Type I and type II errors for Multiple Simultaneous Hypothesis Testing

Conditions for validity of re-sampling based

author: Violeta Calian, University of Iceland

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Top: Computer Science: Bioinformatics

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*Slides*
0:19	Conditions for validity
1:11	Violeta Calian
1:44	Outline
3:34	Problem,motivation and our solution
3:37	The problem
5:36	The problem
7:59	Strategies for hypotheses testing:
8:45	Motivation: gene expression levels microarray data 1
9:07	Motivation: gene expression levels microarray data 2
9:45	Motivation: gene expression levels microarray data 3
10:28	Our solution
12:04	Our solution
12:43	Error rates and error control
13:26	Error rate control
13:40	the comparison-wise error rate:
13:56	the experiment-wise error rate
14:12	the family-wise error rate
14:28	the False Discovery Rate
15:04	generalised family-wise error rates (gFWER)
15:20	The MCP principle
17:12	Consequences
17:57	More general form of Partitioning principle
18:13	More general form of Partitioning principle
18:33	More general form of Partitioning principle
18:46	More general form of Partitioning principle
19:08	Notations
19:17	Step-down Algorithm
21:06	Critical values cI have the property
21:45	msht07_calian_cfv_Page_28
23:11	Comments
24:15	Models. Test statistics. Critical values
24:46	Model 2: linear mixed effects model
25:12	Data
25:40	Test statistics
26:33	In practice5
27:09	Relation between the 2 versions
28:05	Theoretical results on maxT re-sampling distributions
29:13	Test statistic re-sampling distributions
29:18	Proposition 1
29:59	Proposition 2
32:14	re-sampling with replacement
33:17	re-sampling with replacement
33:25	b1, b2) permutations
33:45	b3) re-sampling
33:52	Simple examples
34:51	re-sampling residuals
35:21	maxT distributions
35:28	maxT distributions
36:28	Distribution of the vector test statistic
36:43	Distribution of the vector test statistic
37:59	Example 1
38:04	Example 1
39:01	Example 2
39:09	Example 2
39:54	Conclusions 1
40:26	Conclusions 2
41:09	Conclusions 3

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