Exercise: Endarterectomy versus stenting using CMA2, answer 5

Question 5: Is the default fixed effects model the right one to use?

Suggested answer:

To answer this you need to look at the heterogeneity statistics. Click "Next table" to see them.

Because these results form a very wide table, I have split them here. This is the first part of the table:

Model Effect size and 95% interval Test of null (2-Tail)
Model Number
Studies
Point
estimate
Lower
limit
Upper
limit
Z-value P-value
Fixed 9 0.676 0.535 0.853 –3.293 0.001
Random effects 9 0.668 0.470 0.949 –2.250 0.024

This is the second part of the table:

Heterogeneity Tau-squared
  Q-value       df (Q)       P-value     I-squared   Tau
 Squared  
  Standard  
Error
  Variance       Tau    
12.763 8 0.120 37.317 0.089 0.129 0.017 0.298

Note that there are only nine studies, because Brooks et al. (2004) has been dropped.

The Q-value is the chi-squared test for heterogeneity test statistic. The heterogeneity is not significant, P = 0.12, even by the relaxed standard of P<0.10 sometimes used for this test. The I2 statistic is 37%, so there is some heterogeneity, but not as much as 50%, which would be moderate. I would suggest that a fixed effects model is acceptable here. Meier et al. (2010) preferred a random effects model. There is room for debate about this one and either approach would be accepted by most meta-analists, I think.

The point estimates for the two models are very similar, but the confidence interval is wider for the random effects model and the P value is larger, as we would expect.


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Last updated: 19 February, 2010.

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