Observer-expectancy effect

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The observer-expectancy effect (also called the experimenter-expectancy effect, expectancy bias, observer effect, or experimenter effect) is a form of

double-blind experimental design
.

It may include conscious or unconscious influences on subject behavior including creation of demand characteristics that influence subjects, and altered or selective recording of experimental results themselves.[2]

Overview

The experimenter may introduce cognitive bias into a study in several ways‍—‍in the observer-expectancy effect, the experimenter may subtly communicate their expectations for the outcome of the study to the participants, causing them to alter their behavior to conform to those expectations. Such observer bias effects are near-universal in human data interpretation under expectation and in the presence of imperfect cultural and methodological norms that promote or enforce objectivity.[3]

The classic example of experimenter bias is that of "

posture and facial expression changed in ways that were consistent with an increase in tension, which was released when the horse made the final, correct tap. This provided a cue that the horse had learned to use as a reinforced cue to stop tapping.[citation needed
]

Experimenter-bias also influences human subjects. As an example, researchers compared performance of two groups given the same task (rating portrait pictures and estimating how successful each individual was on a scale of −10 to 10), but with different experimenter expectations.[citation needed]

In one group, ("Group A"), experimenters were told to expect positive ratings while in another group, ("Group B"), experimenters were told to expect negative ratings. Data collected from Group A was a significant and substantially more optimistic appraisal than the data collected from Group B. The researchers suggested that experimenters gave subtle but clear cues with which the subjects complied.[4]

Prevention

Double blind techniques may be employed to combat bias by causing the experimenter and subject to be ignorant of which condition data flows from.[citation needed
]

It might be thought that, due to the central limit theorem of statistics, collecting more independent measurements will improve the precision of estimates, thus decreasing bias. However, this assumes that the measurements are statistically independent. In the case of experimenter bias, the measures share correlated bias: simply averaging such data will not lead to a better statistic but may merely reflect the correlations among the individual measurements and their non-independent nature.[citation needed]

See also

References

  1. ^ Goldstein, Bruce. "Cognitive Psychology". Wadsworth, Cengage Learning, 2011, p. 374
  2. ISBN 978-0-495-59533-5
    . Retrieved 7 September 2013.
  3. ^ Rosenthal, R. (1966). Experimenter Effects in Behavioral Research. NY: Appleton-Century-Crofts.
  4. ^ Rosenthal R. Experimenter Effects in Behavioral Research. New York, NY: Appleton-Century-Crofts, 1966. 464 p.

External links

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