J Acad Nutr Diet. 2019 Dec;119(12):1993-2003. doi: 10.1016/j.jand.2019.07.009. Epub 2019 Oct 1.
This is part of a series of monographs on research design and analysis. The purpose of this article is to describe the purposes of and approach to conducting Bayesian decision making and analysis. Bayesian decision making involves basing decisions on the probability of a successful outcome, where this probability is informed by both prior information and new evidence the decision maker obtains. The statistical analysis that underlies the calculation of these probabilities is Bayesian analysis. In recent years, the Bayesian approach has been applied more commonly in both nutrition research and clinical decision making, and registered dietitian nutritionists would benefit from gaining a deeper understanding of this approach. This article provides a background of Bayesian decision making and analysis, and then presents applications of the approach in two different areas-medical diagnoses and nutrition policy research. It concludes with a description of how Bayesian decision making may be used in everyday life to allow each of us to appropriately weigh established beliefs and prior knowledge with new data and information in order to make well-informed and wise decisions.
这是一系列关于研究设计和分析的专论中的一部分。本文的目的是描述进行贝叶斯决策和分析的目的和方法。贝叶斯决策涉及根据成功结果的概率做出决策，而该概率是由先验信息和决策者获得的新证据共同提供的。为计算这些概率而进行的统计分析就是贝叶斯分析。近年来，贝叶斯方法在营养研究和临床决策制定中得到了更广泛的应用，注册营养师从更深入地了解这种方法中受益。本文提供了贝叶斯决策和分析的背景，然后介绍了该方法在两个不同领域——医学诊断和营养政策研究中的应用。最后，本文描述了贝叶斯决策如何在日常生活中使用，以便我们每个人都能适当地权衡既定的信念和先验知识与新的数据和信息，从而做出明智和明智的决策。
