Ascertainment Bias
Ascertainment Bias : Systematic error, arising from the kind of individuals or patients (e.g., slightly ill, moderately ill, acutely ill) that the individual observer is seeing. Also systematic error arising from the diagnostic process (which may be determined by the culture, customs, or individual idiosyncrasy of the person providing care for the patient)... Bias Due To Instrumental Error: Systematic error due to faulty calibration, inaccurate measuring instruments, contaminated reagents, incorrect dilution or mixing of reagents, etc.... Bias Due To Withdrawals: A difference between the true value and that actually observed in a study due to the characteristics of those subjects who choose to withdraw.... Bias, In Assumption: (Syn: Conceptual Bias) Error arising from faulty logic or premises or mistaken beliefs on the part of the investigator. False conclusions about the explanation for associations between variables. Example: Having correctly deduced the mode of transmission of cholera, John Snow concluded that yellow fever was transmitted by similar means. In fact, the "miasma" theory would better fit the facts of yellow fever transmission.... Bias in Autopsy Series: Systematic error resulting from the fact that autopsies represent a nonrandom sample of all deaths.... Bias in Handling Outliers: Error arising from a failure to discard an unusual value occurring in a small sample, or due to exclusion of unusual values that should be included.... Bias in Publication: An editorial predilection for publishing particular findings, e.g., positive results, which leads to the failure of authors to submit negative findings for publication. This can distort the general belief about what has been demonstrated in a particular situation.... Bias in The Presentation of Data: Error due to irregularities produced by digit preference, incomplete data, poor techniques of measurement, or technically poor laboratory standards.... Bias of Interpretation: Error arising from inference and speculation. Sources of the error include (1) failure of the investigator to consider every interpretation consistent with the facts and to assess the credentials of each, and (2) mishandling of cases that constitute exceptions to some general conclusion.... Design Bias: The difference between a true value and that actually obtained, occurring as a result of faulty design of a study. Some examples are (1) uncontrolled studies where the effects of two processes cannot be separated (confounding), (2) controlled studies where observations are based on a poorly defined population, and (3) nonsimultaneous comparisons.... Detection Bias: Due to systematic error(s) in methods of ascertainment, diagnosis, or verification of cases in an epidemiologic survey, study, or investigation. Example: Verification of diagnosis by laboratory tests in hospital cases, but failure to apply the same tests to cases outside hospital.... Information Bias: (Syn: Observational Bias) A flaw in measuring exposure or outcome that results in differential quality (accuracy) of information between compared groups.... Interviewer Bias: Systematic error due to interviewers' subconscious or even conscious gathering of selective data.... length Bias: A systematic error due to the selection of a disproportionate number of long_duration cases (cases who survive longest) in one group and not in the other. Can occur when prevalent cases, rather than incident cases, are included in a case control study.... "Lead_Time" Bias: A systematic error arising when follow_up of two groups does not begin at strictly comparable times. Occurs especially when one group has been diagnosed earlier in the natural history of the disease than the other group.... Measurement Bias: Systematic error arising from inaccurate measurement (or classification) of subjects on the study variables.... Observer Bias: Systematic difference between a true value and that actually observed due to observer variation. Observer variation may be due to differences among observers (interobserver variation) or to variation in readings by the same observer on separate occasions (intraobserver variation).... Recall Bias: Systematic error due to differences in accuracy or completeness of recall to memory of prior events or experiences. Example: Mothers whose children have had or have died of leukemia are more likely than mothers of healthy living children to remember details of diagnostic x_ray examinations to which these children were exposed in utero.... Reporting Bias: Selective suppression or revealing of information such as past history of sexually transmitted disease.... Response Bias: Systematic error due to difference in characteristics between those who choose or volunteer to participate in a study and those who do not.... Sampling Bias: Unless the sampling method ensures that all members of the "universe" or reference population have a known chance of selection in the sample, bias is possible. The best way to ensure a known chance of selection for all is to use a probability sampling method such as a table of random numbers.... Selection Bias (Berkson's Bias): Error due to systematic differences in characteristics between those who are selected for study and those who are not. Examples include hospital cases or cases under a physician's care, excluding those who die before admission to hospital because the course of their disease is so acute, those not sick enough to require hospital care, or those excluded by distance, cost, or other factors. Selection bias also invalidates generalizable conclusions from surveys which would include only volunteers from a healthy population. A special example is Berkson's Bias, which Berkson characterized as the set of selective factors that lead hospital cases and controls in a case control study to be systematically different from one another. This occurs when the combination of exposure and disease under study increases the risk of hospital admission, thus leading to a systematically higher exposure rate among the hospital cases than the hospital controls. This in turn results in systematic distortion of the odds ratio. [from Berkson, J., Limitations of the application of fourfold table analysis to hospital data, Biometrics Bull, 2: 47_53, 1946.] [Last, 1983: A Dictionary of Epidemiology]; (c) An inclination that influences judgment. The term "bias" may be used in a merely descriptive way to mean an inclination, but more often it is used as a term of evaluation to mean an inclination that influences judgment and ought not to. "Prejudice" is a synonym for bias in this pejorative sense. However, bias that cannot be completely eliminated in the work of scientific investigators, in contrast to bias or prejudice that can and should be eliminated, is also an important topic in research ethics. For example, the way disciplinary training inclines people to interpret the results of an experiment in terms of the established categories of that discipline is a feature of research, and one that must be taken into account in assessing responsible behavior in research. Since undertaking research requires undergoing advanced training in a discipline, it is impossible to eliminate all preconceptions from one's interpretation of the data. of course, researchers may hold disciplinary biases and still be unbiased in other respects. For example, they may be impartial on the question of the truth or falsity of a particular research hypothesis. [OECES, 1998: Online Ethics Glossary]; (d) Any difference between the true value and that actually obtained due to all causes other than sampling variability. [SRA, 1999: Glossary of Risk Analysis Terms]; (e) Any difference between the true value and that actually obtained due to all causes other than sampling variability. [USDOE, 2000: RAIS Glossary]; (f) A systematic error inherent in a method or caused by some feature of the measurement system. [USEPA, 1992: GL for Exposure Assessment]
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