 Mendelian experiments crossing inbred lines met the goal of Johannsen (and biologists following him) of giving repeatable outcomes and exposing hidden processes, but quantitative genetics, designed to analyze continuous traits (see sections  3.3  and  3.4),  bore an ambiguous relationship with that goal. Models allowed breeders to predict outcomes under different mating designs; the outcomes were not strictly repeatable given that what was actually achieved typically varies from what was predicted. Moreover, while researchers could imagine that the hidden processes were like the theoretical ones in the models, the theoretical genotypes forming the basis for quantitative genetic models were unobservable (see entry on  scientific realism).  Nevertheless, material practices of control of materials and conditions ensure that the model-based analyses continue to be useful. In particular, when there are discrepancies between outcomes and predictions, which may result from the hidden processes being unlike the theoretical ones in the models, breeders can always compensate: they can discard the undesired offspring and breed from the desired ones. And, as breeding programs are elaborated that build on the models (e.g., Holland et al. 2003), it becomes ever more difficult in practice to implement data analysis that would build up from an alternative model (see entry on  pragmatism  and  section 4).  Note, because quantitative genetics involves statistical analysis of data on continuous traits, it must be possible to analyze the data on trait variation using models that avoid reference to what is not observed (Taylor 2012). However, this possibility has not been pursued in quantitative genetics (and thus becomes a potential case of Stanford’s [2006] unconceived alternatives mentioned earlier). Indeed, the difficulty of applying any alternative to quantitative genetic models extends to analysis of data on variation in human traits, even though in that realm breeding is not an option and control of biological material and conditions is minimal. 