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MVPA Permutation Schemes: Permutation Testing for the Group Level

机译:MVPA排列方案:组级别的排列测试

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Permutation tests are widely used for significance testing in fMRI MVPA (multivariate pattern analysis) studies, but the precise way in which the tests are carried out varies, and test design is non-trivial because of complex, auto correlated, and stratified dataset structures. Previously, we described permutation tests for single-subject datasets, recommending adoption of "dataset-wise" schemes, in which examples are relabeled prior to cross-validation. Here, we extend that work by describing permutation schemes for group analyses: datasets with more than one participant. Group-level MVPA is most often performed with either cross-validation on the subjects or within-subjects cross-validation, each of which requires a different strategy for permutation testing, as illustrated here.
机译:置换测试已广泛用于功能性MRI MVPA(多变量模式分析)研究中的重要性测试,但是由于复杂,自相关和分层的数据集结构,因此进行测试的精确方式各不相同,并且测试设计非常重要。以前,我们描述了单对象数据集的置换测试,建议采用“按数据集”方案,在这种方案中,在交叉验证之前重新标记示例。在这里,我们通过描述用于组分析的置换方案来扩展这项工作:具有多个参与者的数据集。组级MVPA通常是通过对主题的交叉验证或对象内部的交叉验证来执行的,每个交叉验证都需要不同的排列测试策略,如此处所示。

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