[R-meta] Specifying V in nested subgroup analysis (rma.mv + clubSandwich)

[Timothy MacKenzie]

Dear Meta SIG Members,

I'm running a nested subgroup analysis. That is:

1. Studies are subgrouped by "study_type" into standard vs. alternative.
2. Each previously made subgroup is further subgrouped by "reporting"
into subscale vs. composite (see data example below).

Effect sizes in each study are correlated (due to the individual study
designs) but my question is: given the "nested subgroup nature" of my
model, how should I specify the V (subgroup=NULL, or
subgroup=study_type, or subgroup=reporting)?

Thanks,
Tim M

(V <- with(dat1, impute_covariance_matrix(vi, study, r=.6,subgroup=NULL)))

g<-rma.mv(yi ~ 0 + study_type:reporting, V, random = list(~study_type
| study, ~interaction(study_type,reporting) | obs), struct =
c("DIAG","DIAG"), data = dat1)

m="
study subscale  reporting  obs include yi   vi         study_type
1        A      subscale   1   yes     1.94 0.33503768 standard
1        A      subscale   2   yes     1.06 0.01076604 standard
2        A      subscale   3   yes     2.41 0.23767389 standard
2        A      subscale   4   yes     2.34 0.37539841 standard
3        A&C    composite  5   yes     3.09 0.31349510 standard
3        A&C    composite  6   yes     3.99 0.01349510 standard
4        A&B    composite  7   yes     2.90 0.91349510 standard
4        A&B    composite  8   yes     3.01 0.99349510 standard
5        G&H    composite  9   yes     1.01 0.99910197 alternative
5        G&H    composite  10  yes     2.10 0.97910095 alternative
6        E&G    composite  11  yes     0.11 0.27912095 alternative
6        E&G    composite  12  yes     3.12 0.87910095 alternative
7        E      subscale   13  yes     0.08 0.21670360 alternative
7        G      subscale   14  yes     1.00 0.91597190 alternative
8        F      subscale   15  yes     1.08 0.81670360 alternative
8        E      subscale   16  yes     0.99 0.91297170 alternative"
dat1 <- read.table(text=m,h=T)