Table of contents
Bias
A study is biased if some aspects of the design, sampling, data collection or analysis method produce results that systematically overestimate or underestimate the strenght of association. In particular, bias may arise from selection bias, information bias or confounding.
Selection bias
In survey sampling, the bias that results from an unrepresentative sample is called selection bias. Some common examples of selection bias are described below.
Information bias
Information bias is any systematic difference from the truth that arises in the collection, recall, recording and handling of information in a study, including how missing data is dealt with.
Confounding
A confounder is a variable that influences both the dependent variable and independent variable, causing a spurious association. Confounding is a causal concept, and as such, cannot be described in terms of correlations or associations.