If the parameter estimates are greatly different from the underlying, unknown true values, then an MT analysis could do as much harm as it might do good. Lastly, the researcher needs to consider the increased costs of computing MT analyses. Programs are more complicated, more memory and disk storage are usually needed, and verification of results might be more complicated. These have to be balanced against the benefits of an MT analysis. If culling bias is the main concern, then an MT model must be used regardless of the costs or no analysis should be done at all, except for the traits not affected by culling bias.
Models Consider two traits with a single observation per trait on animals.
A model should be specified separately for each trait. Usually, the same model is assumed for each trait, and this can greatly simplify the computational aspects, but such an assumption may be unrealistic in many situations. Because the two traits will be analyzed simultaneously, the variances and covariances need to be specified for the traits together. If all animals were observed for both traits, then Simulating Records When simulating data for a multiple trait problem it is best to generate observations for all animals for all traits. Then one can go through the simulated data and randomly delete observations to simulate a missing data situation, or selectively delete observations to imitate culling decisions.