I conducted a mediation analysis in PROCESS with a binary DV, a binary IV, and a continuous mediator. My findings are as follows: 1) The first model (X -> M) was significant. 2) In the second model, the X (IV) was not a significant predictor of the Y (DV) but the M (mediator) was. 3) In the third model, the direct effect of X on Y was not significant. The indirect effect of X on Y was significant. What do you make of it? I think this means that the mediator completely explains the relationship between the IV and the DV. So I have a complete mediation, no?
Thank you for the video. According to Baron and Kenny, if there is an insignificant relationship between the independent variable and the dependent variable, the full mediation effect occurs, and if there is a decrease in the relationship between the independent variable and the dependent variable, the partial mediation effect occurs. it's called. My analysis revealed both a decreased relationship and a nonsignificant relationship. How should I interpret this situation?
When relationships become insignificant, then you can interpret it as full mediation, and it is quite obvious that the beta value will be decreased in such cases.
In my case path X to M (p1) and path M to Y(p2) are negative and p3 (direct effect)is postive. Multiple of p1 and p2 is mathematical positve and in essence also these two paths are supposed to be negative as per theory and literature. With direct effect positive and indirect effect also positive, when actually the paths to and from mediators are actually negative, are significant at .05. How shall I interpret this result
It does not effect much in term of interpretations, you can simply conclude since there is partial mediation, it suggests that the IV has some direct impact and some indirect effect on IV.
This is the best video I have seen. Precise and meaningful .. no extra wordings...
Jazak Allah my dear... very very helpful...
I conducted a mediation analysis in PROCESS with a binary DV, a binary IV, and a continuous mediator. My findings are as follows: 1) The first model (X -> M) was significant. 2) In the second model, the X (IV) was not a significant predictor of the Y (DV) but the M (mediator) was. 3) In the third model, the direct effect of X on Y was not significant. The indirect effect of X on Y was significant. What do you make of it? I think this means that the mediator completely explains the relationship between the IV and the DV. So I have a complete mediation, no?
Yes, in this case, there is a full mediation.
Very good
Precise and easy....
Thank you for the video. According to Baron and Kenny, if there is an insignificant relationship between the independent variable and the dependent variable, the full mediation effect occurs, and if there is a decrease in the relationship between the independent variable and the dependent variable, the partial mediation effect occurs. it's called. My analysis revealed both a decreased relationship and a nonsignificant relationship. How should I interpret this situation?
When relationships become insignificant, then you can interpret it as full mediation, and it is quite obvious that the beta value will be decreased in such cases.
thankyou for the meaningful video
super!
In my case path X to M (p1) and path M to Y(p2) are negative and p3 (direct effect)is postive. Multiple of p1 and p2 is mathematical positve and in essence also these two paths are supposed to be negative as per theory and literature. With direct effect positive and indirect effect also positive, when actually the paths to and from mediators are actually negative, are significant at .05. How shall I interpret this result
If there is a partial mediation then how we will interpret it? What would be the result?
It does not effect much in term of interpretations, you can simply conclude since there is partial mediation, it suggests that the IV has some direct impact and some indirect effect on IV.
buddy where is video of Smart PLS
InshAllah soon I will start series on smart PLS