Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Johnny van Doorn"'
Autor:
Koen Derks, Julian Burger, Johnny van Doorn, Jolanda J. Kossakowski, Dora Matzke, Ludovica Atticciati, Julia Beitner, Viket Benzesin, Anne L. de Bruijn, Tara R. H. Cohen, Elisa P. A. Cordesius, Marit van Dekken, Nora Delvendahl, Simone Dobbelaar, Eva R. Groenendijk, Merel E. Hermans, Anu P. Hiekkaranta, Ria H. A. Hoekstra, Agnes M. Hoffmann, Sally A. M. Hogenboom, Sercan Kahveci, Irina J. Karaban, Sofieke Kevenaar, Jurriaan L. te Koppele, Anne-wil Kramer, Emese Kroon, Šimon Kucharský, Ricardo Lieuw-On, Gaby Lunansky, Timo P. Matzen, Annemarie Meijer, Annika Nieper, Laura de Nooij, Leonie Poelstra, Wikke J. van der Putten, Alexandra Sarafoglou, Jessica V. Schaaf, Sara A. J. van de Schraaf, Steven van Schuppen, Manon H. M. Schutte, Mitja Seibold, Scarlett K. Slagter, Aishah C. Snoek, Selina Stracke, Zenab Tamimy, Bram Timmers, Han Tran, Elizabeth S. Uduwa-Vidanalage, Laura Vergeer, Linos Vossoughi, Dilan E. Yücel, Eric-Jan Wagenmakers
Publikováno v:
Journal of European Psychology Students, Vol 9, Iss 1, Pp 48-57 (2018)
We outline a network method to synthesize a literature overview from search results obtained by multiple team members. Several network statistics are used to create a single representativeness ranking. We illustrate the method with the dispersed lite
Externí odkaz:
https://doaj.org/article/9800a8d01f1f48d0a44163995f301424
Autor:
Johnny van Doorn, Julia M. Haaf, Angelika Marlene Stefan, Eric-Jan Wagenmakers, Gregory Edward Cox, Clintin P. Davis-Stober, Andrew Heathcote, Daniel W. Heck, Michael Kalish, David Kellen, Dora Matzke, Richard Donald Morey, Bruno Nicenboim, Don van Ravenzwaaij, Jeffrey N. Rouder, Daniel Schad, Rich Shiffrin, Henrik Singmann, Shravan Vasishth, João Veríssimo, Florence Bockting, Suyog Chandramouli, John C Dunn, Quentin Frederik Gronau, Maximilian Linde, Sara D McMullin, Danielle Navarro, Martin Schnuerch, Himanshu Yadav, Frederik Aust
Publikováno v:
Computational Brain and Behavior, 6(1). Springer
van Doorn et al. (2021) outlined various questions that arise when conducting Bayesian model comparison for mixed effects models. Seven response articles offered their own perspective on the preferred setup for mixed model comparison, on the most app
Autor:
Johnny van Doorn
This booklet offers an introduction to Bayesian inference. We look at how different models make different claims about a parameter, how they learn from observed data, and how we can compare these models to each other. We illustrate these ideas throug
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2be0c0131317c3f0c12dc070f04bf235
Publikováno v:
Computational Brain and Behavior, 6(1). Springer
In van Doorn et al. (2021), we outlined a series of open questions concerning Bayes factors for mixed effects model comparison, with an emphasis on the impact of aggregation, the effect of measurement error, the choice of prior distributions, and the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::17e340ca909c8abef5cbf04d4b295081
https://dare.uva.nl/personal/pure/en/publications/bayes-factors-for-mixed-models-perspective-on-responses(2f2d9553-a892-492f-b679-179377cd7069).html
https://dare.uva.nl/personal/pure/en/publications/bayes-factors-for-mixed-models-perspective-on-responses(2f2d9553-a892-492f-b679-179377cd7069).html
Autor:
