Finally, we tell asreml() what to when it encounters NAs in either the dependent or predictor variables (in this case we choose to remove the records). Our random animal effect is connected to the inverse related matrix ainv which integrate the relativeness or pedigree information.ĭata= specifies the name of the dataframe that contains our variables. The only random effect we have fitted is animal, which will provide an estimate of \(V_A\). In this model, bwt is the response variable and the only fixed effect is the mean (the intercept, denoted as 1). # Model fitted using the sigma parameterization.
Model1 <- asreml( fixed = bwt ~ 1, random = ~ vm(animal, ainv), residual = ~ idv(units), data = gryphon, na.action = na.method( x = "omit", y = "omit") ) # Online License checked out Tue Nov 23 22:09:25 2021 5.1 Univariate model with repeated measures.4.4.3 Adding additional effects and testing significance.