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Measurement bias results from poorly measuring the outcome you are measuring. For example:
- The survey interviewers asking about deaths were poorly trained and included deaths which occurred before the time period of interest.
- This would lead to an overestimate of the mortality rate because deaths which should not be included are included.
- One survey team's portable machine to measure haemoglobin malfunctioned and was not checked, as should be done every day. It measured everyone's haemoglobin as 0.3 g/L too high.
- This would lead to an underestimate of the prevalence of anaemia because the readings would overestimate the haemoglobin for everyone measured by that team.