[R-meta] Unimodal relationship?
Cesar Terrer Moreno
cesar.terrer at me.com
Fri Mar 9 17:01:03 CET 2018
Indeed, I mean a U-shaped curve. I want to:
i) run model selection in the context of meta-analysis, but including this unimodal response, e.g.:
glmulti(es ~ CNr + Biome + ph + totN. + MAT + MAP + deltaco2, marginality=TRUE,
dat=ecmdat,level=2, fitfunction=rma.glmulti, crit="aicc", confsetsize=2^7)
ii) and if it comes up as an important predictor, including this unimodal predictor in a meta-regression.
rma(es, var, data=ecmdat , mods= ~ MAT + MAP + deltaco2 + CNr)
So my question is, how can I treat CNr so the model understand CNr does not follow a linear relationship?
> On 9 Mar 2018, at 16:38, Michael Dewey <lists at dewey.myzen.co.uk> wrote:
> Dear Cesar
> When you say a unimodal relationship do you mean a U-shaped one? There are various options depending on exactly what you want to do.
> On 09/03/2018 12:14, Cesar Terrer Moreno wrote:
>> Dear all,
>> I initially run a model selection analysis, and found 3 potentially important predictors: MAT, MAP and deltaCO2, and potentially also the interaction MAT:deltaco2: https://www.dropbox.com/s/qeu50krq2e78sju/Rplot11.jpeg?dl=0 <https://www.dropbox.com/s/qeu50krq2e78sju/Rplot11.jpeg?dl=0>
>> However, I suspect that the next predictor in importance, CNr, might be more important than here shown. The problem is that it may follow a nonlinear behaviour. In particular, based on the plot, it seems it may follow an unimodal relationship: https://www.dropbox.com/s/ahpq07y8929muti/Rplot13.jpeg?dl=0 <https://www.dropbox.com/s/ahpq07y8929muti/Rplot13.jpeg?dl=0> or at least interact with other predictors more clearly.
>> How would you include a potentially unimodal shape in a model in `metafor`?
>> This is the best model:
>> rma(es, var, data=dat , mods= ~ 1 + MAT + MAP + deltaco2 + deltaco2:MAT, knha=TRUE))
>> Please help me figure out how to include CNr in this model as a nonlinear relationship.
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