P-Value in Anesthesia

P-values in scientific studies are used to determine whether a null hypothesis formulated before the performance of the study is to be accepted or rejected. The p-value is a probability calculation. It reflects the measure of evidence against the null hypothesis. Small p-values correspond to strong evidence. If the p-value is below a predefined limit, the results are designated as "statistically significant" 

For example, If it is to be shown that a new drug is better than an old one, the first step is to show that the two drugs are not equivalent. Thus, the hypothesis of equality is to be rejected.

Limitations of P value:

The p-value refers only to a single hypothesis, called the null hypothesis, and does not make reference to any other hypotheses. One instead one computes the rate of Type I and type II errors as α and β. However, the p-value cannot be directly compared to these error rates α and β – instead it is fed into a decision function.

Shortcomings of P value:

1. The significance level, such as 0.05, is not determined by the p-value. Rather, the significance level is decided by the person conducting the experiment (with the value 0.05 widely used by the scientific community) before the data are viewed, and is compared against the calculated p-value after the test has been performed.

                                I.            Criticismsà criterion used to decide "statistical significance" is based on an arbitrary choice of level (often set at 0.05). If significance testing is applied to hypotheses that are known to be false in advance, a non-significant result will simply reflect an insufficient sample size

                              II.            The p-value is incompatible with the likelihood principle, and p-value depends on the experiment design.

                            III.            p-value is sometimes portrayed as the main result of statistical significance testing, rather than the acceptance or rejection of the null hypothesis at a pre-prescribed significance level.

                            IV.            Due to these criticisms, scientific articles which use p-value are now, not accepted by some organizations

2. The p-value is not the probability that the null hypothesis is true, nor is it the probability that the alternative hypothesis is false – it is not connected to either of these. (it can simply accept or reject hull hypothesis at a particular significance level)
3. The p-value is not the probability that a finding is "merely a fluke." Calculating the p-value is based on the assumption that every finding is a fluke, that is, the result of chance alone.
4. The p-value is not the probability of falsely rejecting the null hypothesisà prosecutor's fallacy.
5. The p-value cannot predict if replicating the experiment would yield the same conclusion. 
6.  The p-value does not indicate the size or importance of the observed effectà the larger the effect, the smaller sample size will be required to get a significant p-value