[R-meta] Impact of very high tau-square value.
ruecker @end|ng |rom |mb|@un|-|re|burg@de
Wed Jun 26 11:27:19 CEST 2019
in principle, tau -squared can take every non-negative value. Note that
tau is the standard deviation of the random effects. That is, it is
measured on the same scale as the outcome and has the same dimension.
That is, if you measure blood pressure, it is on the scale of blood
pressure, mmHg; if you measure body weight, it is on the scale of body
weight, i.e. kg. There is no other general rule.
If you look at a dimensionless outcome (e.g., (log) odds ratio or
standardized mean difference), the same holds: tau is on the log odds
scale or on the normal scale, respectively.
Thus the meaning of your values depends on what you are measuring.
See the attached paper, page 7.
Am 26.06.2019 um 09:32 schrieb jideofor thomas:
> Hi all,
> I did a random effect meta-analysis using the metafor package and I obtained a tau-squared ( heterogeneity) value greater than 1.
> I was worried because I am nit sure what to make of it; so I did the same analysis under the Bayesian framework. I also obtained a tau-squared value of about 32.8.
> I find it confusing, for one it is quite high and secondly I hadn't come across any discussion on how high the tau-squared value could get.
> My questions are:
> How high can the tau-squared value be?
> Secondly, under this situation can I go ahead and interpret my result but with a warning on the amount of heterogeneity present in the study? Or does the high value of the tau-square make non-sense of my analysis?
> Thanks in advance for your response.
> Jide Ogbu
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Dr. rer. nat. Gerta Rücker, Dipl.-Math.
Institute of Medical Biometry and Statistics,
Faculty of Medicine and Medical Center - University of Freiburg
Stefan-Meier-Str. 26, D-79104 Freiburg, Germany
Mail: ruecker using imbi.uni-freiburg.de
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