Interpreting Moderation Graph


New Member
Hello everyone, I am having troubles interpreting the following graph.
I have performed a interaction analysis to identify if firm size is a moderator of the relationshp between Firm flexibility and consortium adoption.

With a p of .085 > 0.05, I believe it is no moderator at the 95% confidence interval. But how to interpret the graph?

Thank you in advance!

Moderation plot.png


Less is more. Stay pure. Stay poor.
For clarification you only have < 10 observations and you are fitting three terms to the model. If so, what do you think my next reply might say?


New Member
That I have to few data points to provide an interpretation? Referring to your subtitle (less is more;), I unfortunately have no more data points, so I have to work with this. Could you still say something meaningful about this graph?


Less is more. Stay pure. Stay poor.
Yeah, unfortunate data is the exception - more is usually always better :)

I am typically not comfortable with such small datafiles, it is hard to make conclusions beyond chance that are generalizable. What is with the two different graphs? Also I will humor you a little. It seems like I could recreate the data from this figure, but if you want to upload the dataframe and the above syntax for the figure - I may take a gander.

Welcome to the forum!


New Member
EDIT: I have added a .txt file, hopefully you can conveniently copy paste the data from there!

That is definitely true! Unfortunately, I cannot do anything about that at this point. For my other propsitions, I have conducted a necessary conditions analysis, which works fine with n <10.

One of the graphs had the wrong axis titles, I have removed it!

Thank you for your welcome and willingness to help, that is very kind. I am trying to attach an excel, csv file but that does not seem to work. How can I efficiently send the data to you?

Regarding the RStudio Syntax, I have used the ggplot2 package:

> plot <-ggplot(Final_Data_Sheet, aes(Firm_flexibility, Consortium_adoption, colour = Firm_size))
> plot + geom_point() + geom_smooth(method = "lm", aes(fill = Firm_size), alpha = 0.05) + labs(x = "Firm_flexibility", y = "Consortium Adoption", colour = "Firm Size")


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