1) information bias-is a distortion of information/which can affect decisions
2)selection bias- can be due to misclassification and measuring errors
3) confounding- the results are so mixed up that they are going against each other.
Examples:
- 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).
- Biases are beliefs that are not founded by known facts about someone or about a particular group of individuals. For example, one common bias is that women are weak (despite many being very strong). Another is that blacks are dishonest (when most aren't).
- In this article, we consider 5 types of selection bias:
- the non-response bias (example 1), the incidence-prevalence bias (examples 2 and 3), the loss-to-follow-up bias (example 4), the confounding by indication bias (example 5) and the volunteer bias (example 6).
- For example, a study looking at the association between obesity and heart disease might be confounded by age, diet, smoking status, and a variety of other risk factors that might be unevenly distributed between the groups being compared.
