Thomas R, Braganza A, Oommen L M, Muliyil J
Schell Eye Hospital, Department of Ophthalmology, Christian Medical College, Vellore, India.
Indian J Ophthalmol. 1997 Jun;45(2):119-23.
When considering the results of a study that reports one treatment to be better than another, what the practicing ophthalmologist really wants to know is the magnitude of the difference between treatment groups. If this difference is large enough, we may wish to offer the new treatment to our own patients. Even in well executed studies, differences between the groups (the sample) may be due to chance alone. The "p" value is the probability that the difference observed between the groups could have occurred purely due to chance. For many ophthalmologists assessing this difference means a simple look this "p" value to convince ourselves that a statistically significant result has indeed been obtained. Unfortunately traditional interpretation of a study based on the "p" value at an arbitrary cut-off (of 0.05 or any other value) limits our ability to fully appreciate the clinical implications of the results. In this article we use simple examples to illustrate the use of "confidence intervals" in examining precision and the applicability of study results (means, proportions and their comparisons). An attempt is made to demonstrate that the use of "confidence intervals" enables more complete evaluation of study results than with the "p" value.
在考量一项报告称某种治疗方法优于另一种治疗方法的研究结果时,执业眼科医生真正想知道的是治疗组之间差异的大小。如果这种差异足够大,我们可能会希望为自己的患者提供这种新的治疗方法。即使在执行良好的研究中,组间差异(样本)也可能仅仅是由于偶然因素造成的。“p值”是指两组之间观察到的差异纯粹由于偶然因素而出现的概率。对于许多眼科医生来说,评估这种差异意味着简单地查看这个“p值”,以确信我们确实获得了具有统计学意义的结果。不幸的是,基于任意临界值(0.05或任何其他值)的“p值”对研究进行传统解读,限制了我们充分理解结果临床意义的能力。在本文中,我们用简单的例子来说明“置信区间”在检验精度和研究结果(均值、比例及其比较)适用性方面的应用。我们试图证明,与“p值”相比,使用“置信区间”能够对研究结果进行更全面的评估。