[R-meta] Meta-regression question
he||enm|r554 @end|ng |rom gm@||@com
Mon Nov 9 13:00:18 CET 2020
Apologies if this has already been answered and thank you in advance for
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
robust_model<- robust(model1, cluster = df$Study, adjust = TRUE) and also
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
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))
[[alternative HTML version deleted]]
More information about the R-sig-meta-analysis