Bias is a form of systematic error that can affect scientific investigations and distort the measurement process. A biased study loses validity in relation to the degree of the bias.
There are many different types of biases; the most common categories that can affect the validity of research are the following:
1)
Selection biases, which may result in the subjects in the sample being unrepresentative of the population of interest
2)
Measurement biases, which include issues related to how the outcome of interest was measured
3)
Intervention (exposure) biases, which involve differences in how the treatment or intervention was carried out, or how subjects were exposed to the factor of interest
It is difficult or even impossible to completely eliminate bias. Therefore, the goals are to minimize bias and for both investigators and readers to comprehend its residual effects, limiting misinterpretation and misuse of data.
See reference for details. Adapted from Krishna R, Maithreyi R, Surapaneni K M. Research bias: a review for medical students. Journal of Clinical and Diagnostic Research, 2010; 4:2320-2324. Internet. Accessed on May 23, 2016.