Limits...
Using non-normal SEM to resolve the ACDE model in the classical twin design.

Ozaki K, Toyoda H, Iwama N, Kubo S, Ando J - Behav. Genet. (2010)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Research Organization of Information and Systems, The Institute of Statistical Mathematics, 10-3 Midori-cho, Tachikawa, Tokyo, Japan. koken@ism.ac.jp

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.

Show MeSH
Biases (estimated value–true value) when three factors affect a trait
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC3044827&req=5

Fig4: Biases (estimated value–true value) when three factors affect a trait

Mentions: Twenty one patterns of the true explained variance were divided into two cases. In one case, all four factors affect a trait. Therefore, nnSEM is the true model. In the other case, three of the four factors (ACE or ADE) affect a trait. Therefore, both nnSEM and SEM are the true model. Figures 2 and 3 show the results for the former cases, and Figs. 4 and 5 show the results for the latter cases.Fig. 2


Using non-normal SEM to resolve the ACDE model in the classical twin design.

Ozaki K, Toyoda H, Iwama N, Kubo S, Ando J - Behav. Genet. (2010)

Biases (estimated value–true value) when three factors affect a trait
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3044827&req=5

Fig4: Biases (estimated value–true value) when three factors affect a trait
Mentions: Twenty one patterns of the true explained variance were divided into two cases. In one case, all four factors affect a trait. Therefore, nnSEM is the true model. In the other case, three of the four factors (ACE or ADE) affect a trait. Therefore, both nnSEM and SEM are the true model. Figures 2 and 3 show the results for the former cases, and Figs. 4 and 5 show the results for the latter cases.Fig. 2

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Research Organization of Information and Systems, The Institute of Statistical Mathematics, 10-3 Midori-cho, Tachikawa, Tokyo, Japan. koken@ism.ac.jp

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.

Show MeSH