[R] calculate power-linear mixed effect model

[Bert Gunter]

Wrong list! Post on r-sig-mixed-models, not here.

Bert Gunter

"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )

On Fri, Sep 17, 2021 at 12:22 PM Ana Marija <sokovic.anamarija using gmail.com> wrote:
>
> Hi All,
>
> I plan to identify metabolite levels that differ between individuals
> with various retinopathy outcomes (DR or noDR). I plan to model
> metabolite levels using linear mixed models ref as implemented in
> lmm2met software. The model covariates will include: age, sex, SV1,
> SV, and disease_condition.
>
> The random effect is subject variation (ID)
>
> Disease condition is the fixed effect because I am interested in
> metabolite differences between those disease conditions.
>
> This command  will build a model for each metabolite:
> fitMet = fitLmm(fix=c('Sex','Age','SV1,'SV2','disease_condition'),
> random='(1|ID)', data=df, start=10)
>
> SV1 and SV2 are surrogate variables (numerical values)
>
> Next I need to calculate the power of my study. Let's say that I have
> 1,172 individuals total in the study, from which 431 are DR. Let's say
> that I would like to determine the power of this study given the
> effect size of 0.337.
>
> I know about SIMR software in R but I am not sure how to apply it to
> my study design.
>
> I looked at this paper:
> https://besjournals.onlinelibrary.wiley.com/doi/10.1111/2041-210X.12504
>
> But I am not sure how to adapt the code given in the tutorial so that
> it is matching to mine design.
>
> Can you please help,
>
> Thanks
> Ana
>
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