Re: [R] mixed model random interaction term log likelihood ratio test

From: seatales <ssphadke_at_uh.edu>
Date: Thu, 14 Apr 2011 18:57:44 -0700 (PDT)

  1. The three levels of the vector DrugPair actually represent three genotypes, which are some randomly chosen genotypes from a population of many genotypes. That's why I thought it was justified as random effect. Does estimating them as random make sense then?
  2. Also could you please elaborate on your suggestion "=ran"?
  3. Wouldn't (MatingPair|DrugPair) represent nesting rather than the interaction as a random effect? I got (1|DrugPair:MatingPair) from the following post: https://stat.ethz.ch/pipermail/r-sig-mixed-models/2009q1/001966.html

>
> I am using the following model
>
> model1=lmer(PairFrequency~MatingPair+(1|DrugPair)+(1|DrugPair:MatingPair),
> data=MateChoice, REML=F)
>
> 1. After reading around through the R help, I have learned that the above
> code is the right way to analyze a mixed model with the MatingPair as the
> fixed effect, DrugPair as the random effect and the interaction between
> these two as the random effect as well. Please confirm if that seems
> correct.

  You should probably send this sort of question to the r-sig-mixed-models mailing list ...

  You probably want (MatingPair|DrugPair) rather than (1|DrugPair:MatingPair).
Whether REML=FALSE or REML=TRUE depends what you want to do next.

>
> 2. Assuming the above code is correct, I have model2 in which I remove the
> interaction term, model3 in which I remove the DrugPair term and model4 in
> which I only keep the fixed effect of MatingPair.
>

>
> 5. I could not find how to input the random interaction term while using
> lme? Is it the following way? Would someone please guide me to some
> already
> existing posts or help here?

  See above.

>
> Sujal P.
> p.s: If it matters how data is arranged, then I have one vector called
> MatingPair which has 3 levels and another vector DrugPair which also has 3
> levels. The PairFrequency data is a count data and is normally
> distributed.
> The data are huge, hence I am not able to post it here.

  It is probably unwise to estimate DrugPair as a random effect if it only has three levels.

> View this message in context:
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> Sent from the R help mailing list archive at Nabble.com.
> [[alternative HTML version deleted]]
>
>



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Received on Fri 15 Apr 2011 - 06:13:25 GMT

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