False-positive and false-negative risks for individual multicentre trials in critical care.

ABSTRACT:

Background

In medical research, null hypothesis significance testing (NHST) is the dominant framework for statistical inference. NHST involves calculating P-values and confidence intervals to quantify the evidence against the null hypothesis of no effect. However, P-values and confidence intervals cannot tell us the probability that the hypothesis is true. In contrast, false-positive risk (FPR) and false-negative risk (FNR) are post-test probabilities concerning the truth of the hypothesis, that is to say, the probability a real effect exists.

Methods

We calculated the FPR or FNR for 53 individual multicentre trials in critical care based on a pretest probability of 0.5 that the hypothesis was true.

Results

For trials reporting statistical significance,

SUBMITTER: Sidebotham D 

PROVIDER: S-EPMC10430847 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature