Hi I am trying a mediation analysis (using library("mediation") in R)
My model has 3 predictors and one mediator (n=455), but I am only interested in predictor 1. There is some collinerarity between predictor 1 and 2 - 0.383444 (Pearson). No collinerarity between predictor 3 and the others. The Mediator is correlated with IV1 and slightly with IV2. Predictors, Mediator and dependent variable are all continuous.
lm(DV ~ IV1 + IV2 + IV3 , data = data)
Only IV2 is significant, R2 = 0.050
lm(DV ~ Mediator + IV1 + IV2 + IV3 , data = data)
Mediator and IV2 is significant, R2 = 0.056
I have a much bigger dataset with n = 1200, but unfortunately I don't have Mediator information available for them. If I do a linear regression to predict DV with this dataset, IV1 and IV2 are both highly significant, the standardized beta meaningful.
With this information can I investigate the mediating effect of the mediator on IV1 with my small dataset with 455 subjects (using the mediate()-Function of the "mediation"-package in R) , even though the dataset itself is too small to show a significant effect of IV1 on the DV?
Also, I was wondering whether my mediator might mediate IV2-effect. The correlation between IV1 and the mediator is higher than between IV2 and the mediator though.
I am thankful for any ideas.