Non-parametric combination and related permutation tests for neuroimaging

In this work, we show how permutation methods can be applied to combination analyses such as those that include multiple imaging modalities, multiple data acquisitions of the same modality, or simply multiple hypotheses on the same data. Using the well‐known definition of union‐intersection tests an...

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Published in	Human brain mapping Vol. 37; no. 4; pp. 1486 - 1511
Main Authors	Winkler, Anderson M., Webster, Matthew A., Brooks, Jonathan C., Tracey, Irene, Smith, Stephen M., Nichols, Thomas E.
Format	Journal Article Web Resource
Language	English
Published	United States Blackwell Publishing Ltd 01.04.2016 John Wiley & Sons, Inc John Wiley & Sons John Wiley and Sons Inc
Subjects	Algorithms Cerebral Cortex - physiology Cerebral Cortex - physiopathology Cerebral Cortex/physiology/physiopathology conjunctions general linear model Humans Image Processing, Computer-Assisted - methods Magnetic Resonance Imaging - methods multiple testing Neuroimaging - methods non-parametric combination Pain Measurement - methods permutation tests Physical, chemical, mathematical & earth Sciences Physique, chimie, mathématiques & sciences de la terre Statistics, Nonparametric non-parametric combination conjunctions multiple testing general linear model permutation tests
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Abstract	In this work, we show how permutation methods can be applied to combination analyses such as those that include multiple imaging modalities, multiple data acquisitions of the same modality, or simply multiple hypotheses on the same data. Using the well‐known definition of union‐intersection tests and closed testing procedures, we use synchronized permutations to correct for such multiplicity of tests, allowing flexibility to integrate imaging data with different spatial resolutions, surface and/or volume‐based representations of the brain, including non‐imaging data. For the problem of joint inference, we propose and evaluate a modification of the recently introduced non‐parametric combination (NPC) methodology, such that instead of a two‐phase algorithm and large data storage requirements, the inference can be performed in a single phase, with reasonable computational demands. The method compares favorably to classical multivariate tests (such as MANCOVA), even when the latter is assessed using permutations. We also evaluate, in the context of permutation tests, various combining methods that have been proposed in the past decades, and identify those that provide the best control over error rate and power across a range of situations. We show that one of these, the method of Tippett, provides a link between correction for the multiplicity of tests and their combination. Finally, we discuss how the correction can solve certain problems of multiple comparisons in one‐way ANOVA designs, and how the combination is distinguished from conjunctions, even though both can be assessed using permutation tests. We also provide a common algorithm that accommodates combination and correction. Hum Brain Mapp 37:1486‐1511, 2016. © 2016 Wiley Periodicals, Inc.
AbstractList	In this work, we show how permutation methods can be applied to combination analyses such as those that include multiple imaging modalities, multiple data acquisitions of the same modality, or simply multiple hypotheses on the same data. Using the well-known definition of union-intersection tests and closed testing procedures, we use synchronized permutations to correct for such multiplicity of tests, allowing flexibility to integrate imaging data with different spatial resolutions, surface and/or volume-based representations of the brain, including non-imaging data. For the problem of joint inference, we propose and evaluate a modification of the recently introduced non-parametric combination (NPC) methodology, such that instead of a two-phase algorithm and large data storage requirements, the inference can be performed in a single phase, with reasonable computational demands. The method compares favorably to classical multivariate tests (such as MANCOVA), even when the latter is assessed using permutations. We also evaluate, in the context of permutation tests, various combining methods that have been proposed in the past decades, and identify those that provide the best control over error rate and power across a range of situations. We show that one of these, the method of Tippett, provides a link between correction for the multiplicity of tests and their combination. Finally, we discuss how the correction can solve certain problems of multiple comparisons in one-way ANOVA designs, and how the combination is distinguished from conjunctions, even though both can be assessed using permutation tests. We also provide a common algorithm that accommodates combination and correction. Abstract In this work, we show how permutation methods can be applied to combination analyses such as those that include multiple imaging modalities, multiple data acquisitions of the same modality, or simply multiple hypotheses on the same data. Using the well‐known definition of union‐intersection tests and closed testing procedures, we use synchronized permutations to correct for such multiplicity of tests, allowing flexibility to integrate imaging data with different spatial resolutions, surface and/or volume‐based representations of the brain, including non‐imaging data. For the problem of joint inference, we propose and evaluate a modification of the recently introduced non‐parametric combination (NPC) methodology, such that instead of a two‐phase algorithm and large data storage requirements, the inference can be performed in a single phase, with reasonable computational demands. The method compares favorably to classical multivariate tests (such as MANCOVA), even when the latter is assessed using permutations. We also evaluate, in the context of permutation tests, various combining methods that have been proposed in the past decades, and identify those that provide the best control over error rate and power across a range of situations. We show that one of these, the method of Tippett, provides a link between correction for the multiplicity of tests and their combination. Finally, we discuss how the correction can solve certain problems of multiple comparisons in one‐way ANOVA designs, and how the combination is distinguished from conjunctions, even though both can be assessed using permutation tests. We also provide a common algorithm that accommodates combination and correction. Hum Brain Mapp 37:1486‐1511, 2016 . © 2016 Wiley Periodicals, Inc. In this work, we show how permutation methods can be applied to combination analyses such as those that include multiple imaging modalities, multiple data acquisitions of the same modality, or simply multiple hypotheses on the same data. Using the well-known definition of union-intersection tests and closed testing procedures, we use synchronized permutations to correct for such multiplicity of tests, allowing flexibility to integrate imaging data with different spatial resolutions, surface and/or volume-based representations of the brain, including non-imaging data. For the problem of joint inference, we propose and evaluate a modification of the recently introduced non-parametric combination (NPC) methodology, such that instead of a two-phase algorithm and large data storage requirements, the inference can be performed in a single phase, with reasonable computational demands. The method compares favorably to classical multivariate tests (such as MANCOVA), even when the latter is assessed using permutations. We also evaluate, in the context of permutation tests, various combining methods that have been proposed in the past decades, and identify those that provide the best control over error rate and power across a range of situations. We show that one of these, the method of Tippett, provides a link between correction for the multiplicity of tests and their combination. Finally, we discuss how the correction can solve certain problems