Bias

Systematic error, or 'bias' is of particular importance in any epidemiological investigation, and should be avoided wherever possible. As with random error, biases will reduce the accuracy of any results obtained, but they also have the potential to reduce the validity of results. Although confounding is considered by many authors as a form of bias, it is covered separately.

There are a number of types of bias, which may be classified broadly as either selection bias or information bias, and which will differ in the case of different study designs.

Selection bias

Selection bias affects inclusion of individuals in the study and results in the study sample not being representative of the source population. This may occur in the initial selection process, or may be a result of nonresponse or losses to follow up during the study period. The mechanisms by which selection bias can enter a study will depend on the study design:

Descriptive or cross sectional studies

In these studies, lack of compliance may result in selection bias, as participation amongst selected individuals is very rarely 100% in these cases.

Case-control studies

The main source of selection bias in case-control studies is through the selection of the control group. It is of vital importance that the control group comes from the same population as the case group (that is, if they happened to experience the outcome of interest during the study period, they would have been classified as a case instead of a control), and that there is no association between exposures of interest and selection as a control. The selection of the cases can also result in selection bias - in particular, in the case of hospital-based studies, where cases are selected from hospitals (as the population from which these individuals were drawn from makes selection of controls very difficult).

Cohort studies

Selection bias in cohort studies is generally less likely than in other studies, as selection for participation in the study generally precedes the development of the outcome of interest. However, losses to follow-up provide a mechanism by which selection bias may be introduced. For example, in the case of a perceived 'risky behaviour', it is plausible that individuals engaged in this may be less likely to remain in the study, meaning that these individuals (which may be more likely to experience the outcome) will be lost from the study.

Information bias

Information bias results from errors in measurement or classification of exposures or outcomes of interest amongst the individuals included in the study. In the case of analytic studies, this may be classified as differential or non-differential (or measurement error):

• Differential bias occurs when the chance of bias is different for the different groups being compared. For example, in a study investigating whether Boxer dogs have a higher incidence of mast cell tumours than other breeds, Boxers may be more likely to be diagnosed by vets as having these, due to a postulated breed disposition.
• Non-differential bias occurs when the chance of bias is not affected by the group the individuals belong to.

Non-differential bias will tend to reduce the strength of any association present, and will increase the probability of a type II error, whereas the effect of differential bias cannot be predicted.