I have measurements of some response of a gene, and two factors: the gene, g=1...G and whether the patient/subject has a certain disease, t=1,2.(adsbygoogle = window.adsbygoogle || []).push({});

the full model is

[tex]

y_{gtk}=\mu+\alpha_g+\beta_t +(\alpha\beta)_{gt}+\epsilon_{gtk}

[/tex]

I know that to see if genes have any connection at all with the disease, I just fit the reduced model without the [tex] (\alpha\beta)_{gt} [/tex] interaction and compare the two, but if I want to see if, say, gene number g=25 has anything to do with the disease... I know that the null hypothesis is [tex] H_0 : (\alpha\beta)_{25,t}=0, \textrm{ for all } t[/tex], but how do I test this hypothesis? I am confused at what to do when I can't drop the whole factor and compare.

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# Help! -Inference about interaction coefficients in two-factor study

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