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Dear Community,

in my PLS-Model I am using a Interaction Effect(using SmartPLS Moderating Effect). The Boostrapping Analysis shows a significant Moderation Effect, whereas both main effects are not significant.

A --> X: Not significant: p-value: 0,081 / Loading: 0,150
B --> X: Not significant: p-value: 0,354 / Loading: 0,065
AB --> X: Significant: p-value: 0,003 / Loading: 0,232

I am wondering if (and how) I can interpret the significant Moderating Effect in this case?

Thanks you for your support.

The moment you include an interaction effect, the effect of A and B on X are not main effects anymore, but conditional effects or simple effects.

The equation that you estimate is then: X = (p1 + p3 ·B) · A + p2 · B which is equivalent with X = (p2 + p3 ·A) · B + p1 · A or X = p1 · A + p2 · B + p3 (A · B)

p1 (the simple effect or conditional effects) is the effect of A on X, when B is zero (because then p3 is ignored). As we use standardized data in PLS (which includes centering), B is zero at the sample mean of B.
With a significant interaction effect (p3) your overall effect of A on X (p1 + p3·B) might be insignifcant when B is zero (p1), but signficant if B is large (e.g., 2*p3) or small (e.g., -3*p3).

@jmbecker Thanks for the kind reply.

Does anybody know a published paper, that interpreted these kind of interaction effect?

Thank you

Dear Zypriafl, did you find any published paper? I'm dealing with a similar issue.

Thanks in advance,

Jose Mesquita

I found these papers to be somehow related to this isssue:

Belsky, J., Pluess, M., & Widaman, K. F. (2013). Confirmatory and competitive evaluation of
alternative gene‐environment interaction hypotheses. Journal of Child Psychology and
Psychiatry, 54(10), 1135-1143.

Grainger, J., Muneaux, M., Farioli, F., & Ziegler, J. C. (2005). Effects of phonological and
orthographic neighbourhood density interact in visual word recognition. The Quarterly
Journal of Experimental Psychology Section A, 58(6), 981-998.

Oh, I. S., Lee, K., Ashton, M. C., & de Vries, R. E. (2011). Are Dishonest Extraverts More
Harmful than Dishonest Introverts? The Interaction Effects of Honesty‐Humility and
Extraversion in Predicting Workplace Deviance. Applied Psychology, 60(3), 496-516.

Thank you, I'll try to find them.

Does anyone could help me in the following issue:

In my model, I'm measuring the effects of complaint satisfaction (CS) and relational switching costs (RS) on switching intention (SI).

Without moderation the main effects are:

CS>>>>SI, negative and significant;
RS>>>>SI, negative, non significant.

When I include the moderation effect of RS on CS (RS*CS), the interaction effect is not significant, but the simple effect becomes significant.

I've never seem such a result and I'm not sure how to explain it.

I would truly appreciate your comments.

Thanks in advance,

Jose Mesquita

Usually the literature suggests that when the interaction effect is not significant, you should not interpret the simple effects, but only the main effects. Likewise, if the interaction is significant you should not interpret the main effects, but only the simple effects.

However, sometimes it may also happen that the interaction effect has a small to medium effect size and is close to being significant and you may only have insufficient power (not enough observations) to find it significant. Of course, it is hard to tell whether such a situations is really present.

Thank you Prof. Becker

jmbecker wrote: ↑Mon Jul 17, 2017 7:50 pm The moment you include an interaction effect, the effect of A and B on X are not main effects anymore, but conditional effects or simple effects.

The equation that you estimate is then: X = (p1 + p3 ·B) · A + p2 · B which is equivalent with X = (p2 + p3 ·A) · B + p1 · A or X = p1 · A + p2 · B + p3 (A · B)

p1 (the simple effect or conditional effects) is the effect of A on X, when B is zero (because then p3 is ignored). As we use standardized data in PLS (which includes centering), B is zero at the sample mean of B.
With a significant interaction effect (p3) your overall effect of A on X (p1 + p3·B) might be insignifcant when B is zero (p1), but signficant if B is large (e.g., 2*p3) or small (e.g., -3*p3).

Hello Dr.Becker
If Moderator have two value (0 , 1) we should put -1 or +1 to "B". but Standard Deviation of final effect is not available. now how to determine significance of final effect?

You can use the bootstrapping output to calculate the values for all bootstrapping samples and then calculate standard errors and confidence intervals from there