of multiple comparisons in one-way ANOVA designs, and how the combination is distinguished from conjunctions, even though both can be assessed using permutation tests. We also provide a common algorithm that accommodates combination and correction. Hum Brain Mapp 37:1486-1511, 2016. © 2016 Wiley Periodicals, Inc. In this work, we show how permutation methods can be applied to combination analyses such as those that include multiple imaging modalities, multiple data acquisitions of the same modality, or simply multiple hypotheses on the same data. Using the well‐known definition of union‐intersection tests and closed testing procedures, we use synchronized permutations to correct for such multiplicity of tests, allowing flexibility to integrate imaging data with different spatial resolutions, surface and/or volume‐based representations of the brain, including non‐imaging data. For the problem of joint inference, we propose and evaluate a modification of the recently introduced non‐parametric combination (NPC) methodology, such that instead of a two‐phase algorithm and large data storage requirements, the inference can be performed in a single phase, with reasonable computational demands. The method compares favorably to classical multivariate tests (such as MANCOVA), even when the latter is assessed using permutations. We also evaluate, in the context of permutation tests, various combining methods that have been proposed in the past decades, and identify those that provide the best control over error rate and power across a range of situations. We show that one of these, the method of Tippett, provides a link between correction for the multiplicity of tests and their combination. Finally, we discuss how the correction can solve certain problems of multiple comparisons in one‐way ANOVA designs, and how the combination is distinguished from conjunctions, even though both can be assessed using permutation tests. We also provide a common algorithm that accommodates combination and correction. Hum Brain Mapp 37:1486‐1511, 2016 . © 2016 Wiley Periodicals, Inc. In this work, we show how permutation methods can be applied to combination analyses such as those that include multiple imaging modalities, multiple data acquisitions of the same modality, or simply multiple hypotheses on the same data. Using the well-known definition of union-intersection tests and closed testing procedures, we use synchronized permutations to correct for such multiplicity of tests, allowing flexibility to integrate imaging data with different spatial resolutions, surface and/or volume-based representations of the brain, including non-imaging data. For the problem of joint inference, we propose and evaluate a modification of the recently introduced non-parametric combination (NPC) methodology, such that instead of a two-phase algorithm and large data storage requirements, the inference can be performed in a single phase, with reasonable computational demands. The method compares favorably to classical multivariate tests (such as MANCOVA), even when the latter is assessed using permutations. We also evaluate, in the context of permutation tests, various combining methods that have been proposed in the past decades, and identify those that provide the best control over error rate and power across a range of situations. We show that one of these, the method of Tippett, provides a link between correction for the multiplicity of tests and their combination. Finally, we discuss how the correction can solve certain problems of multiple comparisons in one-way ANOVA designs, and how the combination is distinguished from conjunctions, even though both can be assessed using permutation tests. We also provide a common algorithm that accommodates combination and correction. Hum Brain Mapp 37:1486-1511, 2016. copyright 2016 Wiley Periodicals, Inc.
Author	Winkler, Anderson M. Webster, Matthew A. Smith, Stephen M. Brooks, Jonathan C. Tracey, Irene Nichols, Thomas E.
AuthorAffiliation	1 Oxford Centre for Functional MRI of the Brain University of Oxford Oxford United Kingdom 3 Department of Statistics & Warwick Manufacturing Group University of Warwick Coventry United Kingdom 2 Clinical Research and Imaging Centre, University of Bristol Bristol United Kingdom
AuthorAffiliation_xml	– name: 2 Clinical Research and Imaging Centre, University of Bristol Bristol United Kingdom – name: 1 Oxford Centre for Functional MRI of the Brain University of Oxford Oxford United Kingdom – name: 3 Department of Statistics & Warwick Manufacturing Group University of Warwick Coventry United Kingdom
Author_xml	– sequence: 1 givenname: Anderson M. surname: Winkler fullname: Winkler, Anderson M. email: winkler@fmrib.ox.ac.uk organization: Oxford Centre for Functional MRI of the Brain, University of Oxford, Oxford, United Kingdom – sequence: 2 givenname: Matthew A. surname: Webster fullname: Webster, Matthew A. organization: Oxford Centre for Functional MRI of the Brain, University of Oxford, Oxford, United Kingdom – sequence: 3 givenname: Jonathan C. surname: Brooks fullname: Brooks, Jonathan C. organization: Clinical Research and Imaging Centre, University of Bristol, Bristol, United Kingdom – sequence: 4 givenname: Irene surname: Tracey fullname: Tracey, Irene organization: Oxford Centre for Functional MRI of the Brain, University of Oxford, Oxford, United Kingdom – sequence: 5 givenname: Stephen M. surname: Smith fullname: Smith, Stephen M. organization: Oxford Centre for Functional MRI of the Brain, University of Oxford, Oxford, United Kingdom – sequence: 6 givenname: Thomas E. surname: Nichols fullname: Nichols, Thomas E. organization: Oxford Centre for Functional MRI of the Brain, University of Oxford, Oxford, United Kingdom
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/26848101$$D View this record in MEDLINE/PubMed
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Cites_doi	10.1111/j.1467-842X.1961.tb00058.x 10.1002/pst.210 10.1214/aoms/1177729029 10.1016/j.neuroimage.2013.09.071 10.1016/j.neuroimage.2005.03.041 10.1016/j.csda.2003.11.020 10.1016/j.neuroimage.2005.01.013 10.2307/2529826 10.1007/BF02294069 10.2307/3001913 10.1186/1471-2105-14-368 10.1111/j.1541-0420.2007.00984.x 10.1159/000288391 10.1093/biostatistics/kxj009 10.1002/sim.3569 10.1093/biomet/63.3.655 10.1191/0962280203sm341ra 10.1016/j.neuroimage.2004.04.035 10.1214/aoms/1177732979 10.1080/00223980.1972.9924813 10.1214/aoms/1177728599 10.2307/2281130 10.1111/j.1420-9101.2011.02297.x 10.1038/jcbfm.1988.111 10.1016/j.neuroimage.2014.01.060 10.1016/j.neuroimage.2013.12.058 10.1214/10-AOAS393 10.1080/10485250902807407 10.1002/9780470743386 10.1080/01621459.1986.10478341 10.1037/0033-2909.85.1.185 10.1111/j.2517-6161.1995.tb02031.x 10.1080/01621459.1986.10478364 10.1007/978-1-4757-3847-6 10.1126/science.164.3878.444 10.2307/2532163 10.1093/biomet/24.3-4.471 10.1111/j.1420-9101.2005.00917.x 10.1111/j.1420-9101.2010.02226.x 10.1002/9780470689516 10.1007/978-1-4899-7180-7 10.1002/gepi.0042 10.1002/9780470316672 10.1016/S0167-7152(02)00310-3 10.1093/biomet/30.1-2.180 10.1126/science.1067176 10.1016/j.neuroimage.2015.10.090 10.1016/j.neuroimage.2014.06.027 10.1080/01621459.1927.10502953 10.1093/biomet/25.3-4.379 10.1038/nn.3832 10.1016/j.neuroimage.2012.12.055 10.1016/j.jtbi.2011.01.029 10.1016/j.neuroimage.2004.09.040 10.1006/nimg.2001.1037 10.1037/h0059111 10.1002/bimj.200710456 10.1214/aoms/1177698861 10.22237/jmasm/1320120240 10.1016/j.neuroimage.2014.05.018 10.1007/BF02589052 10.1080/01621459.1979.10481035 10.1198/016214504000000089 10.1037/11774-000 10.1207/s15327906mbr2902_2 10.1016/S0140-6736(86)90837-8 10.1214/09-AOS697 10.1038/jcbfm.1991.122 10.1016/j.neuroimage.2005.10.052 10.1177/0962280211403659 10.1037/1082-989X.5.4.496 10.1523/JNEUROSCI.22-07-02748.2002 10.1002/gepi.10264 10.1016/j.neuroimage.2008.03.061 10.2307/1267823 10.2307/2283989 10.1016/j.neuroimage.2012.04.014 10.1080/03610920600694496 10.2307/2987655 10.1016/j.neuroimage.2004.12.005 10.1006/nimg.2002.1107 10.1002/hbm.22164
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Copyright	2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. 2016 Wiley Periodicals, Inc.
