Information bias occurs when any information used in a study is either measured or recorded inaccurately. This paper describes some of the most common types of information bias, using examples from obstetrics and gynecology, and describes how information bias may affect results of observational studies. Non‐differential misclassification occurs when the degree of misclassification of exposure status among those with and those without the disease is the same; in cohort studies, this type of bias is most likely and will bias estimates toward no association when exposure is dichotomized. Non‐differential underreporting of an exposure with more than two categories may mask a true threshold effect as a dose‐response relation and, if a true threshold effect exists, the threshold will be set at too low a level, if the exposure is underreported. Differential misclassification may cause bias in either direction and is particularly likely, when exposure status is reported after the outcome occurred. Misclassification of confounders is an issue that needs special attention by researchers, as failure to measure accurately one or more (strong) confounders may seriously bias the observed results. Misclassification of disease status may also cause bias of estimates of association in either direction. Information bias is probably best prevented during planning of data collection, as there are few and insufficient methods available for correcting inaccurate information.