Reasonably accurate and unbiased estimates were obtained with data containing 500 sires with 20 offspring or 100 sires with 50 offspring, regardless of the data structure. The accuracy and bias of the estimated macro- and micro-GES effects and the estimated breeding values ( EBVs) obtained using the RN-DHGLM depended on the data size. Both datasets had a variable number of offspring per sire, but one dataset also had a variable number of offspring within macro-environments. In the current study, the data size (numbers of sires and progeny) and structure requirements of the RN-DHGLM were investigated for two types of unbalanced datasets. The accuracy of variance components estimated using a RN-DHGLM has been explicitly studied for balanced data and recommendation of a data size with a minimum of 100 sires with at least 100 offspring each have been made. A combined reaction norm and double hierarchical generalised linear model ( RN-DHGLM) allows for simultaneous estimation of base genetic, macro- and micro-GES effects. Macro-GES is genetic sensitivity to macro-environments (definable environments often shared by groups of animals), while micro-GES is genetic sensitivity to micro-environments (individual environments). Genotype-by-environment interaction is caused by variation in genetic environmental sensitivity ( GES), which can be subdivided into macro- and micro-GES.
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