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Keywords	non-parametric combination conjunctions multiple testing general linear model permutation tests
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License	Attribution 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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References	Hochberg Y, Tamhane AC (1987): Multiple Comparison Procedures. New York, NY: Wiley. Owen AB (2009): Karl Pearson's meta-analysis revisited. Ann Stat 37:3867-3892. Chen Z (2011): Is the weighted z-test the best method for combining probabilities from independent tests? J Evol Biol 24:926-930. Marcus R, Peritz E, Gabriel KR (1976): On closed testing procedures with special reference to ordered analysis of variance. Biometrika 63:655. Brombin C, Midena E, Salmaso L (2013): Robust non-parametric tests for complex-repeated measures problems in ophthalmology. Stat Meth Med Res 22:643-660. Good IJ (1955): On the weighted combination of significance tests. J R Stat Soc Series B 17:264-265. Pillai KCS (1955): Some new test criteria in multivariate analysis. The Annals of Mathematical Statistics 26:117-121. Berger RL (1982): Multiparameter hypothesis testing and acceptance sampling. Technometrics 24:295-300. Hsu JC (1996): Multiple Comparison: Theory and Methods. Boca Raton, FL: Chapman & Hall/CRC. Hayasaka S, Du A-T, Duarte A, Kornak J, Jahng G-H, Weiner MW, Schuff N (2006): A non-parametric approach for co-analysis of multi-modal brain imaging data: Application to alzheimer's disease. NeuroImage 30:768-779. Dudbridge F, Koeleman BPC (2003): Rank truncated product of P-values, with application to genomewide association scans. Gene Epidemiol 25:360-366. Oosterhoff J (1969): Combination of One-Sided Statistical Tests. Amsterdam, The Netherlands: Mathematisch Centrum. Chang L-C, Lin H-M, Sibille E, Tseng GC (2013): Meta-analysis methods for combining multiple expression profiles: Comparisons, statistical characterization and an application guideline. BMC Bioinformatics 14:368. Bland JM, Altman DG (1986): Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 327:307-310. Lehmann EL, Romano JP (2005): Testing Statistical Hypotheses, 3rd ed. New York, NY: Springer. Pesarin F (1992): A resampling procedure for nonparametric combination of several dependent tests. J Italian Stat Soc 1:87-101. Jiang B, Zhang X, Zuo Y, Kang G (2011): A powerful truncated tail strength method for testing multiple null hypotheses in one dataset. J Theoretical Biol 277:67-73. Friston KJ, Frith CD, Liddle PF, Frackowiak RS (1991): Comparing functional (PET) images: The assessment of significant change. J Cereb Blood Flow Metab 11:690-699. Tippett LHC (1931): The Methods of Statistics. London: Williams; Northgate. Edgington ES (1972): An additive method for combining probability values from independent experiments. J Psychol 80:351-363. Efron B (2004): Large-scale simultaneous hypothesis testing. J Am Stat Assoc 99:96-104. Blair RC, Higgins JJ, Karniski W, Kromrey JD (1994): A study of multivariate permutation tests which may replace Hotelling's T2 test in prescribed circumstances. Multivariate Behav Res 29:141-163. Winkler AM, Ridgway GR, Webster MA, Smith SM, Nichols TE (2014): Permutation inference for the general linear model. NeuroImage 92:381-397. Pantazis D, Nichols TE, Baillet S, Leahy RM (2005): A comparison of random field theory and permutation methods for the statistical analysis of MEG data. Neuroimage 25:383-394. Rosenthal R (1978): Combining results of independent studies. Psychol Bull 85:185-193. Li J, Tseng GC (2011): An adaptively weighted statistic for detecting differential gene expression when combining multiple transcriptomic studies. Ann Appl Stat 5:994-1019. Wilkinson B (1951): A statistical consideration in psychological research. Psychol Bull 48:156-158. Westfall PH, Troendle JF (2008): Multiple testing with minimal assumptions. Biom J 50:745-755. Berk RH, Cohen A (1979): Asymptotically optimal methods of combining tests. J Am Stat Assoc 74:812-814. Brown MB (1975): A method for combining non-independent, one-sided tests of significance. Biometrics 31:987-992. Smith SM, Nichols TE (2009): Threshold-free cluster enhancement: Addressing problems of smoothing, threshold dependence and localisation in cluster inference. Neuroimage 44:83-98. Lipták T (1958): On the combination of independent tests. A Magyar Tudományos Akadémia Matematikai Kutató Intézetének Közlémenyei 3:171-197. Roy M, Shohamy D, Daw N, Jepma M, Wimmer GE, Wager TD (2014): Representation of aversive prediction errors in the human periaqueductal gray. Nat Neurosci 17:1607-1612. Kost JT, McDermott MP (2002): Combining dependent p-values. Stat Probab Lett 60:183-190. Šidák Z (1967): Rectangular confidence regions for the means of multivariate normal distributions. J Am Stat Assoc 62:626-633. Taylor J, Tibshirani R (2006): A tail strength measure for assessing the overall univariate significance in a dataset. Biostatistics 7:167-181. Won S, Morris N, Lu Q, Elston RC (2009): Choosing an optimal method to combine p-values. Stat Med 28:1537-1553. Petrovic P, Kalso E, Petersson KM, Ingvar M (2002): Placebo and opioid analgesia-Imaging a shared neuronal network. Science 295:1737-1740. Calhoun VD, Sui J (2016): Multimodal fusion of brain imaging data: A key to finding the missing link(s) in complex mental illness. