Morita S
Department of Anesthesia, Teikyo University School of Medicine, Ichihara Hospital.
Masui. 1993 Apr;42(4):585-92.
The data obtained from the clinical practice are not unanimous, because we cannot assume the patient condition constant. It is, however, important to estimate real time patient condition individually to make more appropriate decision on treatment. In the classical statistical approach to the estimation problem, the patient condition is, so to speak, viewed as an unknown constant, which does not change with time. This is a wrong assumption in the clinical world. In Bayesian statistics, an available datum or information prior to the event (prior probability) is used in the estimation process to obtain the posterior probability. Furthermore, datum or information gained in the clinical setting is considered as a fact instead of a random variable and is utilized to join itself with prior probability. In other word, in Bayesian statistics, estimation is changed to prediction. We utilize our subjective thinking in making decision in our daily practice of anesthesia. In fact, subjectivity is based on the beliefs or opinions, depending on the experience and information possessed by the anesthesiologist who is making the assessment. In Bayesian estimation, subjectivity, a measure of belief is incorporated as a prior probability which, I believe, is more flexible in dealing with the real world problems than any other statistical estimation.
从临床实践中获得的数据并不一致，因为我们不能假定患者状况保持不变。然而，重要的是要单独估计实时患者状况，以便对治疗做出更合适的决策。在经典的统计方法中，对于估计问题，患者状况可以说是被视为一个未知常数，不会随时间变化。这在临床领域是一个错误的假设。在贝叶斯统计学中，事件发生前可用的数据或信息（先验概率）在估计过程中用于获得后验概率。此外，在临床环境中获得的数据或信息被视为事实而非随机变量，并被用于与先验概率相结合。换句话说，在贝叶斯统计学中，估计变成了预测。在我们日常的麻醉实践中，我们利用主观思维来做决策。实际上，主观性基于信念或观点，这取决于进行评估的麻醉医生所拥有的经验和信息。在贝叶斯估计中，作为信念度量的主观性被纳入为先验概率，我认为，与任何其他统计估计相比，它在处理现实世界问题时更加灵活。
