Mixed-Effects Model (k = 21; tau^2 estimator: SJ)

tau^2 (estimated amount of residual heterogeneity): 0.2301 (SE = 0.0752) tau (square root of estimated tau^2 value): 0.4797 I^2 (residual heterogeneity / unaccounted variability): 93.30% H^2 (unaccounted variability / sampling variability): 14.92 R^2 (amount of heterogeneity accounted for): 0.00%

Test for Residual Heterogeneity: QE(df = 19) = 494.7195, p-val < .0001

Test of Moderators (coefficient 2): F(df1 = 1, df2 = 19) = 0.4029, p-val = 0.5331

Model Results:

```
estimate se tval pval ci.lb ci.ub
```

intrcpt 0.7497 0.1143 6.5572 <.0001 0.5104 0.9889 *** fidelity_assessmentY -0.3183 0.5014 -0.6348 0.5331 -1.3676 0.7311

Signif. codes: 0 ‘*’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Dear group,

Thank you for your replies regarding my previous post. I have one more question regarding the meta-regression results. I divided studies into "with fidelity assessment (Y)" and "without fidelity assessment (N)". The test of moderators shows that p-value is 0.5331. However p-value for the intrcpt is <.0001. Based on the previous post, I understand that this means that the group without fidelity assessment is significant. My question is that since the moderator test says that p-value is 0.5331, can I still draw the conclusion that the intercpt group is significant?

In this case, the table is telling you that the estimate for the reference level "without fidelity assessment (N)" is significantly different from zero `<.0001`

. And the other level "with fidelity assessment (Y)" is not significantly different from the reference level (N).

So yes, your reference level in the intercept is significant.

July 12, 2019 08:28 AM

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