F. (Fabian) Dablander PhD
Faculteit der Natuurwetenschappen, Wiskunde en Informatica
Institute for Biodiversity and Ecosystem Dynamics
Bezoekadres
- Science Park 904
Postadres
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Postbus 94240
1090 GE Amsterdam
Contactgegevens
- Personal website
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Publicaties
2024
- Dablander, F., Sachisthal, M. S. M., Cologna, V., Strahm, N., Bosshard, A., Grüning, N. M., Green, A. J. K., Brick, C., Aron, A. R., & Haslbeck, J. M. B. (2024). Climate change engagement of scientists. Nature Climate Change. https://doi.org/10.1038/s41558-024-02091-2
2023
- Dablander, F., van den Bergh, D., Ly, A., & Wagenmakers, E. M. (2023). Default Bayes Factors for Testing the (In)equality of Several Population Variances. Bayesian Analysis. Advance online publication. https://doi.org/10.48550/arXiv.2003.06278, https://doi.org/10.1214/23-BA1369
Eigenschink, M., Bellach, L., Leonard, S., Dablander, T. E., Maier, J., Dablander, F., & Sitte, H. H. (2023). Cross-sectional survey and Bayesian network model analysis of traditional Chinese medicine in Austria: investigating public awareness, usage determinants and perception of scientific support. BMJ Open, 13(3), Article e060644. https://doi.org/10.1136/bmjopen-2021-060644 [details]- Haslbeck, J., Ryan, O., & Dablander, F. (2023). Multimodality and Skewness in Emotion Time Series. Emotion, 23(8), 2117-2141. https://doi.org/10.1037/emo0001218 [details]
2022
- Dablander, F., Heesterbeek, H., Borsboom, D., & Drake, J. M. (2022). Overlapping timescales obscure early warning signals of the second COVID-19 wave. Proceedings of the Royal Society B: Biological Sciences, 289(1968), Article 20211809. https://doi.org/10.1098/rspb.2021.1809 [details]
- Dablander, F., Huth, K., Gronau, Q. F., Etz, A., & Wagenmakers, E-J. (2022). A puzzle of proportions: Two popular Bayesian tests can yield dramatically different conclusions. Statistics in Medicine, 41(8), 1319-1333. Advance online publication. https://doi.org/10.1002/sim.9278 [details]
- Dekker, M. M., Blanken, T. F., Dablander, F., Ou, J., Borsboom, D., & Panja, D. (2022). Quantifying agent impacts on contact sequences in social interactions. Scientific Reports, 12, Article 3483. https://doi.org/10.1038/s41598-022-07384-0 [details]
- Haslbeck, J. M. B., Ryan, O., & Dablander, F. (2022). The Sum of All Fears: Comparing Networks Based on Symptom Sum-Scores. Psychological Methods, 27(6), 1061-1068. Advance online publication. https://doi.org/10.1037/met0000418 [details]
- Wagenmakers, E-J., Gronau, Q. F., Dablander, F., & Etz, A. (2022). The Support Interval. Erkenntnis, 87(2), 589–601. Advance online publication. https://doi.org/10.31234/osf.io/zwnxb, https://doi.org/10.1007/s10670-019-00209-z [details]
2021
- Blanken, T. F., Tanis, C. C., Nauta, F. H., Dablander, F., Zijlstra, B. J. H., Bouten, R. R. M., Oostvogel, Q. H., Boersma, M. J., van der Steenhoven, M. V., van Harreveld, F., de Wit, S., & Borsboom, D. (2021). Promoting physical distancing during COVID-19: a systematic approach to compare behavioral interventions. Scientific Reports, 11, Article 19463. https://doi.org/10.1038/s41598-021-98964-z [details]
- Tanis, C. C., Leach, N. M., Geiger, S. J., Nauta, F. H., Dablander, F., van Harreveld, F., de Wit, S., Kanters, G., Knoppers, J., Markus, D. A. W., Bouten, R. R. M., Oostvogel, Q. H., Boersma, M. J., van der Steenhoven, M. V., Borsboom, D., & Blanken, T. F. (2021). Smart Distance Lab’s art fair, experimental data on social distancing during the COVID-19 pandemic. Scientific Data, 8, Article 179. https://doi.org/10.1038/s41597-021-00971-2 [details]
- van Doorn, J., van den Bergh, D., Böhm, U., Dablander, F., Derks, K., Draws, T., Etz, A., Evans, N. J., Gronau, Q. F., Haaf, J. M., Hinne, M., Kucharský, Š., Ly, A., Marsman, M., Matzke, D., Komarlu Narendra Gupta, A. R., Sarafoglou, A., Stefan, A., Voelkel, J. G., & Wagenmakers, E-J. (2021). The JASP guidelines for conducting and reporting a Bayesian analysis. Psychonomic Bulletin & Review, 28(3), 813–826. Advance online publication. https://doi.org/10.3758/s13423-020-01798-5 [details]
