1. A method of identifying parameters that are important in predicting a target variable, the method comprising: compiling training data, said training data identifying, for each of a first set of subjects, values for each of a first set of parameters; compiling test data, said test data identifying, for each of a second set of subjects, values for each of a second set of parameters, said first and second sets of parameters having at least a plurality of common parameters; using the data in the training data, and using a nearest neighbor procedure, to identify, for each of the second set of subjects, a value for a target parameter; and processing the training data and the test data, according to a predefined procedure, to determine the relative importance of at least selected ones of the first group of parameters in predicting the values for the target parameter.