Observational bias (also called observation bias or ascertainment bias) refers to systematic errors in the measurement, recording, or interpretation of data that occur due to the observer's expectations, knowledge, or study design.

It can affect the validity of results in both clinical and epidemiological research, especially in non-randomized or open-label studies.

• Detection bias: Outcomes are more likely to be observed in one group due to increased monitoring or surveillance.
• Observer bias: The person collecting data intentionally or unintentionally distorts measurements due to prior beliefs or expectations.
• Reporting bias: Selective recording or emphasis of certain outcomes over others.
• Recall bias (in self-reported data): Patients may remember or report information differently depending on exposure or outcome status.

In an unblinded clinical trial, a physician who knows which patients are receiving the active drug may more closely monitor them and detect side effects that go unnoticed in the control group — artificially inflating adverse event rates.

• Blinding of participants and investigators
• Standardized protocols for data collection
• Objective outcome measures
• Use of independent adjudicators

• Selection Bias
• Information Bias
• Confirmation Bias