[R-meta] Capturing the variability at the lowest level of longitudinal studies

[Simon Harmel]

Hi All,

I'm running a meta-analysis on a sample of longitudinal studies. However,
there is so much variability both in the number and in the value of the
time points used in each study.

My general data structure looks like:

study  yi  time  esid x1
  1      .1    1     1
  1      .2    4     2
  2      .3    2     3
  2      .4    2     4
  2      .5    2     5
  3      .6    3     6

I was wondering what --rma.mv()-- syntax can capture the variability at the
lowest level in my data?

Currently, I'm using the following, which I know can't capture the
variability at the lowest level in my data:

m1 <- rma.mv(yi ~ time + x1, V = V, struct = "HAR",
                   random = ~time | study,
                   data = data)

I also tried the following:

m2 <- rma.mv(yi ~ time + x1, V = V, struct = c("HAR","HAR"),
                           random = list(~time | study, ~time | esid),
                           data = data)

But I get a warning that says:
"Each level of the outer factor contains only a single level of the inner
factor, so fixed value of phi to 0. "


I appreciate your expertise,
Simon

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