Organize your study to provide the clearest possible answer, then trust in the objectivity of the data rather than looking for the desired outcome.
Ensure the target population is fully represented (e.g. if the study researches impacts on all adults, do not gather data just from a single sex or age).
Minimize risks to subjects, fellow researchers, and the environment.
Use resources wisely. Determine the appropriate number of observations needed to achieve the goal.
Determine criteria for excluding data prior to gathering data, discuss it with others, and include exclusion criteria in any publications.
Describe the experimental controls, plans to reduce bias (e.g. blinding, randomization), power analyses, and statistical methods.
Include a plan to follow data storage and sharing requirements and best practices
Rigor and reproducibility
- High quality study design, data collection, and data analysis are key to producing rigorous and responsible research.
- Scientific rigor is the strict application of the scientific method to ensure unbiased and well-controlled experimental design, methodology, analysis, interpretation and reporting of results. (NIH)
- Scientific rigor is necessary to produce quality data.
- Reproducibility strives to bring transparency to research, allowing others to independently verify your methods and analysis. This transparency also allows the data to be used by others (with proper credit) to make research more effective.