[R-meta] Can/should we code for treatment groups?

[Jack Solomon]

Dear Simon,

I offer my two cents, my senior colleagues (perhaps Wolfgang and James) on
the list are welcome to further clarify. To your main question, no. You
need each code to represent the same thing (e.g., the same type of
treatment) across all studies so you could generalize beyond the observed
levels of "trt_grp" by adding a random-effect for it.

That said, I think (again comments are welcome by the list members) there
is at least one way in which coding by simply distinguishing between
"treatment groups" in each study (i.e., coding any group 1, and then
another group 2 etc. simply for indexing purposes) might be useful.

For example, if you intend (as your example data suggests) to fit a
longitudinal multilevel model, it may be more "realistic" to assume that
true effect sizes at different time points are correlated IF they come from
the same treatment group in each study; rather than simply each study as a
whole disregarding the groups.

The former in `rma.mv()` syntax will be represented by: `~ time | study` .
The latter will be represented by:  `~ time | interaction(study, trt_grp)`.

Again just my two cents,
Jack



On Thu, Jul 29, 2021 at 4:12 PM Simon Harmel <sim.harmel using gmail.com> wrote:

> Dear Meta-Analysis Experts,
>
> My understanding is that when coding for any random feature in studies, the
> code (numeric or otherwise) should denote the same thing across the
> studies. For example, measure "A" in study 1 and study 2, 3 ... should all
> refer to the same thing.
>
> But some of my studies have multiple treatment groups (trt_grp) and I'm
> simply coding them 1, 2, ... in each study. Thus, trt_grp "1" in study 1
> and study 2, 3,... DON'T necessarily refer to the same thing. Same is true
> for "samp" (independent samples of subjects recruited in each study) across
> the studies.
>
> So, my question is; can "trt_grp" and "samp" be used as
> random-effects and be generalizable beyond their levels (or can they even
> be used as fixed effects)?
>
> I highly appreciate your input,
> Simon
>
> study samp trt_grp measure time
> 1       1        1          A             0
> 1       1        2          B            1
> 1       2        1          A             0
> 1       2        2          B            1
> 2       1        1          A             0
> 2       1        2          B            0
>
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>
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