Statistics and Its Interface

Volume 6 (2013)

Number 1

Statistical inference of biometrical genetic model with cultural transmission

Pages: 91 – 98

DOI: http://dx.doi.org/10.4310/SII.2013.v6.n1.a9

Authors

Xiaobo Guo (Department of Statistical Science, School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou, China)

Tian Jin (School of Statistics and Management, Shanghai University of Finance and Economic, Shanghai, China)

Xueqin Wang (Department of Statistical Science, School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou, China)

Heping Zhang (Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, Conn., U.S.A.)

Shouqiang Zhong (Maoming People’s Hospital, Maoming, China)

Abstract

Twin and family studies establish the foundation for studying the genetic, environmental and cultural transmission effects for phenotypes. In this work, we make use of the well established statistical methods and theory for mixed models to assess cultural transmission in twin and family studies. Specifically, we address two critical yet poorly understood issues: the model identifiability in assessing cultural transmission for twin and family data and the biases in the estimates when sub-models are used. We apply our models and theory to two real data sets. A simulation is conducted to verify the bias in the estimates of genetic effects when the working model is a sub-model.

Keywords

twin and family study, biometrical genetic model, cultural transmission, biometrical genetic model, identifiability, likelihood ratio test, mixed effects model

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