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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 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 engineering, science, and statistics, replication is the process of repeating a study or experiment under the same or similar conditions. It is a crucial step to test the original claim and confirm or reject the accuracy of results as well as for identifying and correcting the flaws in the original experiment. [1]
Reproducibility in the narrow sense refers to re-examining and validating the analysis of a given set of data. Replication refers to repeating an existing experiment or study using new, independent data with the goal of verifying the original conclusions.
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 ...
However, certain conditions must be met before the replication of the experiment is commenced: the original research question has been published in a peer-reviewed journal or widely cited, the researcher is independent of the original experiment, the researcher must first try to replicate the original findings using the original data, and the ...
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.
Scientific writing requires transparency in reporting research methods, data collection procedures, and analytical techniques to ensure the reproducibility and reliability of findings. Authors are responsible for accurately representing their data and disclosing any conflicts of interest or biases that may influence the interpretation of results.