UZH ReproducibiliTea Journal Club
The ReproducibilitTea is a journal club dedicated to topics related to reproducibility, open science, research quality, or good/bad research practices (in any field).
Organizer: Simon Schwab
Spring semester 2020
CRS will host the ReproducibiliTea journal club in the spring semester of 2020 again. We meet approximately every second week on Thursdays at 16:00, see schedule below. You can join the journal club at here using Zoom.
Brew your own tea before you join. All participants are welcome! Are you interested in discussing a paper? Contact us at crs@ebpi.uzh.ch
Speaker information: The talk should approximately be 30 min. followed by a 15-30 min. discussion. Please join the meeting 15 min. before for an audio/video check.
Slides: PDF of the talks are available here.
Schedule:
May 28, 2020 16:00 - 17:00, TBA
May 14, 2020 16:00 - 17:00, Servan Grüninger,
What is replication? by Nosek & Errington (2020)
April 30, 2020 16:00 - 17:00, Bettina Baessler,
Robustness and Reproducibility of Radiomics in Magnetic Resonance Imaging: A Phantom Study by Baessler et al. (2019)
April 2, 2020 16:00 - 17:00, Samuel Pawel,
A Reproducible Data Analysis Workflow with R Markdown, Git, Make, and Docker by Peikert & Brandmaier (2019)
March 26, 2020 16:00 - 17:00, Dr. Filip Melinscak,
Automating Sciences: Philosophical and Social Dimensions by King et al. (2018)
Fall semester 2019
| Date | Name | Title |
|---|---|---|
|
19.09.2019 |
Leonhard Held |
Royal Statistical Society discussion of “A new standard for the analysis and design of replication studies” |
|
10.10.2019 |
Samuel Pawel | Predictive evaluation of replication studies Master thesis |
|
24.10.2019 |
Simon Schwab |
Why we need to report more than “Data were analyzed by t-tests or ANOVA”. Weissgerber et al. eLife, 2018. |
| 14.11.2019
|
Eva Furrer |
Changed: Many Labs 2: Investigating Variation in Replicability Across Samples and Settings. Klein, Vianello et al., Advances in Methods and https://journals.sagepub.com/doi/10.1177/2515245918810225 and if time allows Predicting replication outcomes in the Many Labs 2 study. Forsell, Viganola et al. |
| 28.11.2019
|
Mark Robinson |
Many Analysts, One Data Set: Making Transparent How Variations in Analytic Choices Affect Results. R. Silberzahn, E. L. Uhlmann, D. P. Martin et al., Advances in Methods and Practices in Psychological Science, 1(3), 337–356. |
| 05.12.2019 |
Filip Melinscak |
Flexible Yet Fair: Blinding Analyses in Experimental Psychology.
Gilles Dutilh, Alexandra Sarafoglou, and Eric-Jan Wagenmakers
|
