3. What are potential sources of bias, and is it likely that any of these will have a substantial effect on the observed results? When describing an observational study, you should acknowledge that you are aware of potential sources of bias and explain any steps that were taken to minimize their effect. For example, in a mail survey, nonresponse can be a problem, but the sampling plan may seek to minimize its effect by offering incentives for participation and by following up one or more times with those who do not respond to the first request.

A common misperception is that increasing the sample size is a way to reduce bias in observational studies, but this is not the case. For example, if measurement bias is present, as in the case of a scale that is not correctly calibrated and tends to weigh too high, taking 1000 measurements rather than 100 measurements cannot correct for the fact that the measured weights will be too large. Similarly, a larger sample size cannot compensate for response bias introduced by a poorly worded question.