We chose a priori to retain all parameters in our best fitting multivariate model. Sullivan and Eaves (65) have reported that in analyses based on discreet traits, estimates from the full ACE model will be more accurate and that attempts at parsimony result in oversimplification of the models rather than a simpler and more accurate representation of the data. This will likely occur in cases such as ours which involve more complex multivariate modeling and where the sample is not large enough to make definitive conclusions. Removing all parameters with lower bounds spanning zero, including parameters with small point estimates i.e. < 0.10, assumes that the component of variance is known to be zero without any error variance, and if this argument is incorrect, then future research might ignore an important source of variance (65).
