Your indirect effect (path a*b) also included zero, indicating no mediated effect. If removing age and adding age to your model gives you different path coefficients, then that should be of an interest. Otherwise significant age in your model doesn't change your conclusion from the mediation model.
Good luck.