In this paper we provide an overview of statistics that are intended to help people better understand how much of an effect an intervention had. For binary outcomes, reasonable options (such as the risk ratio and the number needed to treat) exist to help researchers and consumers contextualize results. For continuous outcomes the situation is much worse. We discuss several alternatives and propose a new metric, NNTThreshold, that is analogous to the number needed to treat statistic for binary outcomes, that is useful when a clinically meaningful threshold can be identified. We show how to compute this new statistic using commonly available software, and from different forms of information. Finally, we provide the results of a small simulation suggesting that NNTThreshold behaves reasonably well (though is slightly conservative in our example).
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 July 2016.
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#334,694
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Outputs of similar age from Journal of Clinical Epidemiology
#33
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