Dear Community,
I have a model in which a continuous variable A positively influences B and as per the hypothesis, X (continuous variable) positively moderates their relationship. SmartPls bootstrapping results confirmed a significant positive relation between A and B, however, the interaction effect of X came out to be significant with a negative path coefficient (Beta = -0.054, p < 0.001). Now I am confused as I was expecting a positive path coefficient. Please tell me, how should I interpret this outcome, and is my moderation related hypothesis supported or not supported?
Also, the Simple Slope Plot shows almost parallel three lines (X at -1 SD, X at mean and X at +1 SD), with a positive slope.
Further, the bias-corrected confidence intervals also do not include zero in between [-0.0887, -0.0201]
Please tell me how to interpret the above and what to explain and report about hypothesis
Thank You
Moderation effect hypothesized positive but result shows negative an significant path coefficient
-
- PLS Junior User
- Posts: 1
- Joined: Tue May 26, 2020 11:13 am
- Real name and title: Er. Vaibhav Agarwal
- Location: India
-
- PLS Junior User
- Posts: 1
- Joined: Thu Nov 19, 2020 6:28 am
- Real name and title: Yoke Yew
Re: Moderation effect hypothesized positive but result shows negative an significant path coefficient
Dear Vaibhav,
I'm having similar problem, do you get any answer so far? Appreciate if you could advise, thank in advance.
Regards, Yoke Yew
I'm having similar problem, do you get any answer so far? Appreciate if you could advise, thank in advance.
Regards, Yoke Yew
-
- SmartPLS Developer
- Posts: 1284
- Joined: Tue Mar 28, 2006 11:09 am
- Real name and title: Dr. Jan-Michael Becker
Re: Moderation effect hypothesized positive but result shows negative an significant path coefficient
Well, the interpretation is easy and as usual: You have a positive relation between A and B when X is at its mean (i.e., this is the estimated path coefficient between A and B when you moderator is in the model). This relation becomes weaker when X increases (i.e., negative interaction effect).
If you have hypothesized a positive interaction effect (i.e., the relation between A and B becomes stronger when X increases) then you hypothesis is not confirmed.
If you have hypothesized a positive interaction effect (i.e., the relation between A and B becomes stronger when X increases) then you hypothesis is not confirmed.
Dr. Jan-Michael Becker, BI Norwegian Business School, SmartPLS Developer
Researchgate: https://www.researchgate.net/profile/Jan_Michael_Becker
GoogleScholar: http://scholar.google.de/citations?user ... AAAJ&hl=de
Researchgate: https://www.researchgate.net/profile/Jan_Michael_Becker
GoogleScholar: http://scholar.google.de/citations?user ... AAAJ&hl=de