I have been studying this link. However, i can't really figure out how to calculate the p value for a 2 sided F test where the degrees of freedom are different and the F distribution is asymmetric.

I looked at this as well, where the answer says "The p-value is then the largest α that would lead to rejection, which is equivalent to adding the one tailed p-value above to the one-tailed p-value in the other tail for the degrees of freedom interchanged. "

I do not understand the "degrees of freedom interchanged" part.

According to the answer, the p value computed in R would be (1-pf(val, df1= n1, df2=n2, lower.tail = T)) + (1-pf(val, df1=n2, df2=n1, lower.tail =T)) But I just do not understand why ?

Mathematically and in R, how should the p-values of a two-sided F test be calculated where the degrees of freedom are different?


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.