An Overview of Statistical and Clinical Concepts: The Use and Interpretation of Confidence Interval

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. The majority of published research that involves statistical inference seems to make exclusive use of hypothesis testing, and summarize their findings only to statistical significance. Most importantly, p-value does not provide us with two crucial pieces of information: (1) the magnitude of an effect of interest, and (2) the precision of the estimate of the magnitude of that effect. Currently, most of the reputable journals did not accept statistical significance alone; and there has been increasing attention focused on the Effect size index, confidence limits along with clinical significant. However, there is no single guideline for reporting statistical and clinical significance, and there are inconsistencies between journals. The aim of this paper is to provide a correct and integrated instruction for reporting the statistical and clinical significance in medical sciences with the approach of estimation (reporting confidence interval).