[R-meta] Meta-regression question

[Viechtbauer, Wolfgang (SP)]

Dear Hellen,

Just to clarify: Is 'Task' the same as 'task_category'? Or is task_category 'broader', such that there may be multiple tasks within the same study that fall under the same category?

In the latter case, you could even consider the model:

random = ~ 1 | Study/task_category/Task

But whether this is sensible also depends on how often you actually have multiple tasks for the same category within studies (if this occurs only rarely, then distinguishing these two levels is difficult).

Regardless, yes, your last model does make sense, but you don't need the parentheses, so 'mods = ~ task_category' is sufficient (assuming that 'task_category' is either a factor or a character variable; if it is numeric, then you need 'mods = ~ factor(task_category)').

Best,
Wolfgang

>-----Original Message-----
>From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces using r-project.org]
>On Behalf Of Hellen Mirr
>Sent: Monday, 09 November, 2020 13:00
>To: r-sig-meta-analysis using r-project.org
>Subject: [R-meta] Meta-regression question
>
>Hello
>
>Apologies if this has already been answered and thank you in advance for
>your help!
>
>We are doing a multilevel meta-analysis and would like to run a
>meta-regression to see differences across performance as a function of a
>grouping variable we have.
>
>Our dataset structure is as follows.
>We have two patient groups (A and B) and their performance on a series of
>tasks across several studies. All these tasks are of specific categories,
>e.g. Computing, Imagery, Reading - etc. in the variable "task_category"
>
>We have fit a multi-level meta as follows:
>model1 <-rma.mv(yi, vi, random = ~ 1 | Study/Task, tdist=TRUE, data=df)
>and then applied RVE as some studies reported multiple effect sizes for the
>same patients
>robust_model<- robust(model1, cluster = df$Study, adjust = TRUE) and also
>with clubsandwich
>coef_test () function for better small-sample adjustments.
>
>We would now like to run a meta-regression to see if there are differences
>in performance based on the category of tasks (which is coded in the
>variable "task_category")
>
>Would this be appropriate? As I am getting a bit confused and not sure this
>is the right approach
>metaregression_model <-rma.mv(yi, vi, random = ~ 1 | Study/Task, tdist =
>TRUE, data = df,
>                                 method = "REML",
>                                 mods = ~ (task_category))
>
>Thank you!
>
>Best,
>Hellen