help > RE: modeling interaction with continuous predictors
Mar 11, 2022  09:03 PM | Andrew Zalesky
RE: modeling interaction with continuous predictors
Hi Selma, 


yes you are right. If you have the degrees of freedom of the numerator and denominator, the F-value threshold can be easily computed. For example, in Matlab, we can use finv(1-0.01,v1,v2), where v1 and v2 are the degrees of freedom of the numerator and denominator. 

Some researchers struggle with determining the degrees of freedom. Usually, v1 is the number of independent predictors in your model and v2 is the sample size minus the total number of predictors. 

For example, for p=0.01, if we have 5 predictors and a sample size of 100, we have 

F = finv(1-0.01,5,100-5) = 3.22

Note that the exact degrees of freedom may depend on the specifics of the model. 

best,
Andrew
Originally posted by Selma Lugtmeijer:
Hi,

thank you for the quick reply and apologies for not being clear. I hope I can clarify. I did not mean to ask what F-value would give me significant results. My question is on how to determine the F-value threshold. I thought that I could put in the F-value that with my sample size would correspond to a p-value of .01. Maybe my logic is erroneous but for every F-score + numerator + denominator you can calculate the corresponding p-value, so to determine which F-value to put in as threshold I thought to take the F-value that for my sample size corresponds to a p-value of .01. Is it correct to do it like this or is there some other guidance for what value to put there?

Selma

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TitleAuthorDate
Hamed Zivari Dec 8, 2021
Selma Lugtmeijer Mar 10, 2022
Andrew Zalesky Mar 11, 2022
Selma Lugtmeijer Mar 11, 2022
RE: modeling interaction with continuous predictors
Andrew Zalesky Mar 11, 2022
Marius Gruber Dec 22, 2021
Andrew Zalesky Dec 22, 2021
Andrew Zalesky Dec 8, 2021