Related references
Note: Only part of the references are listed.Electroencephalographic correlates of temporal Bayesian belief updating and surprise
Antonino Visalli et al.
NEUROIMAGE (2021)
Permutation Tests for Regression, ANOVA, and Comparison of Signals: The permuco Package
Jaromil Frossard et al.
JOURNAL OF STATISTICAL SOFTWARE (2021)
Having your cake and eating it too: Flexibility and power with mass univariate statistics for ERP data
Eric C. Fields et al.
PSYCHOPHYSIOLOGY (2020)
Unfold: an integrated toolbox for overlap correction, non-linear modeling, and regression-based EEG analysis
Benedikt Ehinger et al.
PEERJ (2019)
Recognition memory and featural similarity between concepts: The pupil's point of view
Maria Montefinese et al.
BIOLOGICAL PSYCHOLOGY (2018)
SEREEGA: Simulating event-related EEG activity
Laurens R. Krol et al.
JOURNAL OF NEUROSCIENCE METHODS (2018)
Accounting for stimulus and participant effects in event-related potential analyses to increase the replicability of studies
Audrey Buerki et al.
JOURNAL OF NEUROSCIENCE METHODS (2018)
Balancing Type I error and power in linear mixed models
Hannes Matuschek et al.
JOURNAL OF MEMORY AND LANGUAGE (2017)
MELD: Mixed effects for large datasets
Dylan M. Nielson et al.
PLOS ONE (2017)
iMap4: An open source toolbox for the statistical fixation mapping of eye movement data with linear mixed modeling
Junpeng Lao et al.
BEHAVIOR RESEARCH METHODS (2017)
Cluster-based computational methods for mass univariate analyses of event-related brain potentials/fields: A simulation study
C. R. Pernet et al.
JOURNAL OF NEUROSCIENCE METHODS (2015)
Fitting Linear Mixed-Effects Models Using lme4
Douglas Bates et al.
JOURNAL OF STATISTICAL SOFTWARE (2015)
A general permutation approach for analyzing repeated measures ANOVA and mixed-model designs
Sara Kherad-Pajouh et al.
STATISTICAL PAPERS (2015)
Beyond Power Calculations: Assessing Type S (Sign) and Type M (Magnitude) Errors
Andrew Gelman et al.
PERSPECTIVES ON PSYCHOLOGICAL SCIENCE (2014)
Statistical Power and Optimal Design in Experiments in Which Samples of Participants Respond to Samples of Stimuli
Jacob Westfall et al.
JOURNAL OF EXPERIMENTAL PSYCHOLOGY-GENERAL (2014)
The adaptation of the Affective Norms for English Words (ANEW) for Italian
Maria Montefinese et al.
BEHAVIOR RESEARCH METHODS (2014)
Random effects structure for confirmatory hypothesis testing: Keep it maximal
Dale J. Barr et al.
JOURNAL OF MEMORY AND LANGUAGE (2013)
Advanced EEG analysis using threshold-free cluster-enhancement and non-parametric statistics
Armand Mensen et al.
NEUROIMAGE (2013)
Mass univariate analysis of event-related brain potentials/fields I: A critical tutorial review
David M. Groppe et al.
PSYCHOPHYSIOLOGY (2011)
HDHPLUS® technology reactors as interoperating simulation components
Cesar Pernalete et al.
CIENCIA E INGENIERIA (2011)
LIMO EEG: A Toolbox for Hierarchical LInear MOdeling of ElectroEncephaloGraphic Data
Cyril R. Pernet et al.
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE (2011)
Threshold-free cluster enhancement: Addressing problems of smoothing, threshold dependence and localisation in cluster inference
Stephen M. Smith et al.
NEUROIMAGE (2009)
Mixed-effects modeling with crossed random effects for subjects and items
R. H. Baayen et al.
JOURNAL OF MEMORY AND LANGUAGE (2008)
Statistical parametric mapping for event-related potentials (II): a hierarchical temporal model
SJ Kiebel et al.
NEUROIMAGE (2004)
Assessing the accuracy of prediction algorithms for classification: an overview
P Baldi et al.
BIOINFORMATICS (2000)
Share Paper
