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Reproducibility, closely related to replicability and repeatability, is a major principle underpinning the scientific method.For the findings of a study to be reproducible means that results obtained by an experiment or an observational study or in a statistical analysis of a data set should be achieved again with a high degree of reliability when the study is replicated.
The study also found that most Germans have positive perceptions of replication efforts: only 18% think that non-replicability shows that science cannot be trusted, while 65% think that replication research shows that science applies quality control, and 80% agree that errors and corrections are part of science.
Goodman, Fanelli and Ioannidis define method reproducibility as "the provision of enough detail about study procedures and data so the same procedures could, in theory or in actuality, be exactly repeated." [2] This acception is largely synonymous with replicability in a computational context or reproducibility in an experimental context. In ...
In engineering, science, and statistics, replication is the process of repeating a study or experiment under the same or similar conditions to support the original claim, which is crucial to confirm the accuracy of results as well as for identifying and correcting the flaws in the original experiment. [1]
The Reproducibility Project is a series of crowdsourced collaborations aiming to reproduce published scientific studies, finding high rates of results which could not be replicated. It has resulted in two major initiatives focusing on the fields of psychology [ 1 ] and cancer biology. [ 2 ]
In addition to the main result, Ioannidis lists six corollaries for factors that can influence the reliability of published research. Research findings in a scientific field are less likely to be true, the smaller the studies conducted. the smaller the effect sizes. the greater the number and the lesser the selection of tested relationships.
This approach is valuable in fields where research findings are sensitive to the methods of data analysis, such as psychology, [4] neuroscience, [5] economics, and social sciences. Multiverse analysis aims to mitigate issues related to reproducibility and replicability by revealing how different analytical choices can lead to different ...
An attribute agreement analysis is designed to simultaneously evaluate the impact of repeatability and reproducibility on accuracy. It allows the analyst to examine the responses from multiple reviewers as they look at several scenarios multiple times.