Bayesian threshold analysis of litter size in sheep

Background: Litter size at birth (LSB) is one of the most important economic traits in sheep and could be used genetic improvement schemes for meat production. LSB inherently a categorical trait should analysed with threshold models. Objective: Bayesian models were to analyze estimate parameters. Methods: Data was based on 7,901 records from 14,968 dams 682 sires collected 1986 2012 Makouie Sheep Breeding Station Iran. Means posterior distributions (MPDs) LSB's parameters estimated, best-fitted selected using deviance information criterion. Results: In repeated measurement analysis, estimated direct maternal heritabilities, permanent environmental effect (±SE), according model (model 5), 0.01 (0.010), 0.02 (0.014), (0.011), respectively. univariate best estimates heritabilities 0.12 (0.064) 0.08 (0.045), An increasing trend observed parity 2 (0.15 (0.082) 0.25 (0.083), respectively). bivariate 0.03 (0.027) 0.22 (0.041), The correlations among parities (0.054) (0.021), Conclusions: results showed considerable influence factors each sheep; also, statistically different (p<0.05) obtained another, indicating large influences parity.