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 | 958 | 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 | 315 | 2020 |
Node centrality measures are a poor substitute for causal inference F Dablander, M Hinne Scientific reports 9 (1), 6846, 2019 | 174 | 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 | 152 | 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 28 (4), 765, 2023 | 51 | 2023 |
The psychometric modeling of scientific reasoning: A review and recommendations for future avenues PA Edelsbrunner, F Dablander Educational Psychology Review 31, 1-34, 2019 | 44 | 2019 |
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 | 40 | 2022 |
The support interval EJ Wagenmakers, QF Gronau, F Dablander, A Etz Erkenntnis, 1-13, 2020 | 40 | 2020 |
An introduction to causal inference F Dablander PsyArXiv, 2020 | 39 | 2020 |
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 | 38 | 2020 |
Multimodality and skewness in emotion time series. J Haslbeck, O Ryan, F Dablander Emotion, 2023 | 31 | 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 | 22 | 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 | 21 | 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 | 17 | 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 | 16 | 2021 |
Bayesian estimation of explained variance in ANOVA designs M Marsman, L Waldorp, F Dablander, EJ Wagenmakers Statistica Neerlandica 73 (3), 351-372, 2019 | 16 | 2019 |
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 | 15 | 2019 |
Climate change engagement of scientists F Dablander, MSM Sachisthal, V Cologna, N Strahm, A Bosshard, ... Nature Climate Change 14 (10), 1033-1039, 2024 | 13 | 2024 |
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 | 13 | 2022 |
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 | 13 | 2021 |