User profiles for M. Hinne

Max Hinne

Assistant professor, Radboud University Nijmegen
Verified email at donders.ru.nl
Cited by 1971

[HTML][HTML] The JASP guidelines for conducting and reporting a Bayesian analysis

…, M Hinne, Š Kucharskı, A Ly, M Marsman… - Psychonomic Bulletin & …, 2021 - Springer
Despite the increasing popularity of Bayesian inference in empirical research, few practical
guidelines provide detailed recommendations for how to apply Bayesian procedures and …

[HTML][HTML] A tutorial on conducting and interpreting a Bayesian ANOVA in JASP

…, JG Voelkel, A Stefan, A Ly, M Hinne… - L'Année …, 2020 - cairn.info
… under M 1 than under M 0 (ie, support for M 1 versus M 0 ); … occur under M 0 than under M 1
(ie, support for M 0 versus M 1 )… |M 1 ), divided by p(D|M 0 ), or as its reciprocal BF 01 , p(D|M

PhenoScore quantifies phenotypic variation for rare genetic diseases by combining facial analysis with other clinical features using a machine-learning framework

AJM Dingemans, M Hinne, KMG Truijen, L Goltstein… - Nature Genetics, 2023 - nature.com
Several molecular and phenotypic algorithms exist that establish genotype–phenotype
correlations, including facial recognition tools. However, no unified framework that investigates …

A conceptual introduction to Bayesian model averaging

M Hinne, QF Gronau, D van den Bergh… - … in Methods and …, 2020 - journals.sagepub.com
Many statistical scenarios initially involve several candidate models that describe the data-generating
process. Analysis often proceeds by first selecting the best model according to …

[HTML][HTML] Node centrality measures are a poor substitute for causal inference

F Dablander, M Hinne - Scientific reports, 2019 - nature.com
… Max Hinne … The density of a directed acyclic graph is given by d = m/(v(v − 1)), where m
is the … Eichler, M. Causal inference with multiple time series: Principles and problems. Philos…

[HTML][HTML] Clustering children's learning behaviour to identify self-regulated learning support needs

SHE Dijkstra, M Hinne, E Segers, I Molenaar - Computers in Human …, 2023 - Elsevier
… This matrix C is of size m × m , where m is the number of ability curves and every C i , j
represents the probability that ability curve i is in the same cluster as ability curve j. …

Wasserstein variational inference

…, U Güçlü, Y Güçlütürk, M Hinne… - Advances in …, 2018 - proceedings.neurips.cc
This paper introduces Wasserstein variational inference, a new form of approximate Bayesian
inference based on optimal transport theory. Wasserstein variational inference uses a new …

Structurally-informed Bayesian functional connectivity analysis

M Hinne, L Ambrogioni, RJ Janssen, T Heskes… - NeuroImage, 2014 - Elsevier
… The G-Wishart is defined for the cone M + (G) of positive-definite symmetric matrices with off-…
0 − 2 / 2 Z G δ 0 D exp − 1 2 D Ω 1 Ω ∈ M + G where δ are the prior degrees of freedom, D a …

[HTML][HTML] The Bayesian Methodology of Sir Harold Jeffreys as a Practical Alternative to the P Value Hypothesis Test

…, M Hinne, D Matzke, M Marsman… - Computational Brain & …, 2020 - Springer
… If an all-or-none decision on the model space is required, we can use the \(P({\mathscr{M}}_{j}
\mid d_{1})\) to select a single model. Once a single model \({\mathscr{M}}_{j}\) is selected, …

[HTML][HTML] Validation of structural brain connectivity networks: The impact of scanning parameters

KS Ambrosen, SF Eskildsen, M Hinne, K Krug… - Neuroimage, 2020 - Elsevier
… gradient strength of 600 mT/m. Free fixative was washed … /m and keeping constant gradient
length delta = 8 m s, gradient separation DELTA = 17 m s as well as the echo time TE = 30 m