[R-meta] Dear Wolfgang

[Viechtbauer, Wolfgang (SP)]

Dear Juhyung,

Too many general questions that I cannot answer while typing one-handed due to my injury.

Best,
Wolfgang

>-----Original Message-----
>From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces using r-project.org] On
>Behalf Of Lee, Ju
>Sent: Sunday, 30 January, 2022 1:51
>To: r-sig-meta-analysis using r-project.org
>Subject: [R-meta] Dear Wolfgang
>
>Dear Wolfgang,
>
>I had additional question about using glmulti for selecting best meta-regression
>models.
>
>A dataset I am running a model selection has 2 continuous and 2 categorical
>variables , for example.
>I’ve been running the following code formats:
>
>rma.glmulti <- function(formula, data, random, ...)
>  rma.mv(formula, VCV, data=data,  random=random, method="REML", ...)
>
>best.mod <- glmulti(LRR ~ var 1 + var 2+ var 3 + var 4
>                               random=list(~ 1|study_ID, ~ 1|ID),
>                               struct="DIAG”,
>                               data=lf,
>                               level=1, fitfunction=rma.glmulti, crit="aicc")
>
>where VCV is the variance-covariance matrix.
>Var 1 &2 are continuous and var 3 &4 are categorical.
>Study_ID is the unique pulication ID.
>ID is the unique effect size ID.
>
>It was my understanding that you need to specify the inner structure of your
>random effect list (ex. random=list(~ var3|study_ID, ~ var3|ID)) when your
>moderator is categorical.
>
>My questions are:
>
>  1.  How do you specify inner random effect when you have multiple categorical
>moderators in your models? (only testing the main effect)
>  2.  How do you incorporate this to your model selection procedure using
>glmulti?
>  3.  OR would the random effect structure specified above (random=list(~
>1|study_ID, ~ 1|ID)) suffice?
>
>Thank you very much.
>Best,
>Juhyung
>
>Juhyung Lee
>Postdoctoral Fellow
>Marine Science Center, Northeastern University
>430 Nahant Rd, Nahant, MA 01908, USA
>Phone: +1(650)285-7614