P-Value
P-values – interpreting the evidence series
Continue reading »A compendium of critical appraisals in Intensive Care Medicine research and related specialties
P-values – interpreting the evidence series
Continue reading »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 »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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