P-values – interpreting the evidence seriesContinue 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 modulesContinue 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 issuesContinue reading »
Fragility Index is the minimum number of patients whose status would have to change from a “non-event” (not having the primary endpoint) to an “event” (having the primary end point) in order to turn a statistically significant result to a nonsignificant result. It is a simple metric to calculate and use.
Reporting the Fragility Index in RCTs may help readers make more informed decisions about the confidence warranted by RCT resultsContinue reading »