Anna G. M. Temp, Alexander Ly, Johnny van Doorn, Eric‐Jan Wagenmakers, Yi Tang, Michael W. Lutz, Stefan Teipel
Publikováno v:
Alzheimer's and Dementia, 2022, 1-11
Alzheimer's and dementia 18(11), 2341-2351 (2022). doi:10.1002/alz.12615
Alzheimer's and Dementia, 18(11), 2341-2351. Elsevier
Alzheimer's and dementia 18(11), 2341-2351 (2022). doi:10.1002/alz.12615
Alzheimer's and Dementia, 18(11), 2341-2351. Elsevier
This perspective is a companion to a recent editorial on the use of Bayesian analysis in clinical research. We aim to introduce and highlight the relevance and advantages that Bayesian inference offers to clinical trials using the data on the amyloid
We explore how to translate default priors from linear mixed models to corresponding aggregate analyses in repeated measures ANOVA and paired t-tests.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9621dde3dea1b132bb95e9e4e9b811b4
https://doi.org/10.31234/osf.io/by2d9
https://doi.org/10.31234/osf.io/by2d9
Publikováno v:
Psychology Learning and Teaching, 19(1), 36-45. Symposium Journals Ltd
Sir Ronald Fisher’s venerable experiment “The Lady Tasting Tea” is revisited from a Bayesian perspective. We demonstrate how a similar tasting experiment, conducted in a classroom setting, can familiarize students with several key concepts of B
Autor:
Jeffrey J. Starns, Yoram K. Kunkels, Gustav Nilsonne, Balazs Aczel, Felix Holzmeister, Jörg Rieskamp, Andrea M Cataldo, Casper J. Albers, Ben R. Newell, Brian A Nosek, Raphael Silberzahn, Jean-François Mangin, Morton Ann Gernsbacher, Gary F. Egan, Alexandra Sarafoglou, Barnabas Szaszi, Matthew J. Salganik, Martin Schweinsberg, Alexander T. Kindel, Niko A. Busch, Daniel J. Simons, Emmanuel Caruyer, Eric-Jan Wagenmakers, Russell A. Poldrack, Dora Matzke, Noah van Dongen, Anna Dreber, Nelson Cowan, Barbara A. Spellman, Chris Donkin, Gilles Dutilh, Johnny van Doorn, Don van Ravenzwaaij, Marcus R. Munafò, Marcel A.L.M. van Assen, Rink Hoekstra, Juergen Huber, Samuel St-Jean, Laura F. Bringmann, Udo Boehm, Daniel J. Benjamin, Tom Schonberg, Eric Luis Uhlmann, D. Stephen Lindsay, Michael Kirchler, David R. Shanks, Jojanneke A. Bastiaansen, Kai J. Jonas, Andrew Delios, Olmo van den Akker, Jelte M. Wicherts, Sabine Hoffmann, Rotem Botvinik-Nezer, Magnus Johannesson
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f2e0e5bf6864bc3b20e122e1d256c9f0
https://doi.org/10.7554/elife.72185.sa2
https://doi.org/10.7554/elife.72185.sa2
Publikováno v:
Tutorials in Quantitative Methods for Psychology, Vol 17, Iss 2, Pp 154-165 (2021)
Although the Kendall distance is a standard metric in computer science, it is less widely used in psychology. We demonstrate the usefulness of the Kendall distance for analyzing psychological data that take the form of ranks, lists, or orders of item
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8437fe579eaa4d88d05d1ea078100e08
https://doi.org/10.31234/osf.io/5juh3
https://doi.org/10.31234/osf.io/5juh3
Autor:
Michael Schulte-Mecklenbeck, Sophia Crüwell, Sam Parsons, Alexander Etz, Hannah Moshontz, Amy Orben, Matthew C. Makel, Johnny van Doorn, Jesse C. Niebaum
Publikováno v:
Zeitschrift für Psychologie
Abstract. The open science movement is rapidly changing the scientific landscape. Because exact definitions are often lacking and reforms are constantly evolving, accessible guides to open science are needed. This paper provides an introduction to op