Multiple test procedures using an upper bound of the number of true hypotheses and their use for evaluating high-dimensional EEG data
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[1] S. Holm. A Simple Sequentially Rejective Multiple Test Procedure , 1979 .
[2] E. Spjøtvoll,et al. Plots of P-values to evaluate many tests simultaneously , 1982 .
[3] G. Hommel. Tests of the overall hypothesis for arbitrary dependence structures , 1983 .
[4] R. Simes,et al. An improved Bonferroni procedure for multiple tests of significance , 1986 .
[5] Gerhard Hommel,et al. Multiple Hypotheses Testing , 1993 .
[6] F. Craik,et al. Hemispheric encoding/retrieval asymmetry in episodic memory: positron emission tomography findings. , 1994, Proceedings of the National Academy of Sciences of the United States of America.
[7] Y. Benjamini,et al. Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .
[8] A. Dale,et al. Building memories: remembering and forgetting of verbal experiences as predicted by brain activity. , 1998, Science.
[9] S. Sarkar. Some probability inequalities for ordered $\rm MTP\sb 2$ random variables: a proof of the Simes conjecture , 1998 .
[10] Y. Benjamini,et al. On the Adaptive Control of the False Discovery Rate in Multiple Testing With Independent Statistics , 2000 .
[11] P Rappelsberger,et al. Long-range EEG synchronization during word encoding correlates with successful memory performance. , 2000, Brain research. Cognitive brain research.
[12] J. Troendle,et al. Stepwise normal theory multiple test procedures controlling the false discovery rate , 2000 .
[13] P Rappelsberger,et al. Theta synchronization predicts efficient memory encoding of concrete and abstract nouns , 2000, Neuroreport.
[14] R. Tibshirani,et al. Significance analysis of microarrays applied to the ionizing radiation response , 2001, Proceedings of the National Academy of Sciences of the United States of America.
[15] F. Turkheimer,et al. Estimation of the Number of “True” Null Hypotheses in Multivariate Analysis of Neuroimaging Data , 2001, NeuroImage.
[16] John D. Storey. A direct approach to false discovery rates , 2002 .
[17] Siu Hung Cheung,et al. A modified Benjamini–Hochberg multiple comparisons procedure for controlling the false discovery rate , 2002 .
[18] Joseph P. Romano,et al. Generalizations of the familywise error rate , 2005, math/0507420.
[19] Huey-miin Hsueh,et al. Comparison of Methods for Estimating the Number of True Null Hypotheses in Multiplicity Testing , 2003, Journal of biopharmaceutical statistics.
[20] M. J. van der Laan,et al. Augmentation Procedures for Control of the Generalized Family-Wise Error Rate and Tail Probabilities for the Proportion of False Positives , 2004, Statistical applications in genetics and molecular biology.
[21] John D. Storey,et al. Strong control, conservative point estimation and simultaneous conservative consistency of false discovery rates: a unified approach , 2004 .
[22] Sabine Weiss,et al. Multivariate tests for the evaluation of high-dimensional EEG data , 2004, Journal of Neuroscience Methods.
[23] S. Dudoit,et al. Multiple Testing. Part III. Procedures for Control of the Generalized Family-Wise Error Rate and Proportion of False Positives , 2004 .
[24] R. Simon,et al. Controlling the number of false discoveries: application to high-dimensional genomic data , 2004 .
[25] Per Broberg,et al. A comparative review of estimates of the proportion unchanged genes and the false discovery rate , 2005, BMC Bioinformatics.
[26] Peter Bühlmann,et al. Lower bounds for the number of false null hypotheses for multiple testing of associations under general dependence structures , 2005 .
[27] B. Lindqvist,et al. Estimating the proportion of true null hypotheses, with application to DNA microarray data , 2005 .
[28] S. Weiss,et al. New concepts of multiple tests and their use for evaluating high-dimensional EEG data , 2005, Journal of Neuroscience Methods.
[29] Y. Benjamini,et al. Adaptive linear step-up procedures that control the false discovery rate , 2006 .
[30] N. Meinshausen,et al. Estimating the proportion of false null hypotheses among a large number of independently tested hypotheses , 2005, math/0501289.
[31] Dan Nettleton,et al. Estimating the number of true null hypotheses from a histogram of p values , 2006 .