Determining significance in neuroimaging studies using covariate-modulated false discovery rate
author:
Glenn Lawyer,
Faculty of Medicine, University of Oslo
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| Slides | |
| 0:02 | Advances in False Discovery Rate control applied in Neuroimaging |
| 0:29 | Outline |
| 1:23 | Outline |
| 1:31 | Voxel-based morphometry |
| 2:09 | Voxel-based morphometry |
| 2:18 | Vertex-based morphometry |
| 2:54 | Pial (outside) surface |
| 3:03 | White matter surface |
| 3:11 | Wireframe |
| 3:57 | Multiple comparisons |
| 4:04 | Multiple comparisons |
| 4:27 | Searching for interesting results |
| 5:06 | Outline |
| 5:58 | Definition |
| 6:06 | Markov Random Fields |
| 6:29 | Markov Random Fields |
| 6:57 | Permutation tests. |
| 7:25 | Weakness with blob-based methods |
| 8:03 | The original concept |
| 8:07 | The method |
| 8:11 | Graphical |
| 9:03 | FDR in practice |
| 9:25 | Outline |
| 9:34 | Local FDR |
| 9:44 | The model |
| 10:38 | The model, cont. |
| 11:02 | Definition |
| 11:11 | Definition |
| 11:30 | Why local? |
| 11:59 | Histogram of Z-scores |
| 13:09 | Requirements |
| 13:34 | Calculating the local FDR |
| 14:06 | The mixture f (z) |
| 14:12 | The mixture f (z) |
| 14:24 | The mixture f (z) |
| 14:58 | The numerator p0f0(z) |
| 15:24 | The numerator p0f0(z) |
| 15:52 | The numerator p0f0(z) |
| 16:49 | Outline |
| 17:03 | Covariate Modulated FDR |
| 17:38 | Microarray example |
| 18:48 | The model |
| 19:00 | The model |
| 19:08 | Definition |
| 19:22 | Definition |
| 19:35 | Definition |
| 20:17 | Compare to Local FDR |
| 20:42 | The model, II |
| 21:39 | Calculating cmFDR |
| 21:46 | Observation |
| 22:39 | Bin the covariates |
| 23:40 | Hyperpriors |
| 24:01 | posterior density |
| 24:36 | posterior density, cont. |
| 24:45 | Approximate |
| 25:11 | Approximate |
| 25:35 | cmFDR with one bin |
| 26:54 | Outline |
| 27:00 | Genetic variation and cortical thickness |
| 28:32 | BDNF -663 |
| 30:55 | cmFDR reasoning |
| 31:19 | Comparison |
| 31:53 | Comparison |
| 35:18 | Bibliography |
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