The summary measures approach for clinical trials

What is it about?

Researchers are sometimes surprised to learn that reducing repeated measures on patients to a single summary is often nearly as powerful as the corresponding mixed model. In fact with complete data they cam be equivalent. Even when data are missing the gain in interpretability may outweigh the small loss in efficiency. In fact, the choice of statistic to carry the signal is more important than the choice between summary measures and mixed models.

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Why is it important?

Eliminates modelling mumbo-jumbo and gets to the essence of the repeated measures problem.