Bias in Statistics > Information Bias
What is Information Bias?
Information bias (also called observation bias or measurement bias) happens when key information is either measured, collected, or interpreted inaccurately. According to John’s Hopkins, it’s when:
“…information is collected differently between two groups, leading to an error in the conclusion of the association.”
This broad category contains Observer Bias, which happens when a researcher is aware of a disease or exposure status, and Recall Bias, where a patient is more likely to remember past details about their disease if they have the disease.
MisclassificationMisclassification — basically incorrect information — happens for a variety of reasons and can be broken down into two types: differential misclassification and non-differential misclassification:
1. Nondifferential misclassification happens when the information is incorrect, but is the same across groups.
In case-control studies, it happens when exposure status is incorrect for both controls and cases.
In cohort studies, it happens when exposure status is incorrect for people with the disease and those without the disease.
2. Differential misclassification happens when the information errors differ between groups. In other words, the bias is different for exposed and non-exposed, or between those who have the disease and those do have not.
Misclassification can be a result of:
- Incomplete medical records.
- Recording errors in records.
- Misinterpretation of records.
- Errors in records, like incorrect disease codes, or patients completing questionnaires incorrectly (perhaps because they don’t remember or misunderstand the question).
How to Control Information Bias
- Implement standardized protocols for collecting data across groups.
- Ensure that researchers and staff do not know about exposure/disease status of study participants. Implement blinding if possible.
- Train interviewers to collect information using standardized methods.
- Try to get information from two different sources, such as the participant and the participant’s spouse.
- Implement strategies to identify potential sources of bias.
If you prefer an online interactive environment to learn R and statistics, this free R Tutorial by Datacamp is a great way to get started. If you're are somewhat comfortable with R and are interested in going deeper into Statistics, try this Statistics with R track.