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, 11:20, 11 March 2014
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| == Modeling Relatedness == | | == Modeling Relatedness == |
− | we use a variance component model to handle familial relationships. In a sample of n individuals, we model the observed phenotype vector (<math>\mathbf{y}</math>) as a sum of covariate effects (specified by a design matrix <math>\mathbf{X}</math> and a vector of covariate effects <math>\boldsymbol{\beta}</math>), additive genetic effects (modeled in vector <math>\mathbf{g}</math>) and non-shared environmental effects (modeled in vector '''ε'''). Thus the null model is: | + | we use a variance component model to handle familial relationships. In a sample of n individuals, we model the observed phenotype vector (<math>\mathbf{y}</math>) as a sum of covariate effects (specified by a design matrix <math>\mathbf{X}</math> and a vector of covariate effects <math>\boldsymbol{\beta}</math>), additive genetic effects (modeled in vector <math>\mathbf{g}</math>) and non-shared environmental effects (modeled in vector <math>\boldsymbol{\varepsilon}</math>). Thus the null model is: |
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| <math>\mathbf{y}=\mathbf{X}\boldsymbol{\beta} +\mathbf{g}+ \boldsymbol{\varepsilon}</math> | | <math>\mathbf{y}=\mathbf{X}\boldsymbol{\beta} +\mathbf{g}+ \boldsymbol{\varepsilon}</math> |