# [R-meta] Output in rma

Daniel Mønsted Shabanzadeh dm@h@b@n @end|ng |rom gm@||@com
Fri Mar 6 09:48:44 CET 2020

```Dear Wolfgang and network

I am doing a meta-regression in metafor on transformed proportions with two
categorical variables and once again having some problems in getting the
outcome right. Hope some of you may know your way through.
In the print output I see that 449 entries are included. How do I obtain
number of entries for each level in the variables in the model?

Regards,
Daniel

b<-rma(xi=compl_treat, ni=total, mods = ~indication_cor+age_cor,
measure = "PAS", data=a, slab=study)> print(b)
Mixed-Effects Model (k = 449; tau^2 estimator: REML)

tau^2 (estimated amount of residual heterogeneity):     0.0160 (SE = 0.0012)
tau (square root of estimated tau^2 value):             0.1263
I^2 (residual heterogeneity / unaccounted variability): 99.57%
H^2 (unaccounted variability / sampling variability):   231.76
R^2 (amount of heterogeneity accounted for):            8.04%

Test for Residual Heterogeneity:
QE(df = 441) = 42409.0416, p-val < .0001

Test of Moderators (coefficients 2:8):
QM(df = 7) = 43.4202, p-val < .0001

Model Results:

estimate      se     zval    pval    ci.lb   ci.ub
intrcpt                      0.1641  0.0122  13.4372  <.0001   0.1402
0.1880  ***
indication_cormissing       -0.0142  0.0244  -0.5839  0.5593  -0.0620
0.0335
indication_cortherapeutic    0.0803  0.0195   4.1207  <.0001   0.0421
0.1185  ***
age_cor1                     0.0088  0.0166   0.5280  0.5975  -0.0238
0.0414
age_cor2                     0.0170  0.0262   0.6468  0.5177  -0.0344
0.0683
age_cor3                     0.0466  0.0193   2.4158  0.0157   0.0088
0.0843    *
age_cor4                    -0.0408  0.0328  -1.2433  0.2138  -0.1052
0.0235
age_cormissing              -0.0446  0.0530  -0.8419  0.3998  -0.1484
0.0592

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Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1