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Research misconduct refers to deliberate or accidental manipulation or misrepresentation of research data, findings, or processes. It can take many forms, such as fabricating data, plagiarism, or failing to disclose conflicts of interest. Data falsification is a serious problem in the field of medical research, as it can lead to the promotion of false or misleading information. Researchers might engage in p-hacking - the practice of using someone else's research results or ideas without giving them proper attribution. Conflict of interest (COI) occurs when an individual's personal, financial, or professional interests could potentially influence their judgment or actions in relation to their research. Nondisclosure of COI can be considered research misconduct and can damage the reputation of the authors and institutions. Hypothesis after results are known can lead to the promotion of false or misleading information. Cherry-picking data is the practice of focusing attention on certain data points or results that support a particular hypothesis, while ignoring or downplaying results that do not. Researchers should be transparent about their methods and report their findings honestly and accurately. Research institutions should have clear and stringent policies in place to address scientific misconduct. This knowledge must become widespread, so that researchers and readers understand what approaches to statistical analysis and reporting amount to scientific misconduct. It is imperative that readers and researchers alike are aware of the methods of statistical analysis and reporting that constitute scientific misconduct.
Rao et al. (Mon,) studied this question.