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

[Viechtbauer Wolfgang (SP)]

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