Coordinate based random effect size meta-analysis of neuroimaging studies
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Radu Tanasescu | C. R. Tench | C. S. Constantinescu | W. J. Cottam | D. P. Auer | D. Auer | C. Tench | C. Constantinescu | R. Tanasescu
[1] Y. Benjamini,et al. Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .
[2] M. Lindquist,et al. Meta-analysis of functional neuroimaging data: current and future directions. , 2007, Social cognitive and affective neuroscience.
[3] K. Zilles,et al. Coordinate‐based activation likelihood estimation meta‐analysis of neuroimaging data: A random‐effects approach based on empirical estimates of spatial uncertainty , 2009, Human brain mapping.
[5] Karl J. Friston,et al. Statistical parametric maps in functional imaging: A general linear approach , 1994 .
[6] Peter J. Diggle,et al. Statistics: a data science for the 21st century , 2015 .
[7] N. Laird,et al. Meta-analysis in clinical trials. , 1986, Controlled clinical trials.
[8] Guinevere F. Eden,et al. Meta-Analysis of the Functional Neuroanatomy of Single-Word Reading: Method and Validation , 2002, NeuroImage.
[9] J Radua,et al. A new meta-analytic method for neuroimaging studies that combines reported peak coordinates and statistical parametric maps , 2012, European Psychiatry.
[10] Joaquim Radua,et al. Meta-analytical comparison of voxel-based morphometry studies in obsessive-compulsive disorder vs other anxiety disorders. , 2010, Archives of general psychiatry.
[11] Hans-Peter Kriegel,et al. A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise , 1996, KDD.
[12] Angela R. Laird,et al. Behavior, sensitivity, and power of activation likelihood estimation characterized by massive empirical simulation , 2016, NeuroImage.
[13] Sylvain Chevillard,et al. The functions erf and erfc computed with arbitrary precision and explicit error bounds , 2009, Inf. Comput..
[14] J. Raduà,et al. Localized grey matter atrophy in multiple sclerosis: A meta-analysis of voxel-based morphometry studies and associations with functional disability , 2013, Neuroscience & Biobehavioral Reviews.
[15] M. E. Muller,et al. A Note on the Generation of Random Normal Deviates , 1958 .
[16] Dorothee P. Auer,et al. Coordinate Based Meta-Analysis of Functional Neuroimaging Data; False Discovery Control and Diagnostics , 2013, PloS one.
[17] Angela R. Laird,et al. Activation likelihood estimation meta-analysis revisited , 2012, NeuroImage.
[18] Beatriz Luna,et al. Combining Brains: A Survey of Methods for Statistical Pooling of Information , 2002, NeuroImage.
[19] Paul A. Taylor,et al. Is the statistic value all we should care about in neuroimaging? , 2016, NeuroImage.
[20] F. Barkhof,et al. Grey Matter Atrophy in Multiple Sclerosis: Clinical Interpretation Depends on Choice of Analysis Method , 2016, PloS one.
[21] W. J. Cottam,et al. Neuroscience and Biobehavioral Reviews Functional Reorganisation in Chronic Pain and Neural Correlates of Pain Sensitisation: a Coordinate Based Meta-analysis of 266 Cutaneous Pain Fmri Studies , 2022 .
[22] Thomas E. Nichols,et al. Minimal Data Needed for Valid & Accurate Image-Based fMRI Meta-Analysis , 2016, bioRxiv.
[23] Stephen M. Smith,et al. Meta-analysis of neuroimaging data: A comparison of image-based and coordinate-based pooling of studies , 2009, NeuroImage.
[24] Brian A. Nosek,et al. Power failure: why small sample size undermines the reliability of neuroscience , 2013, Nature Reviews Neuroscience.
[25] S. Costafreda. Parametric coordinate-based meta-analysis: Valid effect size meta-analysis of studies with differing statistical thresholds , 2012, Journal of Neuroscience Methods.
[26] Sergi Costafreda-Gonzalez. Parametric coordinate-based meta-analysis: valid effect size meta-analysis of studies with differing statistical thresholds , 2012 .
[27] Angela M. Uecker,et al. ALE meta‐analysis: Controlling the false discovery rate and performing statistical contrasts , 2005, Human brain mapping.
[28] Simon B Eickhoff,et al. Minimizing within‐experiment and within‐group effects in activation likelihood estimation meta‐analyses , 2012, Human brain mapping.
[29] Hans Knutsson,et al. Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates , 2016, Proceedings of the National Academy of Sciences.
[30] Dorothee P. Auer,et al. Coordinate Based Meta-Analysis of Functional Neuroimaging Data Using Activation Likelihood Estimation; Full Width Half Max and Group Comparisons , 2014, PloS one.
[31] J L Lancaster,et al. Automated Talairach Atlas labels for functional brain mapping , 2000, Human brain mapping.
[32] J. Brooks. Why most published research findings are false: Ioannidis JP, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece , 2008 .
[33] Katya Rubia,et al. Anisotropic Kernels for Coordinate-Based Meta-Analyses of Neuroimaging Studies , 2014, Front. Psychiatry.
[34] Michael B. Miller,et al. The principled control of false positives in neuroimaging. , 2009, Social cognitive and affective neuroscience.
[35] W. J. Cottam,et al. Coordinate based meta-analysis does not show grey matter atrophy in narcolepsy , 2015, Neuroscience & Biobehavioral Reviews.