A major principle of the scientific method is replication, or the ability of an experiment or study to be duplicated. A similar idea is “reproducible research,” – that the results of a study can be reproduced given the raw data and the analysis protocols or methods (usually in code, script, or syntax form). With full transparency, the reader has the ability to evaluate all the analytical decisions that led to the study conclusion.
The concept of reproducible research has gained recent attention in the research world due to the rise of the number of published articles, the increasing complexity of data analysis, and the alarming recent rise in retraction rates.
This workshop covers ethical issues in data analysis, including concepts such as HARKing, P-hacking, Fishing Expeditions and the File Drawer Effect. It also covers possible solutions to these issues, including strategies that can be adopted locally by the research team, as well as changes to publishing practices that can affect paradigm shifts in entire fields of research.