Is it dishonest to remove outliers and/or transform data?
Почем лучок пучок,
There is no dishonesty in removing an outlier if that “participant” didn’t follow instructions and just tapped one button repeatedly. If it clearly affects the mean greatly and do not represent true scores then it should be removed. Although there are reasons to remove outliers or transform data, some may do it without a decent reason. Say, you ran research – it took many years, lots of money at stake, career and reputation and tons of pressure to find significant result. Some may falsify the data; hide certain aspects of results to present significant or at least desirable results. Of course, it is hypothetical again. People won’t do it. But it happens, because science is a career-driven discipline. Good reputation provides researchers with funding and ongoing support. Check this guy out who fell to the dark side of conducting research
For such reasons it is dishonest to transform data. But there are legitimate reasons for removing outliers. For example, not following instructions as I mentioned previously or when participants didn’t understand instructions, withdrew from the experiment or some other factors that I can’t think about now. Nevertheless, you have to be very careful deciding whether remove outliers or not, because outliers might occur due to measurement error or simply by chance. It should be thoroughly examined whether after removing the outlier the sample still represents the population, how greatly it affects the results and so on.
It is not dishonest to remove the outlier if there are thoroughly considered decisions, well-weighted reasons behind that, but it’s unfair if there are no such things 🙂
For every move you make there is a certain reason.