Fabian Dablander
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The JASP guidelines for conducting and reporting a Bayesian analysis
J Van Doorn, D Van Den Bergh, U Böhm, F Dablander, K Derks, T Draws, ...
Psychonomic Bulletin & Review 28, 813-826, 2021
A tutorial on conducting and interpreting a Bayesian ANOVA in JASP
D van den Bergh, J Van Doorn, M Marsman, T Draws, EJ Van Kesteren, ...
L’Année psychologique 120 (1), 73-96, 2020
Node centrality measures are a poor substitute for causal inference
F Dablander, M Hinne
Scientific reports 9 (1), 6846, 2019
How to become a Bayesian in eight easy steps: An annotated reading list
A Etz, QF Gronau, F Dablander, PA Edelsbrunner, B Baribault
Psychonomic Bulletin & Review 25 (1), 219-234, 2018
Anticipating critical transitions in psychological systems using early warning signals: Theoretical and practical considerations.
F Dablander, A Pichler, A Cika, A Bacilieri
Psychological Methods, 2022
The psychometric modeling of scientific reasoning: A review and recommendations for future avenues
PA Edelsbrunner, F Dablander
Educational Psychology Review 31, 1-34, 2019
An introduction to causal inference
F Dablander
PsyArXiv, 2020
The support interval
EJ Wagenmakers, QF Gronau, F Dablander, A Etz
Erkenntnis, 1-13, 2020
A clinical PREMISE for personalized models: Toward a formal integration of case formulations and statistical networks.
J Burger, S Epskamp, DC van der Veen, F Dablander, RA Schoevers, ...
Journal of Psychopathology and Clinical Science 131 (8), 906, 2022
The Bayesian Methodology of Sir Harold Jeffreys as a Practical Alternative to the P Value Hypothesis Test
A Ly, A Stefan, J van Doorn, F Dablander, D van den Bergh, A Sarafoglou, ...
Computational Brain & Behavior 3, 153-161, 2020
Multimodality and skewness in emotion time series.
J Haslbeck, O Ryan, F Dablander
Emotion, 2023
The sum of all fears: Comparing networks based on symptom sum-scores.
J Haslbeck, O Ryan, F Dablander
Psychological Methods 27 (6), 1061, 2022
What does the crowd believe? A hierarchical approach to estimating subjective beliefs from empirical data.
M Franke, F Dablander, A Schöller, E Bennett, J Degen, MH Tessler, ...
CogSci, 2016
Overlapping Time Scales Obscure Early Warning Signals of the Second COVID-19 Wave
F Dablander, H Heesterbeek, D Borsboom, JM Drake
Proceedings of the Royal Society B: Biological Sciences 289 (1968), 2022
Promoting physical distancing during COVID-19: a systematic approach to compare behavioral interventions
TF Blanken, CC Tanis, FH Nauta, F Dablander, BJH Zijlstra, RRM Bouten, ...
Scientific Reports 11 (1), 19463, 2021
Bayesian estimation of explained variance in ANOVA designs
M Marsman, L Waldorp, F Dablander, EJ Wagenmakers
Statistica Neerlandica 73 (3), 351-372, 2019
Smart Distance Lab’s art fair, experimental data on social distancing during the COVID-19 pandemic
CC Tanis, NM Leach, SJ Geiger, FH Nauta, F Dablander, F van Harreveld, ...
Scientific Data 8 (1), 179, 2021
The science behind the magic? The relation of the Harry Potter “Sorting Hat Quiz” to personality and human values
L Jakob, E Garcia-Garzon, H Jarke, F Dablander
Collabra: Psychology 5 (1), 31, 2019
From face-to-face to Facebook: Probing the effects of passive consumption on interpersonal attraction
AC Orben, A Mutak, F Dablander, M Hecht, JM Krawiec, N Valkovičová, ...
Frontiers in psychology 9, 1163, 2018
A puzzle of proportions: Two popular Bayesian tests can yield dramatically different conclusions
F Dablander, K Huth, QF Gronau, A Etz, EJ Wagenmakers
Statistics in Medicine 41 (8), 1319-1333, 2022
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