Latent and observable variables: Difference between revisions

Revision as of 09:45, 13 May 2008

Revision as of 08:39, 5 June 2008

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One advantage of using latent variables is that it [[Dimensionality reduction|reduces the dimensionality]] of data. A large number of observable variables can be aggregated in a model to represent an underlying concept, making it easier for humans to understand the data. In this sense, they serve the same function as theories in general do in science. At the same time, latent variables link observable ("sub-symbolic") data in the real world, to symbolic data in the modelled world.

==Examples of latent variables==

===Psychology===

* extraversion <ref name="status"> Borsboom, Mellenbergh, van Heerden (2003) ''The Theoretical Status of Latent Variables'' Psychological Review Vol 110, No 2 http://rhowell.ba.ttu.edu/BorsboomLatentvars2003.pdf</ref>

* spatial ability <ref name="status"> Borsboom, Mellenbergh, van Heerden (2003) ''The Theoretical Status of Latent Variables'' Psychological Review Vol 110, No 2 http://rhowell.ba.ttu.edu/BorsboomLatentvars2003.pdf</ref>

* intelligence

==References==

{{Reflist|2}}

==See also==

* [[Latent variable model]]

* [[Item response theory]]

* [[Rasch model]]

[[Category:Social sciences]]

[[Category:Bayesian networks]]

[[Category:Econometrics]]

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[[Category:Statistical models]]

[[Category:Statistical terminology]]

[[Category:Psychometrics]]

{{econometrics-stub}}