Analysis of family‐wise error rates in statistical parametric mapping using random field theory
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[1] Karl J. Friston,et al. Assessing the significance of focal activations using their spatial extent , 1994, Human brain mapping.
[2] Dimitris Papadias,et al. Topological Inference , 1995, IJCAI.
[3] Karl J. Friston,et al. A unified statistical approach for determining significant signals in images of cerebral activation , 1996, Human brain mapping.
[4] Thomas E. Nichols,et al. Validating cluster size inference: random field and permutation methods , 2003, NeuroImage.
[5] Thomas E. Nichols,et al. Nonstationary cluster-size inference with random field and permutation methods , 2004, NeuroImage.
[6] Richard M. Leahy,et al. A comparison of random field theory and permutation methods for the statistical analysis of MEG data , 2005, NeuroImage.
[7] Michael B. Miller,et al. The principled control of false positives in neuroimaging. , 2009, Social cognitive and affective neuroscience.
[8] Thomas E. Nichols. Multiple testing corrections, nonparametric methods, and random field theory , 2012, NeuroImage.
[9] Anjali Krishnan,et al. Cluster-extent based thresholding in fMRI analyses: Pitfalls and recommendations , 2014, NeuroImage.
[10] Thomas E. Nichols,et al. Can parametric statistical methods be trusted for fMRI based group studies? , 2015, 1511.01863.
[11] Hans Knutsson,et al. Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates , 2016, Proceedings of the National Academy of Sciences.