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[3] Using an audit protocol tool, it was identified that human entry errors range from 0.01% when entering donors' clinical follow-up details, to 0.53% when entering pathological details, highlighting the importance of an audit protocol tool in a medical research database.
A type II error, or a false negative, is the erroneous failure in bringing about appropriate rejection of a false null hypothesis. [1] Type I errors can be thought of as errors of commission, in which the status quo is erroneously rejected in favour of new, misleading information. Type II errors can be thought of as errors of omission, in which ...
There is no single definition of diagnostic error, reflecting in part the dual nature of the word diagnosis, which is both a noun (the name of the assigned disease; diagnosis is a label) and a verb (the act of arriving at a diagnosis; diagnosis is a process).
Generally speaking, there are three main approaches to handle missing data: (1) Imputation—where values are filled in the place of missing data, (2) omission—where samples with invalid data are discarded from further analysis and (3) analysis—by directly applying methods unaffected by the missing values. One systematic review addressing ...
The false positive rate (FPR) is the proportion of all negatives that still yield positive test outcomes, i.e., the conditional probability of a positive test result given an event that was not present.
A reconstruction of the skull purportedly belonging to the Piltdown Man, a long-lasting case of scientific misconduct. Scientific misconduct is the violation of the standard codes of scholarly conduct and ethical behavior in the publication of professional scientific research.
Research integrity or scientific integrity became an autonomous concept within scientific ethics in the late 1970s. In contrast with other forms of ethical misconducts, the debate over research integrity is focused on "victimless offence" that only hurts "the robustness of scientific record and public trust in science". [3]
In scientific inquiry and academic research, data fabrication is the intentional misrepresentation of research results. As with other forms of scientific misconduct, it is the intent to deceive that marks fabrication as unethical, and thus different from scientists deceiving themselves. There are many ways data can be fabricated.