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Using Non-Normal SEM to Resolve the ACDE Model in the Classical Twin Design

Overview of attention for article published in Behavior Genetics, August 2010
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Title
Using Non-Normal SEM to Resolve the ACDE Model in the Classical Twin Design
Published in
Behavior Genetics, August 2010
DOI 10.1007/s10519-010-9386-5
Pubmed ID
Authors

Koken Ozaki, Hideki Toyoda, Norikazu Iwama, Saori Kubo, Juko Ando

Abstract

One of the biggest problems in classical twin studies is that it cannot estimate additive genetic (A), non-additive genetic (D), shared environmental (C), and non-shared environmental (E) effects, simultaneously, because the model, referred to as the ACDE model, has negative degrees of freedom when using Structural Equation Modeling (SEM). Therefore, instead of the ACDE model, the ACE model or the ADE model is actually used. However, using the ACE or ADE models almost always leads to biased estimates. In the present paper, the univariate ACDE model is developed using non-normal Structural Equation Modeling (nnSEM). In SEM, (1st- and) 2nd-order moments, namely, (means and) covariances are used as information. However, nnSEM uses higher-order moments as well as (1st- and) 2nd-order moments. nnSEM has a number of advantages over SEM. One of which is that nnSEM can specify models that cannot be specified using SEM because of the negative degrees of freedom. Simulation studies have shown that the proposed method can decrease the biases. There are other factors that have possible effects on phenotypes, such as higher-order epistasis. Since the proposed method cannot estimate these effects, further research on developing a more exhaustive model is needed.

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Mendeley readers

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Geographical breakdown

Country Count As %
Japan 1 3%
United States 1 3%
Unknown 27 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 24%
Student > Bachelor 6 21%
Researcher 3 10%
Student > Master 3 10%
Student > Doctoral Student 2 7%
Other 6 21%
Unknown 2 7%
Readers by discipline Count As %
Psychology 10 34%
Neuroscience 3 10%
Agricultural and Biological Sciences 3 10%
Medicine and Dentistry 3 10%
Social Sciences 2 7%
Other 5 17%
Unknown 3 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 August 2011.
All research outputs
#20,145,561
of 22,651,245 outputs
Outputs from Behavior Genetics
#795
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Outputs of similar age
#89,630
of 94,333 outputs
Outputs of similar age from Behavior Genetics
#7
of 7 outputs
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