Hi all,
I have been working on a meta-analysis for the studies in my area of research. I have now got to the point of testing for differences between different subgroups that may have an effect on the HR.
Now, when I run the subgroup analysis, the output includes a heterogeneity summary as below (I have excluded the output of the subgroup analysis here, although for reference the two HRs derived were 1.01 (0.92-1.11) and 0.70 (0.45-1.11):
Heterogeneity summary
-----------------------------------------------------------------------------
Group | df Q P > Q tau2 % I2 H2
---------------+-------------------------------------------------------------
No | 13 44.66 0.000 0.01 53.75 2.16
Yes | 1 1.79 0.181 0.05 44.23 1.79
---------------+-------------------------------------------------------------
Overall | 15 49.37 0.000 0.02 69.62 3.29
-----------------------------------------------------------------------------
Test of group differences: Q_b = chi2(1) = 2.33 Prob > Q_b = 0.127
My question is the following-does the p-value here (0.127) simply relate to the heterogeneity summary, or is it formally testing for differences between the two groups I am interested in examining? I was under the impression that to formally test for subgroup differences in a meta-analysis, we should be running a meta-regression (which I've done as well), although the p-value derived from a meta-regression differs slightly from the p-value derived here in the heterogeneity summary (0.075). What method should I be using to formally test for differences between groups in a meta-analysis?
Warm regards, Oliver
I have been working on a meta-analysis for the studies in my area of research. I have now got to the point of testing for differences between different subgroups that may have an effect on the HR.
Now, when I run the subgroup analysis, the output includes a heterogeneity summary as below (I have excluded the output of the subgroup analysis here, although for reference the two HRs derived were 1.01 (0.92-1.11) and 0.70 (0.45-1.11):
Heterogeneity summary
-----------------------------------------------------------------------------
Group | df Q P > Q tau2 % I2 H2
---------------+-------------------------------------------------------------
No | 13 44.66 0.000 0.01 53.75 2.16
Yes | 1 1.79 0.181 0.05 44.23 1.79
---------------+-------------------------------------------------------------
Overall | 15 49.37 0.000 0.02 69.62 3.29
-----------------------------------------------------------------------------
Test of group differences: Q_b = chi2(1) = 2.33 Prob > Q_b = 0.127
My question is the following-does the p-value here (0.127) simply relate to the heterogeneity summary, or is it formally testing for differences between the two groups I am interested in examining? I was under the impression that to formally test for subgroup differences in a meta-analysis, we should be running a meta-regression (which I've done as well), although the p-value derived from a meta-regression differs slightly from the p-value derived here in the heterogeneity summary (0.075). What method should I be using to formally test for differences between groups in a meta-analysis?
Warm regards, Oliver
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