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Recall bias is a type of measurement bias, and can be a methodological issue in research involving interviews or questionnaires.In this case, it could lead to misclassification of various types of exposure. [2]
Observational error, also known as Systematic bias – Difference between a measured value of a quantity and its true value; Outline of public relations – Overview of and topical guide to public relations; Outline of thought – Overview of and topical guide to thought; Pollyanna principle – Tendency to remember pleasant things better
Systematic errors in the measurement of experimental quantities leads to bias in the derived quantity, the magnitude of which is calculated using Eq(6) or Eq(7). However, there is also a more subtle form of bias that can occur even if the input, measured, quantities are unbiased; all terms after the first in Eq(14) represent this bias.
Heuristics are simple for the brain to compute but sometimes introduce "severe and systematic errors." [6] For example, the representativeness heuristic is defined as "The tendency to judge the frequency or likelihood" of an occurrence by the extent of which the event "resembles the typical case." [13]
Selection bias is the bias introduced by the selection of individuals, groups, or data for analysis in such a way that proper randomization is not achieved, thereby failing to ensure that the sample obtained is representative of the population intended to be analyzed. [1]
A major threat to the validity of causal inferences is confounding: Changes in the dependent variable may rather be attributed to variations in a third variable which is related to the manipulated variable.
In educational measurement, bias is defined as "Systematic errors in test content, test administration, and/or scoring procedures that can cause some test takers to get either lower or higher scores than their true ability would merit." [16] The source of the bias is irrelevant to the trait the test is intended to measure.
Some have called this a 'demarcation bias' because the use of a ratio (division) instead of a difference (subtraction) removes the results of the analysis from science into pseudoscience (See Demarcation Problem). Some samples use a biased statistical design which nevertheless allows the estimation of parameters.