Bias refers to systematic or nonrandom error. Bias causes the observed value to deviate from the true value. It can weaken the association or generate a spurious association. Because all studies are susceptible to bias, a key goal is to minimize bias or to adjust the observed value of the association using special methods to correct for bias. There are three general sources of error that may compromise the results of an investigation, including selection bias, confounding, and information bias.
Selection bias can occur in the recruitment of study subjects to a cohort when the study and control groups differ from each other by a factor that is likely to affect the results. Thus, the observed cohort differs from the population at large by some unmeasured variable that could predict the outcome. Non-population-based cross-sectional studies are particularly vulnerable to selection bias.
Confounding occurs when a variable or characteristic can account for part or all of an apparent association. For example, if inhaled uranium particles appear to be associated with the development of lung cancer, cigarette smoking may confound this outcome if the cohort exposed to uranium had more members that smoked than the unexposed cohort. Confounding variables can be either measured or unmeasured. With measured confounders, carefully applied statistical adjustments can control for or reduce their influence. With unmeasured confounders, no adjustment is possible. With studies of uranium miners, for example, it is usually not possible to adjust for the role of cigarette smoking by individuals, since the employee records of decades ago seldom contained information about smoking.
Information bias results from the way in which the data are collected, for example, from measurement errors, imprecise measurement, and misdiagnosis. These types of errors may be uniform across the entire study population or may affect some parts of the population more than others. Bias may result from misclassification of study subjects with respect to the outcome variable. Other common sources of information bias are due to the inability of study subjects to accurately recall the circumstances of the exposure (recall bias) or to the likelihood that one group more frequently reports what it remembers than another group (reporting bias). Information bias is especially pernicious when it affects one comparison group more than another.
As seen below in the discussion of categories of association, the committee distinguishes between “sufficient evidence of a causal relationship” and “sufficient evidence of an association.” Thus, before describing the categories used to summarize its findings, the committee provides a brief discussion of the concepts of causation and association.