OPEN SCIENCE INITIATIVES
My research is carried out using open science principles.
I make my measures and data publicly available to others wherever possible, preregister both hypotheses and analytic plans, and am currently transitioning to doing all my data processing and analyses in R. I am also active in the open
science community, including on Twitter and as a member
and attendee of the Society for the Improvement of
Psychological Science (SIPS).
I also have several on-going collaborations in the open science domain: one with Ian Hussey on a dataset involving implicit attitudes data from roughly 1 million participants and another on hidden invalidity in social and personality psychology measures. I’ve also participated in multiple Many Labs (5) large-scale collaborative efforts on reproducibility in psychological science, and others on transparency in research practices.
Ebersole, C., et al. (2020). Many Labs 5: Testing Pre-Data Collection Peer Review as an Intervention to Increase Reproducibility. Advances in Methods and Practices in Psychological Science, 3, 309-331. Link.
Hussey, I., & Hughes, S. (2020). Hidden Invalidity in 15 Commonly Used Measures in Social and Personality Psychology. Advances in Methods and Procedures in Psychological Science, 3, 166-184. Link.
Landy, J. F., et al. (2020). Crowdsourcing Hypothesis Tests: Making Transparent How Design Choices Shape Research Results. Psychological Bulletin, 146, 451-479. Link.
Hussey, I., Hughes, S., & Nosek, B. Attitudes 2.0: A Large Dataset for Investigating Relations Among Implicit and Explicit Attitudes and Identity. Nature Scientific Data.