**Preparations for Berlin Oxford summer school** Please participate in this reproducible/open **SURVEY PILOT** (aimed at psychology, but all welcome!): https://asuclas.qualtrics.com/jfe/form/SV_3yMMxvTjLuqN5kN (contact jackie.thompson@psy.ox.ac.uk with any questions) . 1. Create an account on Open Science Framework if you don’t have one yet: https://osf.io/ 2. Check whether there are any further instructions for the specific workshops you will attend (see below) ## Workshops @[toc](Overview) ### Workshop 1: Statistics refresher ### If you have any specific stats questions feel free to email your tutors Amy Orben amy.orben@psy.ox.ac.uk and Jackie Thompson jackie.thompson@psy.ox.ac.uk before the workshop. They might be able to help out, especially if you give them a bit of time to prepare. *Preparations* 1. Have Microsoft Excel installed on your laptop (free versions such as LibreOffice Calc might also work but our resources were created using Excel) 2. Install R and RStudio ([see below for instructions][1]). If you have never worked with R or RStudio before, you might want to have a look at the Software Carpentry “Introduction to R and RStudio” session (but there are also many other helpful introductory courses on the internet): https://swcarpentry.github.io/r-novice-gapminder/ There is also a free intro to R course on [DataCamp][2] which we can recommend. ### Workshop 2: Reproducible Workflows ### Please bring a laptop with your favourite analysis software installed (either R+RStudio or Anaconda+Python3). Please also install [Git][3] and get a free [Github][4] account ### Workshop 4: Reproducibility crisis in clinical studies? A critical evaluation ### This workshop looks at the concept of reproducibility from a clinical study perspective and asks whether the reproducibility crisis also affect clinical studies. Is there a need for reproducibility, and if so, of why? Is there a difference between observational and interventional studies? This workshop is open to researchers from all backgrounds. We explicitly welcome researchers who are not working on clinical studies to ensure critical evaluation of the topic through varied viewpoints and hopefully new insights. The **goal** of the workshop is to sharpen some of our ideas and perhaps identify a gap in the knowledge that needs to be addressed. The **activities** in this workshop include group discussion and pen and paper assignments. The **product** of this workshop is will be a blog post or potentially a commentary paper. To **prepare** for the workshop by making sure that you are familiar with the following papers. You do not have to know the details of each paper, but a glance at each paper will help you formulate your thoughts during the workshop. The papers can be found in the OSF repository. 1. Estimating the reproducibility of psychological science. Science (80- ) 2015; 349: aac4716-aac4716. 2. Kimmelman J, Mogil JS, Dirnagl U. 2Distinguishing between Exploratory and Confirmatory Preclinical Research Will Improve Translation. PLoS Biol 2014; 12: e1001863. 3. Nosek BA, Ebersole CR, DeHaven AC, Mellor DT. The preregistration revolution. Proc Natl Acad Sci 2018; 115: 2600–6. 4. Dal-Re R,Ioannidis JP, Bracken MB, Buffler PA, Chan A-W, Franco EL, La Vecchia C, Weiderpass E. Making Prospective Registration of Observational Research a Reality. Sci Transl Med 2014; 6: 224cm1-224cm1. ### Workshop 5: COBIDAS and BIDS for neuroimaging ### Please bring a laptop. ### Workshop 7: Copyright, Creative Commons licenses, and the GNU GPLv3 ### Please bring a laptop. ### Workshop 8: Public Engagement in Research and Debate [Please read up on participation in a research museum.][5]. For the original German version see [here][6]. A project description is [here][7]. You will meet Wiebke at 1 pm at the Naturkundemuseum Portal 5 (Mitarbeitereingang/Employee Entrance). You will need to register there and receive a guest badge. She will pick you up. For a description how to get to the museum please see the program. ### Workshop 9: Simulating experimental data Slides for this workshop are available here: https://www.slideshare.net/deevybishop Further relevant materials on Open Science Framework: https://osf.io/gupxv/ *Preparations* 1. Have Microsoft Excel installed on your laptop (free versions such as LibreOffice Calc might also work but our resources were created using Excel) 2. Install R and RStudio (see below for instructions). If you have never worked with R or RStudio before, you might want to have a look at the Software Carpentry “Introduction to R and RStudio” session (but there are also many other helpful introductory courses on the internet): https://swcarpentry.github.io/r-novice-gapminder/ There is also a free intro to R course on [DataCamp][8] which we can recommend. ## Installation instructions ## ### Installing R * Open an internet browser and go to www.r-project.org * Click the "download R" link in the middle of the page under "Getting Started." * Click on the link for a CRAN location close to you * Mac users: * Click on the "Download R for (Mac) OS X" link at the top of the page. * Click on the file containing the latest version of R under "Files." * Save the .pkg file, double-click it to open, and follow the installation instructions. * Windows users: * Click on the "Download R for Windows" link at the top of the page. * Click on the "install R for the first time" link at the top of the page. * Click "Download R for Windows" and save the executable file somewhere on your computer. * Run the .exe file and follow the installation instructions. ### Installing R studio R studio is a friendly interface for R. Once it is installed, you need not open the original R software: instead, you access R by opening the R studio application * Go to www.rstudio.com and click on the "Download RStudio" button. * Click on "Download RStudio Desktop." Mac users: * Click on the version recommended for your system, or the latest Mac version, save the .dmg file on your computer, double-click it to open, and then drag and drop it to your applications folder. Windows users: * Click on the version recommended for your system, or the latest Windows version, and save the executable file. Run the .exe file and follow the installation instructions. ## Workshop 10: How to make your data FAIR (findable, accessible, interoperable, and re-usable) You'll also need R and RStudio (see excellent instructions above). Thereafter please run the following to install the codebook package. The second command might fail if you do not have [Rtools](https://cran.r-project.org/bin/windows/Rtools/), if so, don't be bothered and just use the slightly older codebook version that installed successfully. ```r install.packages(c("rmarkdown", "caTools", "tidyverse", "psych", "likert", "knitr", "pander", "skimr", "DT", "future", "haven", "rlang", "mice", "tibble", "purrr", "htmltools", "labeling", "labelled", "rio", "shiny", "miniUI", "glue", "remotes", "codebook")) remotes::install_github('rubenarslan/codebook') ``` ### Resources / Links - [Draft spec for PsychBIDS](https://docs.google.com/document/d/1tKInjbzQp-lkOKazW32f4lk93Peqqm8adfNzRy8I4ZE/edit#) - [Codebook tutorial](https://psyarxiv.com/5qc6h/) - [FAIR paper](https://www.nature.com/articles/sdata201618) [1]: http://#Workshop_1_Statistics_refresher_9 [2]: http://datacamp.com [3]: https://git-scm.com/downloads [4]: https://github.com/ [5]: https://osf.io/74eb3/ [6]: https://www.museumfuernaturkunde.berlin/sites/default/files/pdf-temporary/180821_Publikation%20Besucherpartizipation_ONLINE.pdf [7]: https://www.museumfuernaturkunde.berlin/en/museum/ausstellungen/visitors-participation-museum-fur-naturkunde-berlin%29 [8]: http://datacamp.com