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging (in press). doi:10.1016/j.bpsc.2015.12.005. Nichols T, Hayasaka S (2003): Controlling the familywise error rate in functional neuroimaging: A comparative review. Stat Meth Med Res 12:419-446. Wilks SS (1932): Certain generalizations in the analysis of variance. Biometrika 24:471-494. Uludağ K, Roebroeck A (2014): General overview on the merits of multimodal neuroimaging data fusion. NeuroImage 102:3-10. Brooks JCW, Zambreanu L, Godinez A, Craig ADB, Tracey I (2005): Somatotopic organisation of the human insula to painful heat studied with high resolution functional imaging. NeuroImage 27:201-209. Wu SS (2006): Combining univariate tests for multivariate location problem. Commun Stat 35:1483-1494. Timm NH (2002): Applied Multivariate Analysis. New York: Springer. Christensen R (2001): Advanced Linear Modelling, 2nd ed. New York, USA: Springer. Friston KJ, Penny WD, Glaser DE (2005): Conjunction revisited. NeuroImage 25:661-667. Pearson K (1933): On a method of determining whether a sample of size n supposed to have been drawn from a parent population having a known probability integral has probably been drawn at random. Biometrika 25:379-410. Anderson TW (2003): An Introduction to Multivariate Statistical Analysis. Hoboken, NJ: Wiley. Scheffé H (1959): The Analysis of Variance. New York: Wiley. Holm S (1979): A simple sequentially rejective multiple test procedure. Scand J Stat 6:65-70. Westberg M (1985): Combining independent statistical tests. Statistician 34:287-296. Wilson EB (1927): Probable inference, the law of succession, and statistical inference. J Am Stat Assoc 22:209-212. Roy SN (1953): On a heuristic method of test construction and its use in multivariate analysis. Ann Math Stat 24:220-238. Zhu D, Zhang T, Jiang X, Hu X, Chen H, Yang N, Lv J, Han J, Guo L, Liu T (2014): Fusing DTI and fMRI data: A survey of methods and applications. NeuroImage 102:184-191. Hayasaka S, Nichols TE (2004): Combining voxel intensity and cluster extent with permutation test framework. NeuroImage 23:54-63. Benjamini Y, Hochberg Y (1995): Controlling the false discovery rate: A practical and powerful approach to multiple testing. J R Stat Soc Ser B 57:289-300. David FN (1934): On the Pλn test for randomness: Remarks, further illustration, and table of Pλn for given values of -log10λn. Biometrika 26:1. 1−11. Nichols T, Brett M, Andersson J, Wager T, Poline J-B (2005): Valid conjunction inference with the minimum statistic. NeuroImage 25:653-660. Winer BJ (1962): Statistical Principles in Experimental Design. New York: McGraw-Hill. Lazar NA, Luna B, Sweeney JA, Eddy WF (2002): Combining brains: A survey of methods for statistical pooling of information. NeuroImage 16:538-550. Johnson RA, Wichern DW (2007): Applied Multivariate Statistical Analysis, 6th ed. Upper Sadle River, NJ: Pearson Prentice Hall. Pesarin F (1990): On a nonparametric combination method for dependent permutation tests with applications. Psychother Psychosom 54:172-179. Tukey JW (1949): Comparing individual means in the analysis of variance. Biometrics 5:99-114. Genovese CR, Lazar NA, Nichols T (2002): Thresholding of statistical maps in functional neuroimaging using the false discovery rate. NeuroImage 15:870-878. Lancaster HO (1961): The combination of probabilities: An application of orthonormal functions. Aus J Stat 3:20-33. Pesarin F (2001): Multivariate Permutation Tests, with Applications in Biostatistics. West Sussex, England, UK: Wiley. Licata SC, Nickerson LD, Lowen SB, Trksak GH, MacLean RR, Lukas SE (2013): The hypnotic zolpidem increases the synchrony of BOLD signal fluctuations in widespread brain networks during a resting paradigm. NeuroImage 70:211-222. Pesarin F, Salmaso L (2010b): Finite-sample consistency of combination-based permutation tests with application to repeated measures designs. J Nonparametr Stat 22:669-684. Stouffer SA, Suchman EA, DeVinney LC, Star SA Jr, Robin MW (1949): The American Soldier: Adjustment During Army Life (Vol. 1). Princeton, NJ: Princeton University Press. Draper D, Gaver DP, Goel PK, Greenhouse JB, Hedges LV, Morris CN, Waternaux C (1992): Combining information: Statistical issues and opportunities for research. Washington, DC: National Academy Press. Hall P, Wilson SR (1991): Two guidelines for bootstrap hypothesis testing. Biometrics 47:757-762. Hotelling H (1931): The generalization of Student's ratio. Ann Math Stat 2:360-378. Fox PT, Mintun MA, Reiman EM, Raichle ME (1988): Enhanced detection of focal brain responses using intersubject averaging and change-distribution analysis of subtracted PET images. J Cerebral Blood Flow Metab 8:642-653. Chen G, Adleman NE, Saad ZS, Leibenluft E, Cox RW (2014): Applications of multivariate modeling to neuroimaging group analysis: A comprehensive alternative to univariate general linear model. NeuroImage 99:571-588. Tracey I, Ploghaus A, Gati JS, Clare S, Smith S, Menon RS, Matthews PM 2002; 16 2009; 44 1976; 63 2002; 15 1990; 54 2006; 30 2013; 22 2000; 5 2006; 35 1991; 11 1934; 26 2004; 23 1967; 62 1949; 5 1932 1931 2011; 10 1972; 80 2013; 70 1954; 49 2002; 60 1994; 29 1979; 74 2005; 27 2011; 277 1979 1933; 25 2005; 25 2003; 12 1955; 17 1982; 24 1986; 81 2013; 14 1991; 47 2001 1961; 3 1987 1979; 6 2011; 24 2008; 64 2014; 17 1958; 3 1953; 24 1949 1992; 1 2014; 99 2012; 62 1955; 26 2014; 92 2014; 91 1986; 51 2002; 295 1995; 57 2004; 47 2009 2006; 7 1996 2007 2006; 5 1951 1975; 31 2005 1993 2003 1992 1951; 48 2002 2008; 50 2011; 5 1959 2009; 28 1986; 327 1969; 164 2004; 99 1927; 22 1978; 85 1988; 8 2002; 22 2003; 25 1932; 24 2014; 35 2010a 1962 2016 2015 2013 1967; 38 1985; 34 2010b; 22 1938; 30 2005; 18 1931; 2 1969 2009; 37 2014; 102 e_1_2_13_24_1 e_1_2_13_47_1 e_1_2_13_20_1 e_1_2_13_66_1 e_1_2_13_101_1 e_1_2_13_43_1 e_1_2_13_62_1 e_1_2_13_81_1 e_1_2_13_92_1 e_1_2_13_96_1 e_1_2_13_17_1 e_1_2_13_13_1 e_1_2_13_36_1 e_1_2_13_59_1 e_1_2_13_32_1 e_1_2_13_55_1 e_1_2_13_78_1 e_1_2_13_51_1 e_1_2_13_74_1 David FN (e_1_2_13_22_1) 1934; 26 Oosterhoff J (e_1_2_13_61_1) 1969 e_1_2_13_70_1 Johnson RA (e_1_2_13_44_1) 2007 Lehmann EL (e_1_2_13_50_1) 2005 e_1_2_13_4_1 e_1_2_13_88_1 e_1_2_13_29_1 e_1_2_13_25_1 e_1_2_13_48_1 e_1_2_13_100_1 e_1_2_13_21_1 e_1_2_13_104_1 e_1_2_13_86_1 e_1_2_13_9_1 e_1_2_13_63_1 e_1_2_13_82_1 Timm NH (e_1_2_13_84_1) 2002 Holm S (e_1_2_13_39_1) 1979; 6 Tippett LHC (e_1_2_13_85_1) 1931 e_1_2_13_95_1 Mudholkar GS (e_1_2_13_57_1) 1979 e_1_2_13_99_1 e_1_2_13_18_1 e_1_2_13_14_1 e_1_2_13_37_1 e_1_2_13_10_1 e_1_2_13_56_1 Pesarin F (e_1_2_13_67_1) 2001 e_1_2_13_75_1 e_1_2_13_52_1 e_1_2_13_71_1 e_1_2_13_5_1 Westfall PH (e_1_2_13_91_1) 1993 e_1_2_13_49_1 e_1_2_13_26_1 e_1_2_13_68_1 Hotelling H (e_1_2_13_40_1) 1951 e_1_2_13_45_1 e_1_2_13_87_1 e_1_2_13_64_1 e_1_2_13_103_1 e_1_2_13_41_1 e_1_2_13_60_1 e_1_2_13_83_1 e_1_2_13_6_1 Fisher RA (e_1_2_13_28_1) 1932 e_1_2_13_90_1 e_1_2_13_94_1 Good IJ (e_1_2_13_33_1) 1955; 17 e_1_2_13_98_1 e_1_2_13_19_1 e_1_2_13_15_1 e_1_2_13_38_1 e_1_2_13_11_1 e_1_2_13_34_1 e_1_2_13_30_1 e_1_2_13_72_1 e_1_2_13_2_1 Calhoun VD (e_1_2_13_16_1) 2016 e_1_2_13_27_1 e_1_2_13_46_1 e_1_2_13_69_1 e_1_2_13_102_1 e_1_2_13_42_1 e_1_2_13_65_1 e_1_2_13_7_1 Anderson TW (e_1_2_13_3_1) 2003 e_1_2_13_80_1 Stouffer SA (e_1_2_13_79_1) 1949 Bhandary M (e_1_2_13_8_1) 2011; 10 e_1_2_13_93_1 Scheffé H (e_1_2_13_76_1) 1959 e_1_2_13_97_1 e_1_2_13_35_1 e_1_2_13_58_1 e_1_2_13_31_1 e_1_2_13_77_1 e_1_2_13_12_1 e_1_2_13_54_1 Lipták T (e_1_2_13_53_1) 1958; 3 e_1_2_13_73_1 Draper D (e_1_2_13_23_1) 1992 e_1_2_13_89_1
