[R-meta] rma.mv to lme possible?

[Timothy MacKenzie]

Dear All,

I've specified the following rma.mv() model for my meta-analysis.
However, I'm wondering how to replicate this model using lme() from
the nlme package (sample data is provided below)?

V <- with(dat1, clubSandwich::impute_covariance_matrix(vi,study,r=.6))

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

I'm open to either ML or REML methods of estimation. I have tried the
following with no success:

 lme(yi ~ 0 + study_type,
    random = list(~study_type | study,
                          ~interaction(study_type,reporting) | obs),
    weights = varComb(varFixed(~vi),
                      varIdent(form = ~study | study_type),
                      varIdent(form = ~obs    |
interaction(study_type,reporting))),
      correlation = corCompSymm(.6, ~1|study, fixed = TRUE),
      data = dat1,
      control=lmeControl(sigma = 1,returnObject=TRUE))

Thanks,
Tim M
d="
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 0.31349510 standard
4        A&B    composite  8   yes     3.01 0.91349510 standard
5        G&H    composite  9   yes     2.01 0.97910095 alternative
5        G&H    composite  10  yes     2.11 0.37910095 alternative
6        E&G    composite  11  yes     2.01 0.67910095 alternative
6        E&G    composite  12  yes     2.11 0.87910095 alternative
7        E      subscale   13  yes     0.08 0.21670360 alternative
7        G      subscale   14  yes     0.77 0.91297170 alternative
8        F      subscale   15  yes     1.08 0.81670360 alternative
8        E      subscale   16  yes     1.07 0.91297170 alternative"

dat1 <- read.table(text=d,h=T)