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首页> 外文期刊>Journal of biopharmaceutical statistics >Bayesian sample size determination for longitudinal studies with continuous response based on different scientific questions of interest
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Bayesian sample size determination for longitudinal studies with continuous response based on different scientific questions of interest

机译：基于不同科学问题的不同科学问题，贝叶斯模拟纵向研究的纵向研究确定

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摘要

Longitudinal study designs are commonly applied in much scientific research, especially in the medical, social, and economic sciences. Longitudinal studies allow researchers to measure changes in each individual's responses over time and often have higher statistical power than cross-sectional studies. Choosing an appropriate sample size is a crucial step in a successful study. In longitudinal studies, because of the complexity of their design, including the selection of the number of individuals and the number of repeated measurements, sample size determination is less studied. This paper uses a simulation-based method to determine the sample size from a Bayesian perspective. For this purpose, several Bayesian criteria for sample size determination are used, of which the most important one is the Bayesian power criterion. We determine the sample size of a longitudinal study based on the scientific question of interest, by the choice of an appropriate model. Most of the methods of determining sample size are based on the definition of a single hypothesis. In this paper, in addition to using this method, we determine the sample size using multiple hypotheses. Using several examples, the proposed Bayesian methods are illustrated and discussed.
机译：纵向研究设计通常适用于大量科学研究，特别是在医学，社会和经济科学中。纵向研究允许研究人员随着时间的推移测量每个人的反应的变化，并且通常具有比横截面研究更高的统计功率。选择适当的样本大小是成功学习的关键步骤。在纵向研究中，由于其设计的复杂性，包括选择个体的数量和重复测量的数量，所以研究样本尺寸测定。本文采用基于仿真的方法来确定贝叶斯视角的样本大小。为此目的，使用用于样本尺寸确定的几个贝叶斯标准，其中最重要的是贝叶斯电力标准。通过选择适当的模型，我们根据感兴趣的科学问题确定纵向研究的样本量。确定样本大小的大多数方法基于单个假设的定义。在本文中，除了使用此方法之外，我们还使用多个假设确定样本大小。使用几个例子，说明和讨论了所提出的贝叶斯方法。

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