The model includes the following variables (N=367):
(i) X is an independent variable
(ii) Y is dependent variable
The result shows following significant relationships:
(i) c= X--->Y; Beta value=0.47 (pM; Beta value=0.80 (pY ; Beta value=0.24(pY ; Beta value=0.34 (pY (without mediation) ; Beta value=0.49(pM ; Beta value=0.79 (pY; Beta value=0.16 (p=0.21) insignificant path ~absence of mediation
While for female; complete mediation occurs
c=X--->Y (Without mediator) ; Beta value=0.40 (pM; Beta value=0.74(pY ; Beta value=0.56(pY ; Beta value=-0.047 (p=0.796 i.e. insignificant and beta value is negative)
Though, the stated relationship is a case of complete mediation (c* is insignificant and beta value approaches zero) but it is observed that the effect size is greater than 1 i.e. a.b (indirect effect)/c (Total effect)= 0.74*0.56/0.40=1.03 which is considered as inconsistent mediation.
Kindly advice me how will I report such findings and are there any literature support that incorporates inconsistent but full mediation of gender?
For one, your obtained ratio of the indirect to the total effect is very nearly one and could be attributed to some sort of rounding error. That being said, I am not sure how important exploring this particular value is to be honest. See page 15 of the Hayes (2009) ref I have linked to. Also, there is a general trend away from talking about mediation as being "full" vs. "partial". It should be sufficient to demonstrate that your indirect effect is significantly different from zero, preferably using a bootstrapping approach (here is an easy web utility that would work with your existing analyses: http://www.quantpsy.org/medmc/medmc.htm).
http://moodle.f.bg.ac.rs/file.php/48/Hayes2009.pdf
- Badges
- Science topic
- Similar topics
- Mathematics
- Statistics
- Statistical Modeling