Analysis of Hungarian sport horse show jumping results using different transformations and models

The aim of this paper is to estimate heritabilities and to compare data transformation methods and models for Hungarian Sporthorse show jumping results. The analysis is based on data collected between 1996 and 2005. The linear animal model included fixed effects of gender, breeder, rider, age, and start (coded as year of competition, type of competition and height of obstacle). Square root, cubic and fourth roots, Blom score and cotangent transformed ranks were used as measurements of performance. Difference the height of the obstacle and fault points, height of the obstacle and height of the obstacle and fault point were also used as performance traits. Variance and covariance components were estimated with VCE-5 software package. Model fit was evaluated by log-likelihood values and Akaike’s information criterion (AIC). Heritability was low for each performance trait and each model. The poorest goodnessof-fit model was the difference between height of the obstacle and fault points, whereas the best fitting genetic model based on AIC was from using the cotangent transformation.