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covariance_structure_of_correlated_random_effects_for_multiple_traits [2018/03/29 18:54] andres |
covariance_structure_of_correlated_random_effects_for_multiple_traits [2022/05/30 21:50] (current) dani |
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- | The documentation is bit confusing on how to declare several correlated effects for several traits. Whereas ''renumf90'' does this automatically for maternal effects models, it is not so obvious if one does it by itself. | + | The documentation is bit confusing on how to declare several correlated effects for several traits. Whereas ''renumf90'' does this automatically for maternal effects models, it is not so obvious if one does it by itself. Llibertat Tusell and Andres Legarra put this together. |
For instance terminal crosses models (e.g. [[https://gsejournal.biomedcentral.com/articles/10.1186/s12711-016-0211-3||here]]) use: | For instance terminal crosses models (e.g. [[https://gsejournal.biomedcentral.com/articles/10.1186/s12711-016-0211-3||here]]) use: | ||
- | * trait_pure: **y = hys u + e** (animal) | + | * trait_pure: **y = herd-year-season + u + e** (animal) |
- | * trait_crossbred : **y = hys s + e** (sire of crossbred) | + | * trait_crossbred : **y = herd-year-season + s + e** (sire of crossbred) |
Thus we have two traits, purebred and crossbred performance, but effect **u** only affects purebreds and effect **s** only affects crossbreds. Data file has "animal" in column 4 and "sire" in column 5. Effect **hys** has respectively 12 and 25 levels. | Thus we have two traits, purebred and crossbred performance, but effect **u** only affects purebreds and effect **s** only affects crossbreds. Data file has "animal" in column 4 and "sire" in column 5. Effect **hys** has respectively 12 and 25 levels. |