Buchinsky Farrel J, Chadha Neil K
1 Allegheny General Hospital, Pittsburgh, Pennsylvania, USA.
2 Department of Otolaryngology/Head and Neck Surgery, Lewis Katz School of Medicine at Temple University, Philadelphia, Pennsylvania, USA.
Otolaryngol Head Neck Surg. 2017 Dec;157(6):915-918. doi: 10.1177/0194599817739260.
In biomedical research, it is imperative to differentiate chance variation from truth before we generalize what we see in a sample of subjects to the wider population. For decades, we have relied on null hypothesis significance testing, where we calculate P values for our data to decide whether to reject a null hypothesis. This methodology is subject to substantial misinterpretation and errant conclusions. Instead of working backward by calculating the probability of our data if the null hypothesis were true, Bayesian statistics allow us instead to work forward, calculating the probability of our hypothesis given the available data. This methodology gives us a mathematical means of incorporating our "prior probabilities" from previous study data (if any) to produce new "posterior probabilities." Bayesian statistics tell us how confidently we should believe what we believe. It is time to embrace and encourage their use in our otolaryngology research.
在生物医学研究中，在将我们在一组受试者样本中观察到的情况推广到更广泛的人群之前，必须区分偶然变异和真相。几十年来，我们一直依赖于零假设显著性检验，即计算数据的P值以决定是否拒绝零假设。这种方法容易受到大量错误解读和错误结论的影响。贝叶斯统计不是通过计算零假设为真时数据的概率来反向推导，而是允许我们正向推导，即根据现有数据计算假设的概率。这种方法为我们提供了一种数学手段，将先前研究数据（如果有的话）中的“先验概率”纳入进来，以产生新的“后验概率”。贝叶斯统计告诉我们应该对自己所相信的内容有多大的信心。是时候在我们的耳鼻喉科研究中接受并鼓励使用它们了。