References_xml	– volume: 295 start-page: 1737 year: 2002 end-page: 1740 article-title: Placebo and opioid analgesia—Imaging a shared neuronal network publication-title: Science – volume: 24 start-page: 926 year: 2011 end-page: 930 article-title: Is the weighted z‐test the best method for combining probabilities from independent tests? publication-title: J Evol Biol – volume: 327 start-page: 307 year: 1986 end-page: 310 article-title: Statistical methods for assessing agreement between two methods of clinical measurement publication-title: Lancet – year: 2005 – volume: 3 start-page: 171 year: 1958 end-page: 197 article-title: On the combination of independent tests publication-title: A Magyar Tudományos Akadémia Matematikai Kutató Intézetének Közlémenyei – volume: 81 start-page: 1000 year: 1986 end-page: 1004 article-title: The maximum familywise error rate of Fisher's least significant difference test publication-title: J Am Stat Assoc – volume: 5 start-page: 253 year: 2006 end-page: 263 article-title: A note on the power of Fisher's least significant difference procedure publication-title: Pharm Stat – volume: 23 start-page: 54 year: 2004 end-page: 63 article-title: Combining voxel intensity and cluster extent with permutation test framework publication-title: NeuroImage – volume: 7 start-page: 167 year: 2006 end-page: 181 article-title: A tail strength measure for assessing the overall univariate significance in a dataset publication-title: Biostatistics – volume: 62 start-page: 811 year: 2012 end-page: 815 article-title: Multiple testing corrections, nonparametric methods, and random field theory publication-title: NeuroImage – volume: 22 start-page: 643 year: 2013 end-page: 660 article-title: Robust non‐parametric tests for complex‐repeated measures problems in ophthalmology publication-title: Stat Meth Med Res – volume: 38 start-page: 659 year: 1967 end-page: 680 article-title: On the combination of independent test statistics publication-title: Ann Math Stat – volume: 64 start-page: 1215 year: 2008 end-page: 1222 article-title: Screening for partial conjunction hypotheses publication-title: Biometrics – volume: 47 start-page: 757 year: 1991 end-page: 762 article-title: Two guidelines for bootstrap hypothesis testing publication-title: Biometrics – volume: 22 start-page: 170 year: 2002 end-page: 185 article-title: Truncated product method for combining p‐values publication-title: Genetic Epidemiol – year: 1969 – volume: 51 start-page: 479 year: 1986 end-page: 481 article-title: A note on Roy's largest root publication-title: Psychometrika – volume: 80 start-page: 351 year: 1972 end-page: 363 article-title: An additive method for combining probability values from independent experiments publication-title: J Psychol – volume: 15 start-page: 870 year: 2002 end-page: 878 article-title: Thresholding of statistical maps in functional neuroimaging using the false discovery rate publication-title: NeuroImage – volume: 102 start-page: 3 year: 2014 end-page: 10 article-title: General overview on the merits of multimodal neuroimaging data fusion publication-title: NeuroImage – year: 1949 – volume: 24 start-page: 295 year: 1982 end-page: 300 article-title: Multiparameter hypothesis testing and acceptance sampling publication-title: Technometrics – volume: 85 start-page: 185 year: 1978 end-page: 193 article-title: Combining results of independent studies publication-title: Psychol Bull – volume: 24 start-page: 220 year: 1953 end-page: 238 article-title: On a heuristic method of test construction and its use in multivariate analysis publication-title: Ann Math Stat – year: 1993 – volume: 81 start-page: 826 year: 1986 end-page: 831 article-title: Modified sequentially rejective multiple test procedures publication-title: J Am Stat Assoc – year: 2016 article-title: Multimodal fusion of brain imaging data: A key to finding the missing link(s) in complex mental illness publication-title: Biological Psychiatry: Cognitive Neuroscience and Neuroimaging – volume: 5 start-page: 496 year: 2000 end-page: 515 article-title: Combining independent p values: Extensions of the stouffer and binomial methods publication-title: Psychol Meth – volume: 99 start-page: 96 year: 2004 end-page: 104 article-title: Large‐scale simultaneous hypothesis testing publication-title: J Am Stat Assoc – volume: 1 start-page: 87 year: 1992 end-page: 101 article-title: A resampling procedure for nonparametric combination of several dependent tests publication-title: J Italian Stat Soc – year: 1931 – volume: 92 start-page: 381 year: 2014 end-page: 397 article-title: Permutation inference for the general linear model publication-title: NeuroImage – year: 1987 – year: 2007 – volume: 5 start-page: 994 year: 2011 end-page: 1019 article-title: An adaptively weighted statistic for detecting differential gene expression when combining multiple transcriptomic studies publication-title: Ann Appl Stat – volume: 6 start-page: 65 year: 1979 end-page: 70 article-title: A simple sequentially rejective multiple test procedure publication-title: Scand J Stat – volume: 60 start-page: 183 year: 2002 end-page: 190 article-title: Combining dependent