[R-meta] residual heterogeneity in meta-regression

Daniel Mønsted Shabanzadeh dm@h@b@n @end|ng |rom gm@||@com
Thu Nov 14 11:08:46 CET 2019

Dear Wolfgang

I am performing a meta-regression on multiple one-arm non-randomised
studies in order to explore the impact of moderators on complications
following a surgical intervention. Adding moderators (age catrgory of the
patient, surgical technique etc.) increases the R2:

Mixed-Effects Model (k = 183; tau^2 estimator: REML)

tau^2 (estimated amount of residual heterogeneity):     0.0074 (SE = 0.0010)
tau (square root of estimated tau^2 value):             0.0860
I^2 (residual heterogeneity / unaccounted variability): 99.20%
H^2 (unaccounted variability / sampling variability):   125.63
R^2 (amount of heterogeneity accounted for):            36.78%

Test for Residual Heterogeneity:
QE(df = 156) = 4730.2255, p-val < .0001

Test of Moderators (coefficient(s) 2:27):
QM(df = 26) = 115.5671, p-val < .0001

However, I am unaware of how to interpretate the rising R2 when QE
tests keep on beeing significant. So far I understand that the rising R2
indicates that the heterogeneity is beeing partly explained by moderators,
however does QE change in case most heterogeneity is explained by


Daniel Mønsted Shabanzadeh
Department of Gastroenterology, Surgical Unit
Hvidovre Hospital
Mobile +45 2546 5251

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