Evaluation of Individual Growth Performance of Goat Kids by Using Multilevel Models

Abstract

The aim of this study was to evaluate the individual growth performances of hair goats and hybrids grown in extensive conditions performing two-level linear regression analysis for the period up to the sixth month from birth. Live weight records of 33 male and 57 female males were used in the study. -2LL, AIC and BIC statistics were used to find the covariance structure and model that best explain the change of the live weight occurring from birth to sixth month. According to the results, it was suitable two-level linear regression model which the random intercept and random slope with UN covariance structure for both male and female goat kids. According to this, birth weight, time and time-birth type interaction effect were found to be significant for males on the change in body weight, whereas birth weight, type of birth, time and time-birth interaction effect were significant for females (P <0.01). The change in growth performance from individual to individual was found to be significant for both genders (P <0.01).

Keywords: Hair goat, multilevel modeling, individual growth curve, covariance structure

DOI: 10.7176/JSTR/5-3-12