9.4.19 Advantage of Confidence Intervals Over P values

Describes the Advantage of Confidence Intervals Over P Values

Confidence intervals and p values are two commonly used statistical tools in medical research to determine the significance of study findings. P values provide a measure of the probability of obtaining the observed results due to chance alone, whereas confidence intervals provide an estimate of the range of values that the true population parameter is likely to fall within. While p values are often used to determine statistical significance, they have limitations and can lead to misinterpretation of study results.

One advantage of confidence intervals over p values is that they provide more information about the precision and variability of study results. A confidence interval is a range of values around the point estimate that contains the true population parameter with a certain degree of certainty (usually 95%). This means that if the study were repeated multiple times, 95% of the confidence intervals would contain the true population parameter. Confidence intervals also provide information about the size and direction of the effect, making them more informative than a simple statement of statistical significance.

Another advantage of confidence intervals is that they allow for comparisons between groups or treatments. For example, if the confidence interval for a difference in means between two groups does not include zero, this suggests that there is a statistically significant difference between the two groups. Confidence intervals can also be used to compare the effect size of different treatments or interventions.

In contrast, p values only provide information about the probability of obtaining the observed results due to chance alone and do not provide information about the size or direction of the effect. Furthermore, p values can be influenced by sample size, which can lead to over-reliance on statistical significance rather than clinical significance.

In summary, confidence intervals provide a more informative and nuanced approach to interpreting study results compared to p values and should be used alongside p values to provide a more complete picture of study findings.

References:

1. Altman DG, Bland JM. Statistics notes: Confidence intervals. BMJ. 2000;320(7239):1529.
2. Goodman SN. Toward evidence-based medical statistics. 1: The P value fallacy. Ann Intern Med. 1999;130(12):995-1004.