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The focus of this workshop is on the practical aspects of using open science practices in your research. There are plenty of excellent articles justifying why we need better ways of conducting research in psychology, but the mundane aspect of actually getting it done can sometimes be overlooked. If you would like a guide on how to create and manage an Open Science Framework (OSF) project, there is a handy walkthrough [here][1]. This is a place you can publicly store your data and materials for other researchers to access. A recommending reading list for journal articles focusing on using open science practices covered in the workshop can be found [here][2]. However, a lot of the more useful resources are either blog posts or presentations by other researchers. Here are a selection of the resources I've found particularly useful. ---------- **Planning a study** The most comprehensive pre-registration template is included as a Word document here. This is based on the template for the Open Science Framework's (OSF) [pre-registration challenge][3]. There is also the briefer AsPredicted template included, and you can find these and some additional templates [here][4]. In addition to the templates, there is a list of examples that have been submitted to the pre-registration challenge for different types of research. This sheet was included here, but it is originally from the OSF pre-registration [outreach packet][5]. Pre-registration can be demanding, especially if you or your supervisors have no previous experience. Here are some handy resources to get you more comfortable with pre-registration: - [Pre-registration primer by Tom Hardwicke.][6] - [A plan, not a prison by Alexander DeHaven.][7] - [A practical guide to pre-registration by Anne Scheel][8]. - Knowing a bad pre-registration is almost as important as knowing a good one. I wrote [a blog post][9] about all the mistakes I made in my first attempt so others can learn from it. - [Pre-registration 101 by Lindsay, Simon, and Lilienfeld][10]. A key part of pre-registering research is estimating how many participants you will require to have sufficient statistical power. This ensures that the results are informative regardless of the outcome. However, power analysis can be tricky and it is another skill that is lacking in many statistics courses. Here are some resources that may help: - [G*Power][11] is probably the most common way of conducting a power analysis. It is a free piece of software that covers different designs. However, it is limited when you have more complex designs. - Simulating your experiment is the most flexible way of estimating power. However, it relies on being able to write code. Here is a [tutorial][12] by Jeff Hughes on how to simulate an experiment using R. - Another R power analysis [tutorial][13] by Oli Clark. An extension of pre-registration is the Registered Report (RR) article. This is a type of journal article where pre-registration is incorporated into the review process before any data is collected. RRs are a new publication format, so here are some places to get to grips with them: - Here is a [maintained list][14] of all the journals that accept RRs. This also includes the submission guidelines or editorials announcing them. - Here is a [list of reasons][15] why RR submissions get desk rejected. Make sure you follow these if you plan to submit a RR. - If you want to see some examples of RRs. Here is an example of one written by an [undergraduate student][16] and a [postgraduate student][17]. ---------- **Finishing a study** If you have a finished project, you can retrospectively make aspects of your research more open. Focus on what you *can* make open, rather than what you cannot make open. In the words of [Klein et al. (2018)][18], "each incremental step towards complete transparency adds positive value". **Open materials/data/scripts** - Some [starter tips][19] on sharing data and analysis scripts by Katherine Wood. **Pre- and post-prints** Here are a few resources to help you get acquainted with pre- and post-prints: - I recommend listening to the [Everything Hertz podcast episode][20] on pre-prints. - For extensive guidance on pre-prints, there is a FAQ section on [ASAPbio][21]. ---------- **Open science in qualitative research** This workshop has mostly focused on how to make quantitative research more open as I have very little expertise in qualitative methods. Qualitative research has received less attention which may be due to some of the philosophical differences between the two approaches. Here are some of the resources that I have found tackling the issue of open science in qualitative research: - [An Inside Higher Ed article by Elman and Kapiszewski (2018)][22]. - [Open science in sport and exercise psychology with a focus on qualitative research by Tamminen and Poucher (2018).][23] - [Exploring Pre-registration and Pre-analysis Plans for Qualitative Inference pre-print by Kern and Gleditsch.][24] [1]: [2]: [3]: [4]: [5]: [6]: [7]: [8]: [9]: [10]: [11]: [12]: [13]: [14]: [15]: [16]: [17]: [18]: [19]: [20]: [21]: [22]: [23]: [24]:
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