Information bias arises when there are systematic errors in how data are measured, collected, or classified, leading to inaccurate estimates of associations or effects. This type of bias can distort the true relationship between variables.
For example, in a dietary study, if participants consistently underreport how many calories they consume, the analysis may underestimate the association between diet and weight change.
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