I strongly believe in the value of openness and transparency in science. In light of recent meta-scientific discoveries and developments (e.g., replication crisis, identification of questionable research practices, meta-analytical evidence for publication bias, etc.), I strongly advocate for making all materials (e.g., items, stimuli, coding procedures, etc.), data (if possible), and analysis scripts available to the public. Next to this website, you can find most of the data that I collected over the years on my OSF page.
I believe sharing data, materials, and scripts is important not only for evaluating a study’s contribution and methodological soundness, but also to allow other researchers to reproduce the study computationally, replicate it independently, or include it in meta-analyses. In the last years, I have published several datasets that can be used for scientific purposes. If you have any questions about the data or are interested in collaborating on an analysis, please feel free to reach out.
Datasets focusing on Privacy and Self-Disclosure
- Trepte, S., Masur, P. K. & Dienlin, T. (2019). A longitudinal survey on privacy concerns, literacy, disclosure, support. (5 waves, representative for the German population). GESIS Datorium: https://datorium.gesis.org/xmlui/handle/10.7802/1937
- Masur, P. K. & Scharkow, M. (2016). A cross-sectional survey on privacy and self-disclosure on social media. Open Science Framework: https://osf.io/8bzxd/
Other Datasets
- Bauer, A., Loy, L. S., Masur, P. K. & Schneider, F. M. (2018). A diary study on instant messaging and mindfulness. Open Science Framework: https://osf.io/nmf27/
