[R-meta] network meta-analysis - include block (within-study) level

[Juan Pablo Edwards Molina]

Pretty close to that structure ​you say​:  I have ​several treatments at
each block (balanced experiments), actually different set of treatments
across the k-trials (all trials have the untreated Check)

This are a few lines of trial 3:
​
trt     trial bk  x     y
Check  3    1   40   2493
Check  3    2   45   2173
Check  3    3   40   2628
Check  3    4   40   2168
Fox      3    1   35   3194
Fox      3    2   30   2363
Fox      3    3   35   2887
Fox      3    4   30   3278
NTX     3    1   40   2988
NTX     3    2   35   2361
NTX     3    3   35   2341
NTX     3    4   35   3218
​
|​ Also, do you have the raw mean and variance (or SD) and sample size for
each row of the dataset? It seems like you are first fitting some kind of
ANOVA within each study, but | that might actually complicate things.

Yes, I have the raw full dataset so I ​have the observation level ​values
to calculate SD, means..​

Several authors from the Phytopathology area use ANOVA MSE :

"...The within-study variance (V) for IND or DON for these fungicide trials
is the residual variance (mean square error) from an analysis of variance
(ANOVA) of the effects of treatment on disease or toxin. Where the original
data were available, this variance was calculated directly from an ANOVA..."

http://apsjournals.apsnet.org/doi/abs/10.1094/PHYTO-97-2-0211


*Juan*

On Tue, Aug 8, 2017 at 6:03 PM, Viechtbauer Wolfgang (SP) <
wolfgang.viechtbauer at maastrichtuniversity.nl> wrote:

> Dear Juan,
>
> Could you show a bit of the data (structure)? In particular, does each
> block contain two treatments, so that the structure looks something like
> this?
>
> trial block treatment mean
> --------------------------
> 1     1     1         ...
> 1     1     2         ...
> 1     2     1         ...
> 1     2     2         ...
> 2     1     1         ...
> 2     1     2         ...
> 2     2     1         ...
> 2     2     2         ...
> 2     3     1         ...
> 2     3     2         ...
> ...
>
> ​​
> Also, do you have the raw mean and variance (or SD) and sample size for
> each row of the dataset? It seems like you are first fitting some kind of
> ANOVA within each study, but that might actually complicate things.
>
> Best,
> Wolfgang
>
> -----Original Message-----
> From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-
> bounces at r-project.org] On Behalf Of Juan Pablo Edwards Molina
> Sent: Tuesday, August 08, 2017 22:09
> To: r-sig-meta-analysis at r-project.org
> Subject: [R-meta] network meta-analysis - include block (within-study)
> level
>
> Dear list,
>
> I have a dataset containing crop field randomized block design experiments
> with observations at plot level (experimental unit), and I want to estimate
> the treatments grain yield difference relative to a untreated check.
>
> net1 <- rma.mv(yield, vi2, mods = ~ treatment, random = ~ treatment|
> trial,
>                          method="ML", struct="UN", data=df)
>
> where yield is the vector of mean treatments yield for vi2 is the vector of
> sampling variances obtained by:
>
> vi2 <- V_yield/n  (for each trial)
>
> (V_yield = MSE from anova)
>
> Do I need to include the block in the model? or using the experiment
> treatments means will obtain the same results? I suppose something like:
>
> net2 <- rma.mv(yield, vi2, mods = ~ treatment, random = ~ treatment|
> block|
> trial,
>                          method="ML", struct="UN", data=df)
>
> If the latter would be a better approach, how do I include the sampling
> variance?
>
> Thanks in advance,
>
> Juan Edwards
>

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