ORCID Profile
0000-0003-0270-096X
Current Organisation
University of Amsterdam
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Publisher: American Association for the Advancement of Science (AAAS)
Date: 28-08-2015
Abstract: One of the central goals in any scientific endeavor is to understand causality. Experiments that seek to demonstrate a cause/effect relation most often manipulate the postulated causal factor. Aarts et al. describe the replication of 100 experiments reported in papers published in 2008 in three high-ranking psychology journals. Assessing whether the replication and the original experiment yielded the same result according to several criteria, they find that about one-third to one-half of the original findings were also observed in the replication study. Science , this issue 10.1126/science.aac4716
Publisher: Springer Science and Business Media LLC
Date: 09-10-2020
DOI: 10.3758/S13423-020-01798-5
Abstract: Despite the increasing popularity of Bayesian inference in empirical research, few practical guidelines provide detailed recommendations for how to apply Bayesian procedures and interpret the results. Here we offer specific guidelines for four different stages of Bayesian statistical reasoning in a research setting: planning the analysis, executing the analysis, interpreting the results, and reporting the results. The guidelines for each stage are illustrated with a running ex le. Although the guidelines are geared towards analyses performed with the open-source statistical software JASP, most guidelines extend to Bayesian inference in general.
Publisher: Springer Science and Business Media LLC
Date: 06-07-2018
Publisher: Informa UK Limited
Date: 20-03-2019
Publisher: Springer Science and Business Media LLC
Date: 16-02-2023
DOI: 10.1007/S42113-022-00160-3
Abstract: 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 appropriate specification of prior distributions, and on the desirability of default recommendations. This article presents a round-table discussion that aims to clarify outstanding issues, explore common ground, and outline practical considerations for any researcher wishing to conduct a Bayesian mixed effects model comparison.
Publisher: eLife Sciences Publications, Ltd
Date: 09-11-2021
DOI: 10.7554/ELIFE.72185
Abstract: Any large dataset can be analyzed in a number of ways, and it is possible that the use of different analysis strategies will lead to different results and conclusions. One way to assess whether the results obtained depend on the analysis strategy chosen is to employ multiple analysts and leave each of them free to follow their own approach. Here, we present consensus-based guidance for conducting and reporting such multi-analyst studies, and we discuss how broader adoption of the multi-analyst approach has the potential to strengthen the robustness of results and conclusions obtained from analyses of datasets in basic and applied research.
Publisher: The Quantitative Methods for Psychology
Date: 06-2021
Publisher: eLife Sciences Publications, Ltd
Date: 05-10-2021
No related grants have been discovered for Johnny van Doorn.