p‐values publication-title: Stat Probab Lett – volume: 44 start-page: 83 year: 2009 end-page: 98 article-title: Threshold‐free cluster enhancement: Addressing problems of smoothing, threshold dependence and localisation in cluster inference publication-title: Neuroimage – volume: 277 start-page: 67 year: 2011 end-page: 73 article-title: A powerful truncated tail strength method for testing multiple null hypotheses in one dataset publication-title: J Theoretical Biol – volume: 12 start-page: 419 year: 2003 end-page: 446 article-title: Controlling the familywise error rate in functional neuroimaging: A comparative review publication-title: Stat Meth Med Res – volume: 31 start-page: 987 year: 1975 end-page: 992 article-title: A method for combining non‐independent, one‐sided tests of significance publication-title: Biometrics – year: 1992 – volume: 10 start-page: 436 year: 2011 end-page: 446 article-title: Comparison of several tests for combining several independent tests publication-title: J Modern Appl Stat Meth – volume: 99 start-page: 571 year: 2014 end-page: 588 article-title: Applications of multivariate modeling to neuroimaging group analysis: A comprehensive alternative to univariate general linear model publication-title: NeuroImage – year: 2002 – volume: 35 start-page: 161 year: 2014 end-page: 172 article-title: Altered resting‐state activity in seasonal affective disorder publication-title: Hum Brain Mapp – volume: 34 start-page: 287 year: 1985 end-page: 296 article-title: Combining independent statistical tests publication-title: Statistician – volume: 5 start-page: 99 year: 1949 end-page: 114 article-title: Comparing individual means in the analysis of variance publication-title: Biometrics – volume: 164 start-page: 444 year: 1969 end-page: 445 article-title: Surgery in the rat during electrical analgesia induced by focal brain stimulation publication-title: Science – volume: 70 start-page: 211 year: 2013 end-page: 222 article-title: The hypnotic zolpidem increases the synchrony of BOLD signal fluctuations in widespread brain networks during a resting paradigm publication-title: NeuroImage – year: 2013 – volume: 54 start-page: 172 year: 1990 end-page: 179 article-title: On a nonparametric combination method for dependent permutation tests with applications publication-title: Psychother Psychosom – year: 2009 – volume: 50 start-page: 745 year: 2008 end-page: 755 article-title: Multiple testing with minimal assumptions publication-title: Biom J – year: 1962 – volume: 25 start-page: 360 year: 2003 end-page: 366 article-title: Rank truncated product of P‐values, with application to genomewide association scans publication-title: Gene Epidemiol – year: 2001 – volume: 25 start-page: 383 year: 2005 end-page: 394 article-title: A comparison of random field theory and permutation methods for the statistical analysis of MEG data publication-title: Neuroimage – year: 2010a – volume: 47 start-page: 467 year: 2004 end-page: 485 article-title: A systematic comparison of methods for combining p‐values from independent tests publication-title: Comput Stat Data Anal – year: 1959 – volume: 24 start-page: 471 year: 1932 end-page: 494 article-title: Certain generalizations in the analysis of variance publication-title: Biometrika – volume: 17 start-page: 264 year: 1955 end-page: 265 article-title: On the weighted combination of significance tests publication-title: J R Stat Soc Series B – volume: 91 start-page: 412 year: 2014 end-page: 419 article-title: Cluster‐extent based thresholding in fMRI analyses: Pitfalls and recommendations publication-title: NeuroImage – volume: 26 start-page: 117 year: 1955 end-page: 121 article-title: Some new test criteria in multivariate analysis publication-title: The Annals of Mathematical Statistics – volume: 22 start-page: 209 year: 1927 end-page: 212 article-title: Probable inference, the law of succession, and statistical inference publication-title: J Am Stat Assoc – volume: 18 start-page: 1368 year: 2005 end-page: 1373 article-title: Combining probability from independent tests: The weighted z‐method is superior to Fisher's approach publication-title: J Evol Biol – volume: 17 start-page: 1607 year: 2014 end-page: 1612 article-title: Representation of aversive prediction errors in the human periaqueductal gray publication-title: Nat Neurosci – volume: 63 start-page: 655 year: 1976 article-title: On closed testing procedures with special reference to ordered analysis of variance publication-title: Biometrika – volume: 11 start-page: 690 year: 1991 end-page: 699 article-title: Comparing functional (PET) images: The assessment of significant change publication-title: J Cereb Blood Flow Metab – volume: 57 start-page: 289 year: 1995 end-page: 300 article-title: Controlling the false discovery rate: A practical and powerful approach to multiple testing publication-title: J R Stat Soc Ser B – year: 2015 – volume: 25 start-page: 661 year: 2005 end-page: 667 article-title: Conjunction revisited publication-title: NeuroImage – volume: 25 start-page: 653 year: 2005 end-page: 660 article-title: Valid conjunction inference with the minimum statistic publication-title: NeuroImage – volume: 24 start-page: 1836 year: 2011 end-page: 1841 article-title: Optimally weighted z‐test is a powerful method for combining probabilities in meta‐analysis publication-title: J Evol Biol – volume: 74 start-page: 812 year: 1979 end-page: 814 article-title: Asymptotically optimal methods of combining tests publication-title: J Am Stat Assoc – volume: 28 start-page: 1537 year: 2009 end-page: 1553 article-title: Choosing an optimal method to combine p‐values publication-title: Stat Med – volume: 35 start-page: 1483 year: 2006 end-page: 1494 article-title: Combining univariate tests for multivariate location problem publication-title: Commun Stat – volume: 2 start-page: 360 year: 1931 end-page: 378 article-title: The generalization of Student's ratio publication-title: Ann Math Stat – volume: 16 start-page: 538 year: 2002 end-page: 550 