2020
- Dablander, F., Ryan, O., & Haslbeck, J. M. B. (2020). Choosing between AR(1) and VAR(1) Models in Typical Psychological Applications. PLoS ONE, 15(10), Article e0240730. https://doi.org/10.1371/journal.pone.0240730 [details]
- Ly, A., Stefan, A., van Doorn, J., Dablander, F., van den Bergh, D., Sarafoglou, A., Kucharský, S., Derks, K., Gronau, Q. F., Raj, A., Boehm, U., van Kesteren, E-J., Hinne, M., Matzke, D., Marsman, M., & Wagenmakers, E-J. (2020). The Bayesian Methodology of Sir Harold Jeffreys as a Practical Alternative to the P Value Hypothesis Test. Computational Brain & Behavior, 3(2), 153-161. Advance online publication. https://doi.org/10.31234/osf.io/dhb7x, https://doi.org/10.1007/s42113-019-00070-x [details]
- van den Bergh, D., van Doorn, J., Marsman, M., Draws, T., van Kesteren, E-J., Derks, K., Dablander, F., Gronau, Q. F., Kucharský, Š., Komarlu Narendra Gupta, A. R., Sarafoglou, A., Voelkel, J. G., Stefan, A., Ly, A., Hinne, M., Matzke, D., & Wagenmakers, E-J. (2020). A Tutorial on Conducting and Interpreting a Bayesian ANOVA in JASP. Année Psychologique, 120(1), 73-96. https://doi.org/10.31234/osf.io/spreb, https://doi.org/10.3917/anpsy1.201.0073 [details]
2019
- Dablander, F., & Hinne, M. (2019). Node centrality measures are a poor substitute for causal inference. Scientific Reports, 9, Article 6846. https://doi.org/10.1038/s41598-019-43033-9 [details]
- Dablander, F., Epskamp, S., & Haslbeck, J. M. B. (2019). Studying Statistics Anxiety Requires Sound Statistics: A Comment on Siew, McCartney, and Vitevitch (2019). Scholarship of Teaching and Learning in Psychology, 5(4), 319-323. https://doi.org/10.31234/osf.io/pfnys, https://doi.org/10.1037/stl0000159 [details]
- Edelsbrunner, P., & Dablander, F. (2019). The Psychometric Modeling of Scientific Reasoning: a Review and Recommendations for Future Avenues. Educational Psychology Review, 31(1), 1-34. https://doi.org/10.1007%2Fs10648-018-9455-5 [details]
- Jakob, L., Garcia-Garzon, E., Jarke, H., & Dablander, F. (2019). The Science Behind the Magic? The Relation of the Harry Potter “Sorting Hat Quiz” to Personality and Human Values. Collabra: Psychology, 5(1), Article 31. https://doi.org/10.1525/collabra.240 [details]
- Marsman, M., Waldorp, L., Dablander, F., & Wagenmakers, E-J. (2019). Bayesian estimation of explained variance in ANOVA designs. Statistica Neerlandica, 73(3), 351-372. https://doi.org/10.1111/stan.12173 [details]
2018
- Etz, A., Gronau, Q. F., Dablander, F., Edelsbrunner, P. A., & Baribault, B. (2018). How to become a Bayesian in eight easy steps: An annotated reading list. Psychonomic Bulletin & Review, 25(1), 219-234. https://doi.org/10.3758/s13423-017-1317-5 [details]
2022
- Maier, M., Bartoš, F., Quintana, D., Dablander, F., van den Bergh, D., Marsman, M., Ly, A., & Wagenmakers, E. M. (2022). Model-Averaged Bayesian t-Tests. (pp. 1-44). PsyArXiv. https://doi.org/10.31234/osf.io/d5zwc
2021
- Tanis, C. C., Leach, N. M., Geiger, S., Nauta, F. H., Dablander, F., van Harreveld, F., de Wit, S., Kanters, G., Knoppers, J., Markus, D. A. W., Bouten, R. R. M., Oostvogel, Q. H., Boersma, M. J., van der Steenhoven, M. V., Borsboom, D. & Blanken, T. F. (2021). Metadata record for: Smart Distance Lab's art fair, experimental data on social distancing during the COVID-19 pandemic. Figshare. https://doi.org/10.6084/m9.figshare.14312180.v1
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Nevenwerkzaamheden
Geen nevenwerkzaamheden
Eigenschink, M., Bellach, L., Leonard, S., Dablander, T. E., Maier, J., Dablander, F., & Sitte, H. H. (2023). Cross-sectional survey and Bayesian network model analysis of traditional Chinese medicine in Austria: investigating public awareness, usage determinants and perception of scientific support. BMJ Open, 13(3), Article e060644.