Meta-analysis of sequential trials

What is it about?

It is shown that fixed-effect meta-analyses of naïve treatment estimates from sequentially run trials with the possibility of stopping for efficacy based on a single interim look are unbiassed (or at the very least consistent, depending on the point of view) provided that the trials are weighted by information provided. A simple proof of this is given. An argument is given suggesting that this also applies in the case of multiple looks. The implications for this are discussed.

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Why is it important?

Provides an explanation of a paradoxical disagreement between Bayesian and frequentist inference