Call:
meta(y = TLMAData$correlations, v = TLMAData$vs, data = TLMAData)

95% confidence intervals: z statistic approximation
Coefficients:
           Estimate Std.Error   lbound   ubound z value Pr(>|z|)
Intercept1 -0.23606   0.25102 -0.72806  0.25593 -0.9404   0.3470
Tau2_1_1    0.12462   0.12602 -0.12238  0.37163  0.9889   0.3227

Q statistic on the homogeneity of effect sizes: 179.8323
Degrees of freedom of the Q statistic: 1
P value of the Q statistic: 0

Heterogeneity indices (based on the estimated Tau2):
                             Estimate
Intercept1: I2 (Q statistic)   0.9889

Number of studies (or clusters): 2
Number of observed statistics: 2
Number of estimated parameters: 2
Degrees of freedom: 0
-2 log likelihood: 1.533195 
OpenMx status1: 0 ("0" or "1": The optimization is considered fine.
Other values indicate problems.)