Suppose we have the linear model for Y, with X1, X2 and X3 being continuous independent variables:
Y = b0 + b1 * X1 + b2 * X2 + b3 * X3 + e
To test H0: b1=b2=0 against H1: b1 or b2 or both are different from zero, the F-test can simply be used. If the right tail probability for F is lower than 0.05, say, H0 can be rejected. Here, both "sub-hypotheses" about b1 and b2 are tested two-sided.
But what if the alternative hypothesis H1 would be: b1>0 or b2>0 or both > 0. In that case, both "sub-hypotheses" about b1 and b2 are directional. In a t-test for each b separately, a two-sided p-value (if the software used would only produce two-sided p-values) should be halved. But what about the F-value? Is it possible to use the (or some) F statistic for such simultaneous directional alternative hypotheses? Any thoughts or references would be great, thanks!
Ben.
brmsfor example) and compute the direct evidence (ie. the posterior probability) for the complex alternative. – dipetkov Oct 05 '22 at 18:19