[R-meta] standard error in predictive nonlinear meta-regression

[Cesar Terrer Moreno]

Hi Wolfgang,

Thanks for your response. 

Do you know how I could apply this model to predict effect size on a grid (i.e. on a per pixel basis) for the entire world, with known MAP (precipitation) and MAT (temperature) per pixel coming from maps, and a fix COdif=300?

Something like:

ECMrelSE <- overlay(s[["temperature"]], s[["precipitation"]],  # raster maps for MAT and MAP, respectively
                    fun=predict(ECMmeta, newmods = c(MAP, MAT, 300, MAT*300)))

The above doesn’t work.

Thanks
César

> On 20 Jan 2018, at 10:33, Viechtbauer Wolfgang (SP) <wolfgang.viechtbauer at maastrichtuniversity.nl> wrote:
> 
> Use predict(). In this case:
> 
> predict(ECMmeta, newmods = c(2, 3, 4, 3*4))
> 
> where MAP=2, MAT=3, CO2dif=4, and hence MAT*CO2dif=3*4.
> 
> Best,
> Wolfgang
> 
>> -----Original Message-----
>> From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces at r-
>> project.org] On Behalf Of Cesar Terrer Moreno
>> Sent: Friday, 19 January, 2018 13:45
>> To: r-sig-meta-analysis at r-project.org
>> Subject: [R-meta] standard error in predictive nonlinear meta-regression
>> 
>> Dear all,
>> 
>> Yesterday I could solve my question re SE in a nonlinear model following
>> Phillip and Wolfgang’s great suggestions using the delta method.
>> 
>> Now I need to compute SE for a linear meta-regression:
>> 
>>> summary(ECMmeta <- rma(es, var, data=ecm ,control=list(stepadj=.5),
>> mods= ~ 1 + MAP + MAT*CO2dif, knha=TRUE))
>> 
>> Model Results:
>> 
>>           estimate      se     tval    pval    ci.lb    ci.ub
>> intrcpt       0.5754  0.1828   3.1481  0.0031   0.2057   0.9451   **
>> MAP           0.0002  0.0001   2.6648  0.0111   0.0000   0.0003    *
>> MAT          -0.0589  0.0179  -3.2842  0.0022  -0.0952  -0.0226   **
>> CO2dif       -0.0019  0.0007  -2.7384  0.0093  -0.0032  -0.0005   **
>> MAT:CO2dif    0.0002  0.0001   3.6366  0.0008   0.0001   0.0003  ***
>> 
>> How can I compute SE for a particular pixel with known MAP, MAT and
>> CO2dif?
>> Thanks