[R-meta] Multilevel meta-analysis with a categorical moderator | subgroup analysis using meta-regression

[Katharina Agethen]

Dear all,

I'm currently working on a meta-analysis on collective orientation and job performance. I'm conducting a multilevel meta-analysis to account for dependency in the data because multiple predictors (i.e., several measures of collective orientation) and multiple outcomes (i.e., several measures of job performance (e.g., task performance, contextual performance)) were often assessed in the same sample. Correlation values were converted to Fisher's z scale.

The code for the main effect is as follows:

full.model <- rma.mv(yi = z, 
                     V = vz, 
                     slab = samid,
                     data = df,
                     random = ~ 1 | samid/esid, 
                     test = "t", 
                     method = "REML", 
                     dfs="contain")

summary(full.model)

full.model.robust <- robust(full.model, cluster=df$samid, clubSandwich = TRUE)
summary(full.model.robust)


In addition, I want to test the type of performance (pertype) as a categorical moderator (i.e., general, in-role, extra-role). I fitted a meta-regression model with pertype as the categorical moderator based on all studies:

mod.pertype <- rma.mv(yi = z, 
                    V = vz, 
                    slab = samid, 
                    data = df,
                    random = ~ 1 | samid/esid, 
                    test = "t", 
                    method = "REML",
                    dfs="contain",
                    mods = ~ pertype)

summary(mod.pertype)

mod.pertype.robust <- robust(mod.pertype, cluster=df$samid, clubSandwich = TRUE)
summary(mod.pertype.robust)

Am I right that, in this case, the amount of residual heterogeneity will be the same in each subgroup?
Is it possible to fit a multilevel model with the subgroups using meta-regression while allowing the amount of residual heterogeneity to vary across subgroups?

I understand that I could fit three separate multilevel models for each subgroup and then compare the estimates using a Wald-type test. But I'm wondering whether I can fit a single model with varying heterogeneity across subgroups?
I read Wolfgang's examples of how to compare estimates from independent meta-analyses and subgroups (http://www.metafor-project.org/doku.php/tips:comp_two_independent_estimates). But I'm not sure how to apply these examples to a multilevel meta-analysis with categorical moderators. 

Thanks a lot for your help.

Best,
Katharina

--
Katharina Agethen
Research Assistant
Human Resource Management

OWL University of Applied Sciences and Arts
Department of Business Administration and Economics
Campusallee 12
32657 Lemgo, Germany