[R-meta] Metafor results tau^2 and R^2

Dustin Lee @@@ug@@ @end|ng |rom gm@||@com
Sat Aug 8 22:13:29 CEST 2020

Dear all,

I am currently conducting a meta regression in which we are examining the
role of temporal effects (year of study) in the relationship between
organizational attitudes and job performance. Using a mixed-effects model
using ML estimation, our analyses have thus far produced results that do
not appear to be irregular.

Our problem: With one relationship the analysis is showing the following:
tau^2 (estimated amount of residual heterogeneity):     0 (SE = 0.0152)
tau (square root of estimated tau^2 value):             0
I^2 (residual heterogeneity / unaccounted variability): 0.00%
H^2 (unaccounted variability / sampling variability):   1.00
R^2 (amount of heterogeneity accounted for):            100.00%

However, the significance of the effect of 'year of study' is significant
along with the omnibus Q_M statistic. While I inherently understand this is
due to the way in which these values (R^2, tau^2, I^2, etc.) are calculated
and that it may be due to the smaller than ideal sample size (k =32) as
suggested by López‐López and colleagues (2014). I am unsure on how these
findings should be reported, particularly the 100% R^2 with the significant
predictor 'year of study' result.

Thank you for any assistance you may be able to provide.

All the best,


López‐López, J. A., Marín‐Martínez, F., Sánchez‐Meca, J., Van den
Noortgate, W., & Viechtbauer, W. (2014). Estimation of the predictive power
of the model in mixed‐effects meta‐regression: A simulation study. *British
Journal of Mathematical and Statistical Psychology*, *67*(1), 30-48.

	[[alternative HTML version deleted]]

More information about the R-sig-meta-analysis mailing list