Search results
Results from the WOW.Com Content Network
The effect(s) of such misclassification can vary from an overestimation to an underestimation of the true value. [4] Statisticians have developed methods to adjust for this type of bias, which may assist somewhat in compensating for this problem when known and when it is quantifiable. [5]
This statistics -related article is a stub. You can help Wikipedia by expanding it.
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 ...
Detection bias occurs when a phenomenon is more likely to be observed for a particular set of study subjects. For instance, the syndemic involving obesity and diabetes may mean doctors are more likely to look for diabetes in obese patients than in thinner patients, leading to an inflation in diabetes among obese patients because of skewed detection efforts.
Notable bias (spin) has been reported in the interpretation of results of randomized control trials, although these study designs rank top in the level-of-evidence hierarchy. [36] [37] [38] Contrastingly, a study found low prevalence of bias in the conclusions of non-randomized control trials published in high-ranking orthopedic publications. [39]
Observer bias is one of the types of detection bias and is defined as any kind of systematic divergence from accurate facts during observation and the recording of data and information in studies. [1] The definition can be further expanded upon to include the systematic difference between what is observed due to variation in observers, and what ...
In addition to the main result, Ioannidis lists six corollaries for factors that can influence the reliability of published research. Research findings in a scientific field are less likely to be true, the smaller the studies conducted. the smaller the effect sizes. the greater the number and the lesser the selection of tested relationships.
Epidemiological (and other observational) studies typically highlight associations between exposures and outcomes, rather than causation. While some consider this a limitation of observational research, epidemiological models of causation (e.g. Bradford Hill criteria) [7] contend that an entire body of evidence is needed before determining if an association is truly causal. [8]