LAUSR

Abstract Factors affecting growth of young animals were examined in numerous studies relying on various experimental designs and statistical analyses of collected data. In order to provide truthful inferences of examined effect, statistical analysis of test day records must be conducted in a very specific way. The study aimed to exemplify the usage of the random regression coefficient approach in the analysis of the early growth of kids. A total of 3376 test-day body weights repeatedly collected on 644 Alpine and Saanen kids (raised under the same environmental conditions) were used in the statistical analysis. Fitting the age as quadratic regression within kids in the random part of the statistical model helped to determine the effects of gender, breed, and type of birth on growth rate of the kids. The post-fitting statistical analysis revealed that gender was most influential among the examined effects. Males exhibited significantly faster growth than females in practically all examined points of age. Type of birth only negligibly affected growth of experimental kids. Singletons were slightly heavier than twins immediately after birth while it was vice versa at the end of experiment. Breed did not affect growth performances of the kids at any stage of examined age. Along with the findings of the study, the intention of the authors was to initiate a widespread usage of the random regression coefficient approach in studies based on similarly structured data.