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Reviewer's opinion :The Table 2 fallacy may also apply for the linear regression. Again, the authors should show that for any estimate from the linear regression that is reported in this manuscript, none of the other variables in the model were potential mediators. If there are potential mediators, then several models should be conducted to ensure none of the estimates are over adjusted.

After statistical analysis, I obtained the following results:

As shown in the table, Pearson or Spearman correlation coefficient was selected to evaluate the correlation between the variables in the included linear model according to the characteristics of the data distribution, and it was found that there was no correlation between the confounding factors (age and gender) that needed adjustment and the dependent variable (Mps concentration) (p > 0.05).

Can I answer the reviewer's questions in this way?Did I misunderstand the reviewer's question?

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I would put "significant" between "no" and "correlation" and I would include the effect size (in this case, the correlation coefficients). And I'd take out "that needed adjustment". And I might add something about why what you did rules out mediation. Something beginning "since mediation involves a causal chain where the mediator is related to both the IV and the DV, showing that there are no strong relations between the mediator and the DV shows that there is no mediation."

The reviewer probably knows this, but it doesn't hurt to put it in (especially if the editor doesn't know it).

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  • $\begingroup$ Thank you very much for your answer, which is very helpful to me. $\endgroup$
    – zhiheng yi
    Feb 29 at 11:27
  • $\begingroup$ You're welcome. If it fully answers your question, you can click the check mark to accept it. $\endgroup$
    – Peter Flom
    Feb 29 at 11:29

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