What type of research misconduct involves data manipulation?

The type of research misconduct that specifically involves data manipulation is falsification. Falsification occurs when researchers alter or misrepresent data or results, often to make them appear more favorable or acceptable than they are in reality. This can involve changing measurements, omitting data points, or selectively reporting results to mislead others about the validity of the findings.

Understanding this definition is critical in biomedical research, as falsification undermines the integrity of research results and can have far-reaching implications for scientific progress, public trust in research, and patient safety. Research integrity relies on honest and transparent reporting of data, and when scientists engage in falsification, they violate ethical standards designed to ensure valid and reliable scientific inquiry.

By contrasting this with the other options: fabrication refers to inventing data or results that have not been obtained; plagiarism involves using someone else's work or ideas without proper attribution; and improper authorship refers to issues surrounding who is credited for the research work, rather than how the data itself is handled. Each of these activities represents serious ethical breaches in research, but it is falsification that directly addresses the manipulation of data.