ACE model

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Short description: Statistical model

The ACE model is a statistical model commonly used to analyze the results of twin and adoption studies. This classic behaviour genetic model aims to partition the phenotypic variance into three categories: additive genetic variance (A), common (or shared) environmental factors (C), and specific (or nonshared) environmental factors plus measurement error (E).[1] It is widely used in genetic epidemiology and behavioural genetics.[2][3] The basic ACE model relies on several assumptions, including the absence of assortative mating,[4] that there is no genetic dominance or epistasis,[5] that all genetic effects are additive, and the absence of gene-environment interactions.[3] In order to address these limitations, several variants of the ACE model have been developed, including an ACE-β model, which emphasizes the identification of causal effects,[3] and the ACDE model, which accounts for the effects of genetic dominance.[6]

See also

  • ADE model


  1. Germine, Laura; Russell, Richard; Bronstad, P. Matthew; Blokland, Gabriëlla A.M.; Smoller, Jordan W.; Kwok, Holum; Anthony, Samuel E.; Nakayama, Ken et al. (October 2015). "Individual Aesthetic Preferences for Faces Are Shaped Mostly by Environments, Not Genes". Current Biology 25 (20): 2684–2689. doi:10.1016/j.cub.2015.08.048. ISSN 0960-9822. PMID 26441352. 
  2. Maes, Hermine H. (2005-10-15). "ACE Model" (in en). ACE Model. Chichester, UK: John Wiley & Sons, Ltd. doi:10.1002/0470013192.bsa002. ISBN 978-0470860809. 
  3. 3.0 3.1 3.2 Kohler, Hans-Peter; Behrman, Jere R.; Schnittker, Jason (2011). "Social science methods for twins data: integrating causality, endowments, and heritability". Biodemography and Social Biology 57 (1): 88–141. doi:10.1080/19485565.2011.580619. ISSN 1948-5565. PMID 21845929. 
  4. Beauchamp, Jonathan P.; Cesarini, David; Johannesson, Magnus; Lindqvist, Erik; Apicella, Coren (2010-07-06). "On the sources of the height–intelligence correlation: New insights from a bivariate ACE model with assortative mating" (in en). Behavior Genetics 41 (2): 242–252. doi:10.1007/s10519-010-9376-7. ISSN 0001-8244. PMID 20603722. 
  5. Lawlor, Debbie A.; Lawlor, Deborah A.; Mishra, Gita D. (2009-04-02) (in en). Family Matters: Designing, Analysing and Understanding Family Based Studies in Life Course Epidemiology. OUP Oxford. pp. 252–3. ISBN 9780199231034. 
  6. Wang, Xueqin; Guo, Xiaobo; He, Mingguang; Zhang, Heping (2011-02-09). "Statistical Inference in Mixed Models and Analysis of Twin and Family Data" (in en). Biometrics 67 (3): 987–995. doi:10.1111/j.1541-0420.2010.01548.x. ISSN 0006-341X. PMID 21306354. 

Further reading