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On asymptotic distributions of several test statistics for familial relatedness in linear mixed models.
Devogel, Nicholas; Auer, Paul L; Manansala, Regina; Wang, Tao.
Afiliación
  • Devogel N; Division of Biostatistics, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
  • Auer PL; Division of Biostatistics, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
  • Manansala R; Centre for Health Economics Research & Modelling Infectious Diseases, Vaccine & Infectious Disease Institute WHO Collaborating Centre, Faculty of Medicine & Health Sciences, University of Antwerp, Antwerp, Belgium.
  • Wang T; Division of Biostatistics, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
Stat Med ; 42(17): 2962-2981, 2023 07 30.
Article en En | MEDLINE | ID: mdl-37345498
In this study, the asymptotic distributions of the likelihood ratio test (LRT), the restricted likelihood ratio test (RLRT), the F and the sequence kernel association test (SKAT) statistics for testing an additive effect of the expected familial relatedness (FR) in a linear mixed model are examined based on an eigenvalue approach. First, the covariance structure for modeling the FR effect in a LMM is presented. Then, the multiplicity of eigenvalues for the log-likelihood and restricted log-likelihood is established under a replicate family setting and extended to a more general replicate family setting (GRFS) as well. After that, the asymptotic null distributions of LRT, RLRT, F and SKAT statistics under GRFS are derived. The asymptotic null distribution of SKAT for testing genetic rare variants is also constructed. In addition, a simple formula for sample size calculation is provided based on the restricted maximum likelihood estimate of the effect size for the expected FR. Finally, a power comparison of these test statistics on hypothesis test of the expected FR effect is made via simulation. The four test statistics are also applied to a data set from the UK Biobank.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Modelos Genéticos Límite: Humans Idioma: En Revista: Stat Med Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Modelos Genéticos Límite: Humans Idioma: En Revista: Stat Med Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos