publication . Article . Preprint . 2018

Powerful Statistical Inference for Nested Data Using Sufficient Summary Statistics.

Stefan Haufe;
Open Access English
  • Published: 19 Mar 2018 Journal: Frontiers in Human Neuroscience (issn: 1662-5161, Copyright policy)
  • Publisher: Frontiers Media S.A.
  • Country: Germany
Abstract
Comment: 17 pages, 5 figures
Subjects
free text keywords: 310 Sammlungen allgemeiner Statistiken, Stouffer's method, event-related potentials, hierarchical inference, group-level effect size, significance test, statistical power, sufficient summary statistic, inverse-variance-weighting, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571, Mathematics - Statistics Theory, Statistics - Methodology, Neuroscience, Methods, Biological Psychiatry, Behavioral Neuroscience, Neuropsychology and Physiological Psychology, Neurology, Psychiatry and Mental health
Related Organizations
Funded by
EC| HYPERSCANNING 2.0
Project
HYPERSCANNING 2.0
Hyperscanning 2.0 Analyses of Multimodal Neuroimaging Data: Concept, Methods and Applications
  • Funder: European Commission (EC)
  • Project Code: 625991
  • Funding stream: FP7 | SP3 | PEOPLE
68 references, page 1 of 5

Allefeld C.Görgen K.Haynes J.-D. (2016). Valid population inference for information-based imaging: from the second-level t-test to prevalence inference. NeuroImage 141, 378–392. 10.1016/j.neuroimage.2016.07.040 27450073 [OpenAIRE] [PubMed] [DOI]

Baldi P.Brunak S.Chauvin Y.Andersen C. A.Nielsen H. (2000). Assessing the accuracy of prediction algorithms for classification: an overview. Bioinformatics 16, 412–424. 10.1093/bioinformatics/16.5.412 10871264 [OpenAIRE] [PubMed] [DOI]

Batista-Brito R.Vinck M.Ferguson K.Chang J. T.Laubender D.Lur G.. (2017). Developmental dysfunction of vip interneurons impairs cortical circuits. Neuron 95, 884–895. 10.1016/j.neuron.2017.07.034 28817803 [OpenAIRE] [PubMed] [DOI]

Beckmann C. F.Jenkinson M.Smith S. M. (2003). General multilevel linear modeling for group analysis in fMRI. Neuroimage 20, 1052–1063. 10.1016/S1053-8119(03)00435-X 14568475 [PubMed] [DOI]

Borenstein M.Hedges L. V.Higgins J.Rothstein H. R. (2009). Introduction to Meta-Analysis. Wiley Online Library.

Brockwell S. E.Gordon I. R. (2001). A comparison of statistical methods for meta-analysis. Stat. Med. 20, 825–840. 10.1002/sim.650 11252006 [OpenAIRE] [PubMed] [DOI]

Card N. A. (2011). Applied Meta-Analysis for Social Science Research. New York, NY: Guilford Press.

Chen G.Saad Z. S.Britton J. C.Pine D. S.Cox R. W. (2013). Linear mixed-effects modeling approach to fMRI group analysis. Neuroimage 73, 176–190. 10.1016/j.neuroimage.2013.01.047 23376789 [OpenAIRE] [PubMed] [DOI]

Cochran W. G. (1954). The combination of estimates from different experiments. Biometrics 10, 101–129. 10.2307/3001666 [OpenAIRE] [DOI]

Dähne S.Bießman F.Samek W.Haufe S.Goltz D.Gundlach C. (2015). Multivariate machine learning methods for fusing functional multimodal neuroimaging data. Proc. IEEE 103, 1507–1530. 10.1109/JPROC.2015.2425807 [OpenAIRE] [DOI]

DerSimonian R.Laird N. (1986). Meta-analysis in clinical trials. Control. Clin. Trials 7, 177–188. 10.1016/0197-2456(86)90046-2 3802833 [OpenAIRE] [PubMed] [DOI]

Efron B. (1982). The Jackknife, the Bootstrap and Other Resampling Plans, Vol. 38 SIAM.

