1. A computational system for performing an online choice model, the system comprising: at least one processor; at least one memory operatively coupled to the at least one processor; and a plurality of modules, each of the modules comprising instructions for execution by the at least one processor, the plurality of modules comprising: a problem definition module comprising a problem definition user interface for receiving a plurality of attributes from a user wherein each attribute has an associated plurality of attribute levels; an online choice model survey module comprising: an experimental design generator module for generating a survey experimental design and an associated plurality of treatments; comprising a library of experimental designs, wherein the experimental design generator module determines the signature of the attribute space from the received plurality of attributes and associated attribute levels; and for one or more experimental designs in the library of experimental designs, performs one or more transformations until the signature of the transformed experimental design matches the signature of the attribute space to obtain one or more matching transformed experimental designs; wherein each transformation preserves the information properties of the untransformed experimental design; wherein the experimental design generator module selects the survey experimental design from the one or more matching transformed experimental designs; and wherein the experimental design generator module obtains a set of treatments from the selected survey experimental design; an online survey assembly module which receives the plurality of treatments and assembles an online survey from one or more survey templates pages, and a plurality of treatment representations created using the plurality of treatments received from the experimental design module; a data collection and sampling module for conducting the assembled online survey, wherein the data collection and sampling module allocates treatments to survey respondents and collects responses using the assembled online survey; a model generation module for receiving the data collected by the data collection and sampling module and building a model to obtain a plurality of model parameter estimates and errors from which a utility estimate can be obtained for each attribute level; and a model explorer module comprising a model explorer user interface for allowing the user to enter one or more attribute levels and obtain a model prediction of the expected utility; wherein the one or more transformations comprise one or more of the following group of transformations: factorial splitting of a factor F into two sub factors A, B where A×B=F and A or B match at least one unmatched factor in the signature; factorial expansion of a factor F into a new factor A×F where A×F matches at least one unmatched factor in the signature; factor truncation of a factor F into a new factor F−A where F−A matches at least one unmatched factor in the signature; full factorization by generation of a new factor F where F matches at least one unmatched factor in the signature; and deleting a factor F when all the other factors in the signature are matched.