On the use of receiver operating characteristic curve analysis to determine the most appropriate p value significance threshold

On the use of receiver operating characteristic curve analysis to determine the most appropriate p value significance threshold

Blog Article

Abstract Background p value is the most common statistic reported in scientific research articles.Choosing the conventional threshold of 0.05 commonly used for the p value in research articles, is unfounded.Many researchers have tried to provide a reasonable threshold for the p value; some proposed a lower threshold, eg, 0.

005.However, none of the proposals has gained universal acceptance.Using the puffy spa headband analogy between the diagnostic tests with continuous results and statistical inference tests of hypothesis, I wish to present a method to calculate the most appropriate p value significance threshold using the receiver operating characteristic curve (ROC) analysis.Results As with diagnostic tests where the most appropriate cut-off values are different depending on the situation, there is no unique cut-off for the p significance threshold.

Unlike the previous proposals, which mostly suggest lowering 2006 nissan altima radio the threshold to a fixed value (eg, from 0.05 to 0.005), the most appropriate p significance threshold proposed here, in most instances, is much less than the conventional cut-off of 0.05 and varies from study to study and from statistical test to test, even within a single study.

The proposed method provides the minimum weighted sum of type I and type II errors.Conclusions Given the perplexity involved in using the frequentist statistics in a correct way (dealing with different p significance thresholds, even in a single study), it seems that the p value is no longer a proper statistic to be used in our research; it should be replaced by alternative methods, eg, Bayesian methods.