Large White data set with performance and reproductive traits for a development line were analyzed in order to verify the importance of including maternal and common litter effects in genetic evaluation models, using four different models: model 1 - direct genetic effect; model 2 - the direct and maternal genetic effects; model 3 - the direct and common litter effects; and the model 4 - the direct, maternal and common litter effects. The traits were analyzed by Restricted Maximum Likelihood method (REML). The Likelihood ratio test was applied in order to verify which model was more adapted to the genetic evaluation. Pearson and Spearman correlation among predicted values for each trait in different models were obtained, in order to verify ranking alterations when the most adapted model was not used. The model 4 was the most adapted to performance traits and age at first farrowing and, for the litter traits, the model 1. For some traits, in which the model 4 was the most adapted, the correlations between predicted values, by the model 4 and the remaining, were close to unit, indicating that with limited computational conditions, models less parameterized could be used without prejudice to the real genetic gain.
common litter effect; Likelihood ratio test; maternal genetic effect; Pearson correlation; Spearman correlation
