The growing awareness of the need for reproducibility in research is encouraging, but what does reproducible research actually look like in practice? Marty and I recently had an interesting discussion on what it means for a study’s findings to be independently replicated, and the metrics scientists use to interpret reproducibility. I tend to interpret level of reproducibility using confidence intervals
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In two previous post (1, 2), I highlighted a symposium that was held to improve the reproducibility of biomedical research. The published report includes a discussion on cultural factors that have contributed to the high prevalence of irreproducible research. Culture and nature of science Whether or not the questionable research practices described in the previous post are the result of
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There is much talk about open science lately. One aspect of this movement towards more transparent and reproducible science is the open sharing of data and computer code. As highlighted in a recent article in Nature, Github is increasingly being used by scientists to do just that! Github in science Git is a powerful distributed version control tool that can
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Allocation concealment and blinding are characteristics that prevent bias in randomised controlled trials and experimental studies. However, these concepts are often confused. Using a randomised controlled trial as an example, the statistician Philip Sedgwick explains the differences between allocation concealment and blinding, and why these characteristics are important: Researchers investigated whether a nutritious meal and food packages was more effective
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Sometimes when we plot data we want to indicate a relevant feature or have a user select a section of the data. For example, if we record electromyography (EMG) and force signals, we might want to have the user mark the baseline EMG level so that it can be removed, and determine the amount of EMG produced during a maximum
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In a previous post, I highlighted a symposium that was held to improve the reproducibility of biomedical research. The published report includes a description of the causes and factors associated with poor reproducibility; these are summarized below. Key causes and factors linked to poor reproducibility False discovery rate and small sample sizes. The false discovery rate is the expected proportion
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