Scott examines studies linking sleeping pills to increased mortality, highlighting a new study that found no link after adjusting for 300 confounders, potentially challenging the validity of less thorough studies. Longer summary

Scott Alexander discusses a controversial topic in medical research: the link between sleeping pills and increased mortality. He reviews several studies that found a strong association between sleeping pill use and higher death rates from various causes, even after controlling for confounders. However, he then introduces a new study by Patorno et al. that found no such link for benzodiazepines. The key difference is that this study adjusted for an unprecedented 300 confounders using a new statistical algorithm. Scott suggests that if this study is correct, it could mean that many other medical studies that only control for a handful of confounders might be inadequate. He draws parallels to other fields where dramatically increasing scale or intensity has led to new insights. Shorter summary

Scott Alexander dissects a hoax chocolate study to critique common misconceptions about nutrition science, study design, and statistical methods. Longer summary

Scott Alexander analyzes a viral study claiming chocolate aids weight loss, which was revealed as a hoax designed to expose poor science journalism. He critiques four common but incorrect conclusions drawn from this incident: that people were gullible for believing it, that nutrition isn't a real science, that studies always need high sample sizes, and that p-values should be eliminated. Scott argues that there is previous research supporting chocolate's health benefits, that nutrition science uses multiple study types to build evidence, that sample size importance depends on the effect being studied, and that p-values have their place in research. He agrees with the fifth conclusion that science journalism should be trusted less, but notes that some sources like Wikipedia and specialized blogs are more reliable. Shorter summary