jamovi

Hi everyone,
I'm currently writing my bachelor's thesis and I'm having some trouble understanding and interpreting some results. I initially thought I had understood everything correctly and I have already interpreted the data, but I believe I might have made a mistake. I would be very grateful if you could explain whether my interpretation is correct.

My hypothesis is: A high level of need for cognitive closure strengthens the negative effect of unfinished tasks on flow experience in the evening.
UT_mean: Unfinished Tasks
NFC_mean: Need for Cognitive Closure
FIS_mean: Flow Experience

I conducted a moderation analysis using Medmod in Jamovi. The interaction term is not significant, but each individual level of need for cognitive closure (high, medium, low) is significant, with the low level of need for cognitive closure showing the strongest moderating effect. Can I say that, according to the data, a low level of need for cognitive closure strengthens the negative effect of unfinished tasks on flow experience, or is the correct interpretation that, since all levels are significant and the interaction term is not significant, need for cognitive closure does not moderate the negative effect regardless of its level?


And if, in the Simple Slope Estimates, for example, only the high and medium levels are significant but the low level is not, can I say that these two levels (high and medium) moderate the negative effect, even though the interaction term is not significant?I would greatly appreciate an answer, as I'm feeling a bit at a loss.

I think an equivalent way to state your prediction is that the slope of the relationship between NFC and FIS will vary with UT. Another equivalent statement is that there will be a NFC-by-UT interaction, with respect to FIS. Your results indicate a non-significant interaction (.472) which, translates graphically into the three slopes in your figure being not very different from one another.

The simple slope analyses don't directly address the interaction, and so don't directly address your prediction.