An Overview of Statistical and Clinical Concepts with the Approach of Hypothesis Testing (P-value)

Application and interpretation of statistical significance of association are the basic and necessary principle in medical research. Traditionally, hypothesis testing and reporting p-values are widely used to quantify the statistical significance of observed results. In the last two decades, the calculation of a p-value in research and especially the use of a threshold to declare the statistical significance of the p-value have been challenged. The limitations of p-value, such as the dependence of its value on the sample size and not reflecting the clinical significance, have been repeatedly mentioned. The statisticians and methodologists recommend do not report p-value alone, and reporting of effect size index with corresponding confidence interval is mandatory. However, many researchers do not pay attention to this and do not even interpret the p-value correctly. The present study intended, to provide an integrated instruction for reporting the statistical and clinical significance in medical sciences with the approach of hypothesis testing (reporting p-value).