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, 21:13, 25 March 2014
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| In this model, the scalar parameter <math>\gamma_i</math> is to measure the additive genetic effect of the <math>i^{th}</math> variant. As usual, the score statistic for testing <math>H_0:\gamma_i=0</math> is: | | In this model, the scalar parameter <math>\gamma_i</math> is to measure the additive genetic effect of the <math>i^{th}</math> variant. As usual, the score statistic for testing <math>H_0:\gamma_i=0</math> is: |
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− | <math> U_i=(\mathbf{G_i}-\mathbf{\bar{G_i}} )^T \boldsymbol{\Omega^(-1)(\mathbf{y}-\mathbf{X}\boldsymbol{\beta}) </math> | + | <math> U_i=(\mathbf{G_i}-\mathbf{\bar{G_i}} )^T \boldsymbol{\Omega}^{-1}(\mathbf{y}-\mathbf{X}\boldsymbol{\beta}) </math> |
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| We further derive the variance-covariance matrix of these statistics as | | We further derive the variance-covariance matrix of these statistics as |