Do I need to control for Type 1 errors?

#1
Hi guys, the situation I have is, a reviewer has asked me to reduce my mediation model (MPLUS) as he says I have too many tests going on. In fairness it is a large model.

its 6 IVs > 4 mediators > 1 DV so I guess 24 possible mediated tests although I only have 3 significant indirect paths. i have complied and reduced the model to 5 iVs 3 mediators but I dont wish to lose anymore variables as this will upset the focus of the paper.

I guess I could use Bonferroni corrected alpha but i dont know how to calculate corrected 95%Ci - so that is out.

So at the moment - I have 15 IVs on 3 mediators and 1 DV. Personally, I think this is okat - but what do you think?
 

hlsmith

Omega Contributor
#4
By mediation regression, you are alludung to having multiple interaction terms? Are all of your terms significant or hold clinical significance?
 

seanw

New Member
#6
Hi guys, the situation I have is, a reviewer has asked me to reduce my mediation model (MPLUS) as he says I have too many tests going on. In fairness it is a large model.

its 6 IVs > 4 mediators > 1 DV so I guess 24 possible mediated tests although I only have 3 significant indirect paths. i have complied and reduced the model to 5 iVs 3 mediators but I dont wish to lose anymore variables as this will upset the focus of the paper.

I guess I could use Bonferroni corrected alpha but i dont know how to calculate corrected 95%Ci - so that is out.

So at the moment - I have 15 IVs on 3 mediators and 1 DV. Personally, I think this is okat - but what do you think?
It's not too difficult to calculate the CIs if you use Bonferroni correction. Basically, when you change the p-value, you adjust the critical t-value accordingly when you calculate your CI boundaries. Let p* be your Bonferroni-adjusted p-value and df be your degrees of freedom (same as it would be); then, you can find the corresponding critical t-value in R with

qt(1-p*,df)

Substitute the new critical t-value into the CI formula and voila. :)

Conversely, if it's not strictly necessary to report CIs, you could simply report p-values and compare them to the Bonferroni-adjusted p-value. If you report a standard error as well, then knowledgeable statisticians can figure out the adjusted CIs themselves.