Pval <-as.vector(unname( 2 *pnorm( -abs( x))))
X <(summary( m1_plusBreed, all = TRUE) $ coef.fi) #Conditional model (estimate effects of breed) > covariance_matrix covariance_matrix covariance_matrix colnames( covariance_matrix) rownames( covariance_matrix) terms wald.test( b = m1_plusBreed $ coefficients $ fixed, Sigma = covariance_matrix, Terms = 1 :length( terms)) $ result $ chi2 > #overall Wald chi square tests of breed effect on entire trajectory # models for insulin and glucose trajectories #insulin model works with log transformed insulin #glucose works with farm random intercept and breed fixed effect
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