article-title: Combining brains: A survey of methods for statistical pooling of information publication-title: NeuroImage – year: 2003 – start-page: 23 year: 1951 end-page: 41 – volume: 102 start-page: 184 year: 2014 end-page: 191 article-title: Fusing DTI and fMRI data: A survey of methods and applications publication-title: NeuroImage – year: 1996 – volume: 25 start-page: 379 year: 1933 end-page: 410 article-title: On a method of determining whether a sample of size n supposed to have been drawn from a parent population having a known probability integral has probably been drawn at random publication-title: Biometrika – volume: 3 start-page: 20 year: 1961 end-page: 33 article-title: The combination of probabilities: An application of orthonormal functions publication-title: Aus J Stat – volume: 30 start-page: 180 year: 1938 end-page: 187 article-title: A generalization of Fisher's z test publication-title: Biometrika – volume: 27 start-page: 201 year: 2005 end-page: 209 article-title: Somatotopic organisation of the human insula to painful heat studied with high resolution functional imaging publication-title: NeuroImage – volume: 8 start-page: 642 year: 1988 end-page: 653 article-title: Enhanced detection of focal brain responses using intersubject averaging and change‐distribution analysis of subtracted PET images publication-title: J Cerebral Blood Flow Metab – volume: 49 start-page: 559 year: 1954 end-page: 574 article-title: Combining independent tests of significance publication-title: J Am Stat Assoc – volume: 14 start-page: 368 year: 2013 article-title: Meta‐analysis methods for combining multiple expression profiles: Comparisons, statistical characterization and an application guideline publication-title: BMC Bioinformatics – year: 1932 – volume: 48 start-page: 156 year: 1951 end-page: 158 article-title: A statistical consideration in psychological research publication-title: Psychol Bull – start-page: 345 year: 1979 end-page: 366 – volume: 22 start-page: 2748 year: 2002 end-page: 2752 article-title: Imaging attentional modulation of pain in the periaqueductal gray in humans publication-title: J Neurosci – volume: 37 start-page: 3867 year: 2009 end-page: 3892 article-title: Karl Pearson's meta‐analysis revisited publication-title: Ann Stat – volume: 62 start-page: 626 year: 1967 end-page: 633 article-title: Rectangular confidence regions for the means of multivariate normal distributions publication-title: J Am Stat Assoc – volume: 26 start-page: 1 year: 1934 end-page: 1 article-title: On the test for randomness: Remarks, further illustration, and table of for given values of publication-title: Biometrika – volume: 22 start-page: 669 year: 2010b end-page: 684 article-title: Finite‐sample consistency of combination‐based permutation tests with application to repeated measures designs publication-title: J Nonparametr Stat – volume: 29 start-page: 141 year: 1994 end-page: 163 article-title: A study of multivariate permutation tests which may replace Hotelling's test in prescribed circumstances publication-title: Multivariate Behav Res – volume: 30 start-page: 768 year: 2006 end-page: 779 article-title: A non‐parametric approach for co‐analysis of multi‐modal brain imaging data: Application to alzheimer's disease publication-title: NeuroImage – ident: e_1_2_13_47_1 doi: 10.1111/j.1467-842X.1961.tb00058.x – ident: e_1_2_13_56_1 doi: 10.1002/pst.210 – ident: e_1_2_13_75_1 doi: 10.1214/aoms/1177729029 – ident: e_1_2_13_103_1 doi: 10.1016/j.neuroimage.2013.09.071 – volume-title: Multivariate Permutation Tests, with Applications in Biostatistics year: 2001 ident: e_1_2_13_67_1 contributor: fullname: Pesarin F – ident: e_1_2_13_14_1 doi: 10.1016/j.neuroimage.2005.03.041 – ident: e_1_2_13_54_1 doi: 10.1016/j.csda.2003.11.020 – ident: e_1_2_13_31_1 doi: 10.1016/j.neuroimage.2005.01.013 – ident: e_1_2_13_15_1 doi: 10.2307/2529826 – ident: e_1_2_13_46_1 doi: 10.1007/BF02294069 – ident: e_1_2_13_87_1 doi: 10.2307/3001913 – ident: e_1_2_13_17_1 doi: 10.1186/1471-2105-14-368 – ident: e_1_2_13_5_1 doi: 10.1111/j.1541-0420.2007.00984.x – ident: e_1_2_13_65_1 doi: 10.1159/000288391 – ident: e_1_2_13_81_1 doi: 10.1093/biostatistics/kxj009 – ident: e_1_2_13_98_1 doi: 10.1002/sim.3569 – ident: e_1_2_13_55_1 doi: 10.1093/biomet/63.3.655 – ident: e_1_2_13_60_1 doi: 10.1191/0962280203sm341ra – ident: e_1_2_13_36_1 doi: 10.1016/j.neuroimage.2004.04.035 – ident: e_1_2_13_41_1 doi: 10.1214/aoms/1177732979 – ident: e_1_2_13_26_1 doi: 10.1080/00223980.1972.9924813 – ident: e_1_2_13_82_1 – ident: e_1_2_13_71_1 doi: 10.1214/aoms/1177728599 – ident: e_1_2_13_9_1 doi: 10.2307/2281130 – ident: e_1_2_13_102_1 doi: 10.1111/j.1420-9101.2011.02297.x – volume-title: Applied Multivariate Analysis year: 2002 ident: e_1_2_13_84_1 contributor: fullname: Timm NH – volume-title: Testing Statistical Hypotheses year: 2005 ident: e_1_2_13_50_1 contributor: fullname: Lehmann EL – volume-title: The Methods of Statistics year: 1931 ident: e_1_2_13_85_1 contributor: fullname: Tippett LHC – ident: e_1_2_13_29_1 doi: 10.1038/jcbfm.1988.111 – ident: e_1_2_13_97_1 doi: 10.1016/j.neuroimage.2014.01.060 – ident: e_1_2_13_99_1 doi: 10.1016/j.neuroimage.2013.12.058 – ident: e_1_2_13_51_1 doi: 10.1214/10-AOAS393 – ident: e_1_2_13_69_1 doi: 10.1080/10485250902807407 – ident: e_1_2_13_12_1 doi: 10.1002/9780470743386 – ident: e_1_2_13_77_1 doi: 10.1080/01621459.1986.10478341 – ident: e_1_2_13_73_1 doi: 10.1037/0033-2909.85.1.185 – ident: e_1_2_13_4_1 doi: 10.1111/j.2517-6161.1995.tb02031.x – start-page: 345 volume-title: Symposium on Optimizing Methods in Statistics year: 1979 ident: e_1_2_13_57_1 contributor: fullname: Mudholkar GS – ident: e_1_2_13_37_1 doi: 10.1080/01621459.1986.10478364 – ident: e_1_2_13_20_1 doi: 10.1007/978-1-4757-3847-6 – ident: e_1_2_13_72_1 doi: 10.1126/science.164.3878.444 – ident: e_1_2_13_34_1 doi: 10.2307/2532163 – ident: e_1_2_13_94_1 doi: 10.1093/biomet/24.3-4.471 – ident: e_1_2_13_92_1 doi: 10.1111/j.1420-9101.2005.00917.x – start-page: 23 volume-title: