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

[Dustin Lee]

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,

Dustin

Reference:
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.

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