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bias

 [bi´as]
1. (in a measurement process) systematic error.
2. any influence or action at any stage of a study that systematically distorts the findings.
3. (of a statistical estimator) the difference between the expected value of the estimator and the true parameter value.

bi·as

(bī'-as),
1. Systematic discrepancy between a measurement and the true value; may be constant or proportionate and may adversely affect test results.
2. Any trend in the collection, analysis, interpretation, publication, or review of data that can lead to conclusions that differ systematically from the truth; deviation of results or inferences from the truth, or processes leading to deviation.
[Fr. biais, obliquity, perh. fr. L. bifax, two-faced]

There is no imputation of prejudice, partisanship, or other subjective or emotional factor such as an investigator's desire to achieve a particular outcome. More than 100 varieties of bias have been described, but all fall into a small number of classes: 1. Systematic one-sided variation of measurements from the true value. SYN systematic error, instrumental error 2. Variation of statistical summary measures (means, rates, measures of association) from their true values as a result of systematic variation of measurements, other flaws in data collection, or flaws in study design or analysis. 3. Deviation of inferences from the truth as a result of flaws in study design, data collection, or the analysis or interpretation of results. 4. A tendency of procedures in study design, data collection, analysis, interpretation, review or publication, to yield results or conclusions that depart from the truth. 5. Prejudice leading to the conscious or subconscious selection of study procedures that depart from the truth in a particular direction, or to one-sidedness in interpretation of results. This last form of bias can arise as a result of shoddy scientific methods or deliberate misrepresentation of the truth by investigators.

bias

[bī′əs]
Etymology: MFr, biais
1 an oblique or a diagonal line.
2 a prejudiced or subjective attitude.
3 (in statistics) the distortion of statistical findings from the true value. There can be many kinds of bias; some may be caused by the sampling process, but bias can be caused by other factors.
4 (in electronics) a voltage applied to an electronic device, such as a vacuum tube or a transistor, to control operating limits. See also detection bias.

bias

Epidemiology Deviation of results or inferences from the truth, or processes leading to such systematic deviation; any trend in the collection, analysis, interpretation, publication, or review of data that can lead to conclusions that are systematically incorrect

bi·as

(bī'ăs)
1. Systematic discrepancy between a measurement and the true value; may be constant or proportionate and may adversely affect test results.
2. Any trend in the collection, analysis, interpretation, publication, or review of data that can lead to conclusions that differ systematically from the truth; deviation of results or inferences from the truth, or processes leading to deviation.
[Fr. biais, obliquity, perh. fr. L. bifax, two-faced]

bi·as

(bī'ăs)
1. Systematic discrepancy between a measurement and the true value; may be constant or proportionate and may adversely affect test results.
2. Any trend in the collection, analysis, interpretation, publication, or review, which can lead to conclusions that differ systematically from the truth; deviation of results or inferences from the truth, or processes leading to deviation.
[Fr. biais, obliquity, perh. fr. L. bifax, two-faced]

bias,

n in statistics, the systematic distortion of a statistic caused by a particular sampling process.

bias

any systematic error in the design, conduct or analysis of a study which results in estimates which depart from true values. An unbiased study is free from systematic error. Many types of bias have been named, but three general types can be identified, selection bias, information bias and confounding. Selection bias is a systematic error in a study caused by the individuals selected into the study being different from the entire target population in an important way. See also berkson's bias. Information bias is a systematic error in a study caused by errors in the data which are collected in the study, or in the analysis of the data.
References in periodicals archive ?
Self-awareness has the potential to mitigate the impact of the biases," the study states.
The Skilled Counselor Training Model is one method that might be used to foster skill in controlling subtle interpersonal biases (Crews et al.
Fung and Hsieh [50] make similar arguments, where they discuss the information content and potential measurement biases in hedge fund benchmarks.
Although biases are destructive, one reason that we cling to them is that they contain what psychologists call secondary gains.
Then there are the biases endemic to journalism: The belief in journalistic omniscience; favoring controversy over conciliation; sensationalism and celebrity; the "gotcha" story; "focusing only on problems and not solutions.
I think that the renewed interest is due to two factors: BLS economists have been at the forefront of recent research on biases and their studies are very credible and hence are taken seriously; and there is some evidence of paradigm shift in the economics of the firm.
2) In a multiple-bias incident, two conditions must be met: (a) more than one offense type must occur in the incident and (b) at least two offense types must be motivated by different biases.
AII participants in scientific review panels should disclose sources of potential biases and conflicts of interest.
Stories that confirm those biases will receive inadequate vetting, leading to factual errors.
Two manuscripts recently have been published in Rapid Communications in Mass Spectrometry [RCM 17, 771-776 (2003) and RCM 17, 777-782 (2003)] that detail an international collaboration to identify, understand at a fundamental level, and correct measurement biases manifested in gas isotope ratio mass spectroeters.
A discussion of implications for teacher education and staff development focuses on assessment of student perspectives, identifying one's own biases, learning by doing, and committing more firmly to multicultural education.
Much of our litigation seeks to correct errors and overturn unjust outcomes that result from personal and societal biases, all too frequently not left outside the courtroom door.