Fawcett T. (2006). An introduction to ROC analysis. Patt. Recogn. Lett. 27, 861–874. 10.1016/j.patrec.2005.10.010 [OpenAIRE] [DOI]

Field A. P. (2003). The problems in using fixed-effects models of meta-analysis on real-world data. Unders. Stat. Stat. Issues Psychol. Educ. Soc. Sci. 2, 105–124. 10.1207/S15328031US0202_02 [DOI]

Fisher R. A. (1915). Frequency distribution of the values of the correlation coefficient in samples from an indefinitely large population. Biometrika 10, 507–521. 10.2307/2331838 [OpenAIRE] [DOI]

68 references, page 1 of 5
Abstract
Comment: 17 pages, 5 figures
Subjects
free text keywords: 310 Sammlungen allgemeiner Statistiken, Stouffer's method, event-related potentials, hierarchical inference, group-level effect size, significance test, statistical power, sufficient summary statistic, inverse-variance-weighting, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571, Mathematics - Statistics Theory, Statistics - Methodology, Neuroscience, Methods, Biological Psychiatry, Behavioral Neuroscience, Neuropsychology and Physiological Psychology, Neurology, Psychiatry and Mental health
Related Organizations
Funded by
EC| HYPERSCANNING 2.0
Project
HYPERSCANNING 2.0
Hyperscanning 2.0 Analyses of Multimodal Neuroimaging Data: Concept, Methods and Applications
  • Funder: European Commission (EC)
  • Project Code: 625991
  • Funding stream: FP7 | SP3 | PEOPLE
68 references, page 1 of 5

Allefeld C.Görgen K.Haynes J.-D. (2016). Valid population inference for information-based imaging: from the second-level t-test to prevalence inference. NeuroImage 141, 378–392. 10.1016/j.neuroimage.2016.07.040 27450073 [OpenAIRE] [PubMed] [DOI]

Baldi P.Brunak S.Chauvin Y.Andersen C. A.Nielsen H. (2000). Assessing the accuracy of prediction algorithms for classification: an overview. Bioinformatics 16, 412–424. 10.1093/bioinformatics/16.5.412 10871264 [OpenAIRE] [PubMed] [DOI]

Batista-Brito R.Vinck M.Ferguson K.Chang J. T.Laubender D.Lur G.. (2017). Developmental dysfunction of vip interneurons impairs cortical circuits. Neuron 95, 884–895. 10.1016/j.neuron.2017.07.034 28817803 [OpenAIRE] [PubMed] [DOI]

Beckmann C. F.Jenkinson M.Smith S. M. (2003). General multilevel linear modeling for group analysis in fMRI. Neuroimage 20, 1052–1063. 10.1016/S1053-8119(03)00435-X 14568475 [PubMed] [DOI]

Borenstein M.Hedges L. V.Higgins J.Rothstein H. R. (2009). Introduction to Meta-Analysis. Wiley Online Library.

Brockwell S. E.Gordon I. R. (2001). A comparison of statistical methods for meta-analysis. Stat. Med. 20, 825–840. 10.1002/sim.650 11252006 [OpenAIRE] [PubMed] [DOI]

Card N. A. (2011). Applied Meta-Analysis for Social Science Research. New York, NY: Guilford Press.

Chen G.Saad Z. S.Britton J. C.Pine D. S.Cox R. W. (2013). Linear mixed-effects modeling approach to fMRI group analysis. Neuroimage 73, 176–190. 10.1016/j.neuroimage.2013.01.047 23376789 [OpenAIRE] [PubMed] [DOI]

Cochran W. G. (1954). The combination of estimates from different experiments. Biometrics 10, 101–129. 10.2307/3001666 [OpenAIRE] [DOI]

Dähne S.Bießman F.Samek W.Haufe S.Goltz D.Gundlach C. (2015). Multivariate machine learning methods for fusing functional multimodal neuroimaging data. Proc. IEEE 103, 1507–1530. 10.1109/JPROC.2015.2425807 [OpenAIRE] [DOI]

DerSimonian R.Laird N. (1986). Meta-analysis in clinical trials. Control. Clin. Trials 7, 177–188. 10.1016/0197-2456(86)90046-2 3802833 [OpenAIRE] [PubMed] [DOI]

Efron B. (1982). The Jackknife, the Bootstrap and Other Resampling Plans, Vol. 38 SIAM.

Fawcett T. (2006). An introduction to ROC analysis. Patt. Recogn. Lett. 27, 861–874. 10.1016/j.patrec.2005.10.010 [OpenAIRE] [DOI]

Field A. P. (2003). The problems in using fixed-effects models of meta-analysis on real-world data. Unders. Stat. Stat. Issues Psychol. Educ. Soc. Sci. 2, 105–124. 10.1207/S15328031US0202_02 [DOI]

Fisher R. A. (1915). Frequency distribution of the values of the correlation coefficient in samples from an indefinitely large population. Biometrika 10, 507–521. 10.2307/2331838 [OpenAIRE] [DOI]

68 references, page 1 of 5
Powered by OpenAIRE Research Graph
Any information missing or wrong?Report an Issue