[R-meta] Multiple comparisons / Tukey test multilevel meta analysis

[Michael Dewey]

Dear Anne

While we wait for Wolfgang to reply there are a couple of things you 
could try.

1 - do any of the slightly different approaches outlined in 
http://www.metafor-project.org/doku.php/tips:testing_factors_lincoms work?

2 - what happens if you do traceback() immediately after the error? At 
least then we would know where it is looking for the model.matrix (that 
should work on models from rma.mv as far as I can see).

Michael

On 17/10/2017 10:32, Kranzbuhler, Anne wrote:
> Hi,
> 
> I am doing a multilevel meta analysis with the metafor package (I am new to all this, so please excuse me if this is a stupid question). I want to run a moderator analysis with one categorical moderator that has 15 levels. Is there any way that I could run some sort of post-hoc (Tukey) test to determine which of the levels do or do not differ?
> The output of the model is as follows (I now want to know whether the different levels of the variable "emo" differ. Trying the glht() command always produces an error - see below).
> 
> Is there anyone who could help me with this?
> 
> 
> 
> mods_emos <- rma.mv(EF_FisherZ, variance_FisherZ, W= weight_FisherZ, mods= ~ emo, random = list(~ 1 | Study, ~ 1 |  Effectsizecount), data=data_neg, method='ML')
> summary(mods_emos, digits=3)
> 
> Multivariate Meta-Analysis Model (k = 820; method: ML)
> 
>    logLik  Deviance       AIC       BIC      AICc
> -167.024  3189.101   368.048   448.106   368.811
> 
> Variance Components:
> 
>             estim   sqrt  nlvls  fixed           factor
> sigma^2.1  0.038  0.195     85     no            Study
> sigma^2.2  0.063  0.250    820     no  Effectsizecount
> 
> Test for Residual Heterogeneity:
> QE(df = 805) = 18413.355, p-val < .001
> 
> Test of Moderators (coefficient(s) 2:15):
> QM(df = 14) = 35.150, p-val = 0.001
> 
> Model Results:
> 
>           estimate     se    zval   pval   ci.lb   ci.ub
> intrcpt    -0.286  0.069  -4.129  <.001  -0.422  -0.150  ***
> emo2        0.036  0.125   0.292  0.770  -0.208   0.281
> emo3        0.032  0.124   0.255  0.798  -0.212   0.275
> emo4        0.273  0.120   2.282  0.023   0.039   0.508    *
> emo5        0.140  0.080   1.751  0.080  -0.017   0.297    .
> emo6        0.234  0.099   2.357  0.018   0.040   0.429    *
> emo7        0.210  0.163   1.290  0.197  -0.109   0.529
> emo12       0.364  0.105   3.461  <.001   0.158   0.571  ***
> emo13      -0.090  0.114  -0.784  0.433  -0.313   0.134
> emo14       0.032  0.112   0.289  0.773  -0.187   0.252
> emo15       0.125  0.124   1.012  0.312  -0.117   0.368
> emo17       0.148  0.142   1.044  0.297  -0.130   0.425
> emo18      -0.101  0.128  -0.788  0.431  -0.353   0.150
> emo19       0.104  0.141   0.741  0.458  -0.172   0.381
> emo21       0.260  0.189   1.372  0.170  -0.111   0.631
> 
> 
> glht(mods_emos, linfct = mcp(emo = "Tukey"))
> 
> Error in formula.default(object, env = baseenv()) : invalid formula
> Error in factor_contrasts(model) :
>    no 'model.frame' method for 'model' found!
> 
> 
> 
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-- 
Michael
http://www.dewey.myzen.co.uk/home.html