Psychological Measure
(Redirected from Psychological assessment)
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A Psychological Measure is a human measure of a psychological trait.
- Context:
- It can (often) be proposed by a Psychometrics Researcher (in Psychometrics).
- Example(s):
- a Human Intelligence Test, such as an IQ test.
- a Personality Test (of personality trait)s.
- a Situational Judgement Test.
- a Neuropsychological Test.
- …
- Counter-Example(s):
- a Physiological Test, such as a blood test.
- an Educational Test.
- See: Aptitude, Personality, Personality Measure.
References
2015
- (Wikipedia, 2015) ⇒ http://en.wikipedia.org/wiki/Psychological_testing Retrieved:2015-6-25.
- Psychological testing refers to the administration of psychological tests. A psychological test is "an objective and standardized measure of a sample of behavior" (p. 4). [1] The term sample of behavior refers to an individual's performance on tasks that have usually been prescribed beforehand. The samples of behavior that make up a paper-and-pencil test, the most common type of test, are a series of items. Performance on these items produce a test score. A score on a well-constructed test is believed to reflect a psychological construct such as achievement in a school subject, cognitive ability, aptitude, emotional functioning, personality, etc. Differences in test scores are thought to reflect individual differences in the construct the test is supposed to measure. The technical term for the science behind psychological testing is psychometrics.
2013
- (Kosinski et al., 2013) ⇒ Michal Kosinski, David Stillwell, and Thore Graepel. (2013). “Private Traits and Attributes Are Predictable from Digital Records of Human Behavior.” In: Proceedings of the National Academy of Sciences, 110(15).
- QUOTE: We show that easily accessible digital records of behavior, Facebook Likes, can be used to automatically and accurately predict a range of highly sensitive personal attributes including: sexual orientation, ethnicity, religious and political views, personality traits, intelligence, happiness, use of addictive substances, parental separation, age, and gender. The analysis presented is based on a dataset of over 58,000 volunteers who provided their Facebook Likes, detailed demographic profiles, and the results of several psychometric tests. The proposed model uses dimensionality reduction for preprocessing the Likes data, which are then entered into logistic/linear regression to [[predict individual psychodemographic profiles from Likes. The model correctly discriminates between homosexual and heterosexual men in 88% of cases, African Americans and Caucasian Americans in 95% of cases, and between Democrat and Republican in 85% of cases. For the personality trait “Openness," prediction accuracy is close to the test-retest accuracy of a standard personality test. We give examples of associations between attributes and Likes and discuss implication]]s for online personalization and privacy.