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

[Timothy MacKenzie]

More generally, is there a way to convert/switch an rma.mv() fitted
object to a corresponding lme() fitted object such that then I can use
the resulting object in R packages like "library(effects)"
(https://cran.r-project.org/web/packages/effects/index.html) for
plotting purposes?

Thanks,
Tim M

On Thu, Nov 25, 2021 at 7:57 PM Timothy MacKenzie <fswfswt using gmail.com> wrote:
>
> 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)