medflex: An R Package for Flexible Mediation Analysis using Natural Effect Models

Autor: Johan Steen, Tom Loeys, Beatrijs Moerkerke, Stijn Vansteelandt

Publikováno v: Journal of Statistical Software, Vol 76, Iss 1, Pp 1-46 (2017)

Mediation analysis is routinely adopted by researchers from a wide range of applied disciplines as a statistical tool to disentangle the causal pathways by which an exposure or treatment affects an outcome. The counterfactual framework provides a lan

Externí odkaz: https://doaj.org/article/ba72108e8d704dd2a85a0ffeba3ff1da

The Influence of Study-Level Inference Models and Study Set Size on Coordinate-Based fMRI Meta-Analyses

Autor: Han Bossier, Ruth Seurinck, Simone Kühn, Tobias Banaschewski, Gareth J. Barker, Arun L. W. Bokde, Jean-Luc Martinot, Herve Lemaitre, Tomáš Paus, Sabina Millenet, Beatrijs Moerkerke

Publikováno v: Frontiers in Neuroscience, Vol 11 (2018)

Given the increasing amount of neuroimaging studies, there is a growing need to summarize published results. Coordinate-based meta-analyses use the locations of statistically significant local maxima with possibly the associated effect sizes to aggre

Externí odkaz: https://doaj.org/article/6742f2063c8845d2a83dc298bf81f1f2

neuRosim: An R Package for Generating fMRI Data

Autor: Yves Rosseel, Geert Berdoolaege, Beatrijs Moerkerke, Joke Durnez, Marijke Welvaert

Publikováno v: Journal of Statistical Software, Vol 44, Iss 10 (2011)

Studies that validate statistical methods for functional magnetic resonance imaging (fMRI) data often use simulated data to ensure that the ground truth is known. However, simulated fMRI data are almost always generated using in-house procedures beca

Externí odkaz: https://doaj.org/article/47d679acc5834148bfc2cf4ec9a498b3

Nonlinear mediation analysis with high‐dimensional mediators whose causal structure is unknown

Autor: Wen Wei Loh, Beatrijs Moerkerke, Tom Loeys, Stijn Vansteelandt

Publikováno v: BIOMETRICS

With multiple potential mediators on the causal pathway from a treatment to an outcome, we consider the problem of decomposing the effects along multiple possible causal path(s) through each distinct mediator. Under Pearl's path-specific effects fram

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3ab8b1ebc596b5db3c8cbc1e9200b76b
https://doi.org/10.1111/biom.13402

The empirical replicability of task-based fMRI as a function of sample size

Autor: Gareth J. Barker, Han Bossier, Gunter Schumann, Henrik Walter, Bernd Ittermann, Dimitri Papadopoulos Orfanos, Beatrijs Moerkerke, Erin Burke Quinlan, Luise Poustka, Eric Artiges, Juliane H Fröhner Dipl-Psych, Michael N. Smolka, Ruth Seurinck, Sanne Roels, Robert Whelan, Andreas Heinz, Penny A. Gowland, Herta Flor, Hugh Garavan, Antoine Grigis, Tobias Banaschewski, Frauke Nees, Sylvane Desrivières, Arun L.W. Bokde, Jean-Luc Martinot

Publikováno v: NeuroImage, Vol 212, Iss, Pp 116601-(2020)
Bossier, H, Roels, S P, Seurinck, R, Banaschewski, T, Barker, G J, Bokde, A L W, Quinlan, E B, Desrivières, S, Flor, H, Grigis, A, Garavan, H, Gowland, P, Heinz, A, Ittermann, B, Martinot, J-L, Artiges, E, Nees, F, Orfanos, D P, Poustka, L, Fröhner Dipl-Psych, J H, Smolka, M N, Walter, H, Whelan, R & Schumann, G & Moerkerke, B 2020, ' The empirical replicability of task-based fMRI as a function of sample size ', NeuroImage, vol. 212, 116601 . https://doi.org/10.1016/j.neuroimage.2020.116601
NEUROIMAGE

Replicating results (i.e. obtaining consistent results using a new independent dataset) is an essential part of good science. As replicability has consequences for theories derived from empirical studies, it is of utmost importance to better understa

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1da7392f7ba9ff702164b0006b7494a2
http://www.sciencedirect.com/science/article/pii/S1053811920300884