Dear Np No

First, check the sign of the correlation coefficient (Pearson, Spearman, or others, depending on the condition of your data).

Before studying the regression model, you must calculate the correlation coefficients, which give you the inevitable result about the direction and strength of the relationship.

Regarding the interpretation of negative regression or correlation coefficients

An inverse relationship means, for example, one of two situations.

First: An increase in the value of the independent variable will lead to a decrease in the value of the dependent variable.

Second: A decrease in the value of the independent variable will lead to an increase in the value of the dependent.

The concept of increase and decrease is fundamentally related to the state of the studied variable and its logic.

EXP:

The shorter treatment period means a faster recovery. This is a positive thing, And A drop in vital indicators below a certain level, such as blood pressure, means something negative.

The depth here is expressed in the number after calculating it. If you need more detailed help, you can contact me, and you are welcome.

Interpreting the sign of a regression coefficient in a moderation analysis, such as the PROCESS moderation analysis you've conducted, can be a bit nuanced. Let's break down your scenario:

Now, let's interpret this result:

The negative interaction coefficient suggests that the relationship between Hos and PDm is moderated (influenced) by Coh. Specifically, it indicates that the effect of Hos on PDm becomes less negative or possibly even reverses direction (i.e., becomes positive) as Coh increases.

In simpler terms:

• When Coh is low (or lower), the negative relationship between Hos and PDm is stronger or more pronounced.
• When Coh is high (or higher), the negative relationship between Hos and PDm is weaker, and in extreme cases, it might even become positive (though this should be interpreted cautiously and with consideration of the specific data and context).

In summary, Coh appears to moderate the relationship between Hos and PDm by weakening the negative effect or making it less severe, not exacerbating it. However, be cautious with interpreting the exact magnitude and direction of the moderation effect; it may vary depending on the specific values of Coh and the data you have. Always consider the context and the theoretical implications of your findings when interpreting moderation effects.

Dear Np No,

First of all, you need to understand how moderation works and the specific context of your analysis are. For instance, in moderation analysis, you're typically examining how the relationship between predictor and outcome is influenced by moderator variable. Thus, a negative regression coefficient for moderator term suggests that this variable has a diminishing or attenuating effect on the relationship between the predictor and the outcome.

Overall, depending on the characteristics of the variables involved, we could speak of amplification effect (when variables are negative), attenuation effect (when variables are positive) or direction change

My take on is that the predictor, Hos, has no significant main effect whereas Coh has a positive main effect and the interaction is significant and negative. The upshot is that, although the effect of Hos looks negative as per the literature, this is only significant at higher levels of Coh (which shows a very strong positive relationship to the criterion, PDm).

I would expect such an outcome with an underpowered analysis, but this seems unlikely with an N of 349.