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--- tips:comp_two_independent_estimates [2020/07/03 10:28] – Wolfgang Viechtbauer
+++ tips:comp_two_independent_estimates [2020/07/03 10:32] – Wolfgang Viechtbauer
@@ Line 113: / Line 113: @@
 Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
 </code>
-The result is very similar to what we saw earlier: The coefficient for the ''alloc'' dummy is equal to $b_1 = -0.490$ ($SE = 0.362$) and not significant ($p = .176$).
+The result is very similar to what we saw earlier: The coefficient corresponding to the ''alloc'' dummy is equal to $b_1 = -0.490$ ($SE = 0.362$) and not significant ($p = .176$).
 However, the results are not exactly identical. The reason for this is as follows. When we fit separate random-effects models in the two subsets, we are allowing the amount of heterogeneity within each set to be different (as shown earlier, the estimates were $\hat{\tau}^2 = 0.393$ and $\hat{\tau}^2 = 0.212$ for studies using and not using random assignment, respectively). On the other hand, the mixed-effects meta-regression model fitted above has a single variance component for the amount of residual heterogeneity, which implies that the amount of heterogeneity //within each subset// is assumed to be the same ($\hat{\tau}^2 = 0.318$ in this example).