Search results
Results from the WOW.Com Content Network
Participation bias or non-response bias is a phenomenon in which the results of studies, polls, etc. become non-representative because the participants disproportionately possess certain traits which affect the outcome. These traits mean the sample is systematically different from the target population, potentially resulting in biased estimates.
A survey using a Likert style response set. This is one example of a type of survey that can be highly vulnerable to the effects of response bias. Response bias is a general term for a wide range of tendencies for participants to respond inaccurately or falsely to questions.
Recall bias is of particular concern in retrospective studies that use a case-control design to investigate the etiology of a disease or psychiatric condition. [ 3 ] [ 4 ] [ 5 ] For example, in studies of risk factors for breast cancer , women who have had the disease may search their memories more thoroughly than members of the unaffected ...
It is a type of systemic bias. Language and educational issues can lead to a misunderstanding of the question by the respondent, or similarly, a misunderstanding of the response by the surveyor. Recall bias can lead to misinformation based on a respondent misrecalling the facts in question.
For example, when getting to know others, people tend to ask leading questions which seem biased towards confirming their assumptions about the person. However, this kind of confirmation bias has also been argued to be an example of social skill; a way to establish a connection with the other person. [9]
In social science research social-desirability bias is a type of response bias that is the tendency of survey respondents to answer questions in a manner that will be viewed favorably by others. [1] It can take the form of over-reporting "good behavior" or under-reporting "bad" or undesirable behavior.
Nonsampling error, which occurs in surveys and censuses alike, is the sum of all other errors, including errors in frame construction, sample selection, data collection, data processing and estimation methods.
Bias implies that the data selection may have been skewed by the collection criteria. Other forms of human-based bias emerge in data collection as well such as response bias, in which participants give inaccurate responses to a question. Bias does not preclude the existence of any other mistakes.