层次分析matlab代码-bayesian-prevalence:人口患病率的贝叶斯推断

上传者: 38604951 | 上传时间: 2022-05-14 19:03:36 | 文件大小: 7.28MB | 文件类型: ZIP
层次分析matlab代码贝叶斯流行 贝叶斯推断人口患病率。 该软件包包括用于实现贝叶斯流行度推断的Matlab,Python和R的代码,如下所述: 人口患病率的贝叶斯推断RAA Ince,JW Kay和PG Schyns biorxiv: 考虑在心理学或神经影像学实验中的每个参与者,或在电生理学实验中记录的每个单个单元上执行统计测试(具有常见的假阳性率α)。 经过此第一级分析,我们可以仅使用三个数字来计算总体中此类测试的阳性结果阳性率的贝叶斯估计:测试总数n ,其中k为阳性,假阳性率(alpha) a 。 这些数字可以直接在函数调用中指定,也可以从表示在第一级应用各个测试的结果的变量中获取。 example_csv脚本提供了一个示例,该示例加载此第一级参与者内部有效数据并应用第二级患病率函数。 bayesprev_example.{m,R,py}在分层正态模型下模拟数据,在第一级上对每个参与者内的零进行t检验,在第二级上应用贝叶斯流行率推断。 用户可以调整此示例以加载自己的原始数据,将t检验替换为任何其他参与参与者的统计检验,或者直接加载指标变量的重要性并应用第二级检验(另请参见exa

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