In this episode we follow up on our conversation with Tim Lash on Quantitative Bias Analysis (QBA), something both Hailey and I have experience with. We talk about what QBA is, why you would want to use it and for what sources of bias it is most applicable. We talk about our own experience with QBA and when we find it most useful. We talk about cases where lots of measurement error leads to little bias and cases where small amounts of measurement error leads to lots of bias. We talk about the overused phrase “non-differential bias towards the null” and why we both hate it. We discuss the impact of bias in terms of direction, magnitude and uncertainty in study results. We talk about the critiques of the methods and when QBA should be done. And we discuss what the role of peer review is (and if it should include QBA). And we discuss Matt’s whether our small talk is useful, our ability to time travel and whether naps are good or bad and if podcasts can nap.

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