Critical Care Evidence Updates – November 2021
What’s new in the Critical Care literature – monthly updates
Continue reading »Category: Evidence-based Medicine
Critical Care Evidence Updates – October 2021
What’s new in the Critical Care literature – monthly updates
Continue reading »Critical Care Evidence Updates – September 2021
What’s new in the Critical Care literature – monthly updates
Continue reading »Critical Care Evidence Updates – August 2021
What’s new in the Critical Care literature – monthly updates
Continue reading »Critical Care Evidence Updates – July 2021
What’s new in the Critical Care literature – monthly updates
Continue reading »Critical Care Evidence Updates – June 21
What’s new in the Critical Care literature – monthly updates
Continue reading »Bayesian Statistics
Bayesian Statistics “Under Bayes’ Theorem, no theory is perfect. Rather it is a work in progress, always subject to refinement and further testing” Nate Silver Introduction With the recent publication of the REMAP-CAP steroid arm and the Bayesian post-hoc re-analysis of the EOLIA trial, it appears Bayesian statistics are appearing more frequently in critical care trials. The purpose of this […]
Continue reading »P-Value
P-values – interpreting the evidence series
Continue reading »Critical Appraisal – Glossary
Rather than reinvent the wheel, we are delighted to include a link to the RCEM Critical Appraisal Dictionary. The RCEM learning site provides excellent open access educational resources, including critical care appraisal modules
Continue reading »Type 1 and 2 Errors
In statistical hypothesis testing, a type I error is the incorrect rejection of a true null hypothesis (a “false positive”), while a type II error is incorrectly retaining a false null hypothesis (a “false negative”). The more you try and avoid a Type I error (false positive), the more likely a Type II error (false negative) may happen. Researchers have found that an alpha level of 5% is a good balance between these two issues
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