Proceedings of the second berkeley symposium on mathematical statistics and probability year: 1951 ident: e_1_2_13_40_1 contributor: fullname: Hotelling H – ident: e_1_2_13_19_1 doi: 10.1111/j.1420-9101.2010.02226.x – ident: e_1_2_13_68_1 doi: 10.1002/9780470689516 – ident: e_1_2_13_42_1 doi: 10.1007/978-1-4899-7180-7 – ident: e_1_2_13_101_1 doi: 10.1002/gepi.0042 – ident: e_1_2_13_38_1 doi: 10.1002/9780470316672 – ident: e_1_2_13_45_1 doi: 10.1016/S0167-7152(02)00310-3 – ident: e_1_2_13_48_1 doi: 10.1093/biomet/30.1-2.180 – ident: e_1_2_13_70_1 doi: 10.1126/science.1067176 – ident: e_1_2_13_83_1 doi: 10.1016/j.neuroimage.2015.10.090 – ident: e_1_2_13_18_1 doi: 10.1016/j.neuroimage.2014.06.027 – ident: e_1_2_13_95_1 doi: 10.1080/01621459.1927.10502953 – volume-title: Statistical Methods for Research Workers year: 1932 ident: e_1_2_13_28_1 contributor: fullname: Fisher RA – ident: e_1_2_13_64_1 doi: 10.1093/biomet/25.3-4.379 – ident: e_1_2_13_74_1 doi: 10.1038/nn.3832 – ident: e_1_2_13_52_1 doi: 10.1016/j.neuroimage.2012.12.055 – ident: e_1_2_13_43_1 doi: 10.1016/j.jtbi.2011.01.029 – ident: e_1_2_13_63_1 doi: 10.1016/j.neuroimage.2004.09.040 – volume-title: The Analysis of Variance year: 1959 ident: e_1_2_13_76_1 contributor: fullname: Scheffé H – ident: e_1_2_13_32_1 doi: 10.1006/nimg.2001.1037 – ident: e_1_2_13_93_1 doi: 10.1037/h0059111 – ident: e_1_2_13_90_1 doi: 10.1002/bimj.200710456 – year: 2016 ident: e_1_2_13_16_1 article-title: Multimodal fusion of brain imaging data: A key to finding the missing link(s) in complex mental illness publication-title: Biological Psychiatry: Cognitive Neuroscience and Neuroimaging contributor: fullname: Calhoun VD – ident: e_1_2_13_104_1 doi: 10.1214/aoms/1177698861 – volume: 10 start-page: 436 year: 2011 ident: e_1_2_13_8_1 article-title: Comparison of several tests for combining several independent tests publication-title: J Modern Appl Stat Meth doi: 10.22237/jmasm/1320120240 contributor: fullname: Bhandary M – ident: e_1_2_13_88_1 doi: 10.1016/j.neuroimage.2014.05.018 – ident: e_1_2_13_66_1 doi: 10.1007/BF02589052 – volume: 3 start-page: 171 year: 1958 ident: e_1_2_13_53_1 article-title: On the combination of independent tests publication-title: A Magyar Tudományos Akadémia Matematikai Kutató Intézetének Közlémenyei contributor: fullname: Lipták T – volume-title: Combining information: Statistical issues and opportunities for research year: 1992 ident: e_1_2_13_23_1 contributor: fullname: Draper D – ident: e_1_2_13_7_1 doi: 10.1080/01621459.1979.10481035 – ident: e_1_2_13_27_1 doi: 10.1198/016214504000000089 – ident: e_1_2_13_25_1 – ident: e_1_2_13_96_1 doi: 10.1037/11774-000 – ident: e_1_2_13_10_1 doi: 10.1207/s15327906mbr2902_2 – volume-title: An Introduction to Multivariate Statistical Analysis year: 2003 ident: e_1_2_13_3_1 contributor: fullname: Anderson TW – ident: e_1_2_13_11_1 doi: 10.1016/S0140-6736(86)90837-8 – volume-title: Resampling‐Based Multiple Testing: Examples and Methods for P‐Value Adjustment year: 1993 ident: e_1_2_13_91_1 contributor: fullname: Westfall PH – ident: e_1_2_13_62_1 doi: 10.1214/09-AOS697 – ident: e_1_2_13_30_1 doi: 10.1038/jcbfm.1991.122 – volume-title: Applied Multivariate Statistical Analysis year: 2007 ident: e_1_2_13_44_1 contributor: fullname: Johnson RA – ident: e_1_2_13_35_1 doi: 10.1016/j.neuroimage.2005.10.052 – ident: e_1_2_13_13_1 doi: 10.1177/0962280211403659 – ident: e_1_2_13_21_1 doi: 10.1037/1082-989X.5.4.496 – ident: e_1_2_13_86_1 doi: 10.1523/JNEUROSCI.22-07-02748.2002 – volume-title: Combination of One‐Sided Statistical Tests year: 1969 ident: e_1_2_13_61_1 contributor: fullname: Oosterhoff J – volume: 6 start-page: 65 year: 1979 ident: e_1_2_13_39_1 article-title: A simple sequentially rejective multiple test procedure publication-title: Scand J Stat contributor: fullname: Holm S – volume: 26 start-page: 1 year: 1934 ident: e_1_2_13_22_1 article-title: On the test for randomness: Remarks, further illustration, and table of for given values of publication-title: Biometrika contributor: fullname: David FN – ident: e_1_2_13_24_1 doi: 10.1002/gepi.10264 – ident: e_1_2_13_78_1 doi: 10.1016/j.neuroimage.2008.03.061 – volume: 17 start-page: 264 year: 1955 ident: e_1_2_13_33_1 article-title: On the weighted combination of significance tests publication-title: J R Stat Soc Series B contributor: fullname: Good IJ – ident: e_1_2_13_6_1 doi: 10.2307/1267823 – ident: e_1_2_13_80_1 doi: 10.2307/2283989 – ident: e_1_2_13_58_1 doi: 10.1016/j.neuroimage.2012.04.014 – ident: e_1_2_13_100_1 doi: 10.1080/03610920600694496 – ident: e_1_2_13_89_1 doi: 10.2307/2987655 – ident: e_1_2_13_59_1 doi: 10.1016/j.neuroimage.2004.12.005 – ident: e_1_2_13_49_1 doi: 10.1006/nimg.2002.1107 – ident: e_1_2_13_2_1 doi: 10.1002/hbm.22164 – volume-title: The American Soldier: Adjustment During Army Life (Vol. 1) year: 1949 ident: e_1_2_13_79_1 contributor: fullname: Stouffer SA
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Snippet	In this work, we show how permutation methods can be applied to combination analyses such as those that include multiple imaging modalities, multiple data... Abstract In this work, we show how permutation methods can be applied to combination analyses such as those that include multiple imaging modalities, multiple...
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SubjectTerms	Algorithms Cerebral Cortex - physiology Cerebral Cortex - physiopathology Cerebral Cortex/physiology/physiopathology conjunctions general linear model Humans Image Processing, Computer-Assisted - methods Magnetic Resonance Imaging - methods multiple testing Neuroimaging - methods non-parametric combination Pain Measurement - methods permutation tests Physical, chemical, mathematical & earth Sciences Physique, chimie, mathématiques & sciences de la terre Statistics, Nonparametric
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Title	Non-parametric combination and related permutation tests for neuroimaging
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