[R-meta] Meta analysis on means and standard deviation
||@t@ @end|ng |rom dewey@myzen@co@uk
Tue Oct 22 15:37:48 CEST 2019
You might want to swap to emmeans as lsmeans is deprecated. According to
one of the vignettes for emmeans there is no support for objects of
class rma. However this is R so you could always try it and see what
happens. You are not going to break anything.
On 22/10/2019 13:40, Viechtbauer, Wolfgang (SP) wrote:
> Dear Manon,
> Just to check: Is 'variance' in data frame 'table' the variance of the raw measurements or is it the variance of the means? It should be the latter (if 'variance' is the variance of the measurements, then the variance of the means is 'variance / n', where 'n' is the sample size).
> 1) I don't know what you mean by 'adjusted variance'. Variance of what? The variance of the 'adjusted mean'? If so, how did you compute the 'adjusted mean'?
> 2) With anova(meta, btt = 2:4) you would be testing coefficients 2, 3, and 4 simultaneously. If those coefficients correspond to the 'year' factor, then yes, this is the correct way to do this. And yes, if 'age' is included in the model, then this test is 'adjusted' for 'age'.
> 3) I don't know - haven't tried.
> -----Original Message-----
> From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces using r-project.org] On Behalf Of manonbergerat using gmail.com
> Sent: Tuesday, 22 October, 2019 13:54
> To: r-sig-meta-analysis using r-project.org
> Subject: [R-meta] Meta analysis on means and standard deviation
> Dear Meta-analysis community,
> We are performing a meta-analysis on means and we have some questions about the package metafor.
> Our dataset includes means, standard deviations, the year of measure, and the age of our population.
> The code for our meta regression is :
> meta= rma.uni(yi = M, vi = variance, weights = 1/variance, method="REML", mods=~1+Year+Age, data=table)
> 1: We would like to estimate an adjusted pooled variance.
> For the moment, we have succeed to obtain an adjusted pooled mean. But for the variance, can we take into account the value in the variance-covariance matrix (« vb ») as a result of an adjusted pooled variance?
> 2: We categorized the variable « year » and we would like to have a global p-value of this categorized value.
> Is the function in « Anova » anova(meta, btt = 2:4) correct to obtain this global p-value?
> And is it adjusted related to our other variable « age » ?
> Is it possible to have a p-value for trend?
> 3: Is the « lsmeans » package compatible with metafor?
> Thank you in advance.
> Best regards.
> Manon Bergerat
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