Bias

{
  "id": "MLC-T-ENV-003085",
  "term": "Bias",
  "field": "Environment",
  "definition": "1. Systematic deviation between a measured (i.e., observed) or computed value and its \"true\" value. Bias is affected by faulty instrument calibration and other measurement errors, systematic errors during data collection, and sampling errors such as incomplete spatial randomization during the design of sampling programs.\n\n2. An inadequacy in experimental design that leads to results or conclusions not representative of the population under study.\n\n3. The extent to which a measurement, sampling, or analytic method systematically underestimates or overestimates the true value of an attribute. For example, words, sentence structure, attitudes, and mannerisms may unfairly influence a respondent's answer to a question. Bias in questionnaire data can stem from a variety of other factors, including choice of words, sentence structure, and the sequence of questions.\n\n4. A systematic (consistent) error in test results. Bias can exist between test results and the true value (absolute bias, or lack of accuracy), or between results from different sources (relative bias). For example, if different laboratories analyze a homogeneous and stable blind sample, the relative biases among the laboratories would be measured by the differences existing among the results from the different laboratories. However, if the true value of the blind sample were known, the absolute bias or lack of accuracy from the true value would be known for each laboratory. See Systematic error.\n\n5. The systematic or persistent distortion of a measurement process that causes errors in one direction (i.e., the expected sample measurement is different from the sample's true value).\n\n6. The systematic or persistent distortion of a measurement process which causes errors in one direction (i.e., the expected sample measurement is different from the true value).\n\n7. The systematic or persistent distortion of a measurement process which causes errors in one direction (i.e., the expected sample measurement is different from the sample's true value).\n\n8. The level of agreement between an observed value and the \"true\" value of a characteristic.\n\n9. A systematic error inherent in a method or caused by some feature of the measurement system.\n\n10. In a sampling context, the difference between the conceptual weighted average value of an estimator over all possible samples and the true value of the quantity being estimated. An estimator is said to be unbiased if that difference is zero. The \"systematic or persistent distortion of a measurement process which deprives the result of representativeness (i.e., the expected sample measurement is different than the sample's true value). A data quality indicator\" (QAMS 1993, 3).\n\n11. Systematic error introduced into sampling or analysis by selecting or encouraging one outcome or answer over others.\n\n12. A set of standard criteria for deciding whether a person has a particular disease or health-related condition, by specifying clinical criteria and limitations on time, place, and person.\n\n13. In general, any factor that distorts the true nature of an event or observation. In clinical investigations, a bias is any systematic factor other than the intervention of interest that affects the magnitude of (i.e., tends to increase or decrease) an observed difference in the outcomes of a treatment group and a control group. Bias diminishes the accuracy (though not necessarily the precision) of an observation. Randomization is a technique used to decrease this form of bias. Bias also refers to a prejudiced or partial viewpoint that would affect someone’s interpretation of a problem. Double blinding is a technique used to decrease this type of bias.\n\n14. The constant or systematic distortion of a measurement process, different from random error, which manifests itself as a persistent positive or negative deviation from the known or true value. This can result from improper data collection, poorly calibrated analytical or sampling equipment, or limitations or errors in analytical methods and techniques. {ORD} {OW/EAD} {OPP} {OW/TSC} {OAR/OAQPS} {OECA} {ORCR}\n\n15. The constant or systematic distortion of a measurement process, different from random error, which manifests itself as a persistent positive or negative deviation from the known or true value. This can result from improper data collection, poorly calibrated analytical or sampling equipment, or limitations or errors in analytical methods and techniques. {ORD}\n\n16. In a clinical trial, a flaw in the study design or method of collecting or interpreting information. Biases can lead to incorrect conclusions about what the study or trial showed.\n\n17. A systematic deviation of results or inferences from the truth or processes leading to such systematic deviation; any systematic tendency in the collection, analysis, interpretation, publication, or review of data that can lead to conclusions that are systematically different from the truth. In epidemiology, does not imply intentional deviation.\n\n18. Systematic error, resulting in measurements that will be either consistently low or high relative to the reference value.\n\n19. Systematic or persistent distortion of a measurement process which deprives the result of representativeness (i.e., the expected sample measurement is different than the sample's true value.) A data quality indicator. [QA Glossary]\n\n20. The systematic or persistent distortion of a measurement process which deprives the result of representativeness (i.e., the expected sample measurement is different than the sample's true value.) A data quality indicator.",
  "subject": "Policy and guidance",
  "references": [
    "Modeling Glossary",
    "Drinking Water Technical & Legal Terms",
    "Program Evaluation Glossary",
    "Radon Glossary of Terms",
    "Guidance for Quality Assurance Project Plans",
    "Great Lakes: Quality Management Training - Data Review Glossary",
    "Great Lakes: Quality Management Training - Quality Glossary",
    "Great Lakes Quality Mgmt Plan Glossary",
    "Exposure Factors Handbook: Glossary",
    "Environmental Modeling and Assessment Program (EMAP) Master Glossary; EMAP Master Glossary",
    "EPA 2004",
    "CDC 2005",
    "NLM/NICHSR 2004",
    "Forum on Environmental Measurements (FEM) Glossary",
    "National Cancer Institute Glossary",
    "CDC Glossary of Epidemiology Terms",
    "40 CFR 72.2 (CFR 2013)",
    "Environmental Sampling and Analytical Methods (ESAM) Program Glossary",
    "QA Glossary"
  ],
  "url": "https://mlchart.com/terminology/environment/bias/"
}