Reporting Confidence Interval Instead of a Point Estimate a Review

In medical studies, investigators try to find out whether the difference of a measured outcome between groups is statistically significant by reporting a p value to reject or retain a null hypothesis. Such reporting of p value from comparisons of mean of the two groups has its limitations. Hypothesis testing does not take into account the variability of an observed sample statistic or its precision. Hence, it is important to quantify the uncertainty in this estimate by means of a confidence interval around the mean difference rather than reporting the mean difference simply as a point estimate. The confidence interval provides a range within which the true population value of the mean difference would lie with a certain degree of probability. Thus, a 95% confidence interval provides a range of mean differences that would contain the true population mean difference at least 95 times out of 100 repeated studies. The width of this range is determined by the sampling error or standard error. Greater the standard error, wider the range of the confidence interval. Conversely, a narrow range of confidence interval reflects a more precise study.