Timeline for Reporting results of fixed effect MA alongside results of random effects MA
Current License: CC BY-SA 3.0
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| Mar 30, 2017 at 15:13 | comment | added | D_Williams | I'd be interested to see a paper on this topic investigating your notion. It would not be too difficult to simulate yourself. Simply generate some biased effects selected for significance, then answer your question comparing the performance of RE or FE models over the long run. Also, one could take the position they are will to sacrifice some accuracy of the point estimate to ensure they don't erroneously reject the null. I'd be more worried about the ratio of estimate to standard error. Furthermore, if the interval is to narrower, this can increase type one error rate. | |
| Mar 30, 2017 at 13:43 | comment | added | ChrisP | I'm not sure I agree that RE can always be assumed. If FE models are indeed less affected by the biases of small studies, then in this instance it's conceivable that, while both RE and FE are inaccurate, FE may be less inaccurate (although CIs will probably be too narrow). I imagine there is a simulation study which addresses this, but I haven't been able to find one. | |
| Mar 30, 2017 at 9:33 | history | edited | D_Williams | CC BY-SA 3.0 |
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| Mar 30, 2017 at 9:27 | history | answered | D_Williams | CC BY-SA 3.0 |