6. The method of claim 4, comprising the further step of: forming a plurality of terminal nodes, wherein each said terminal node contains a unique subset of said items, wherein said plurality of terminal nodes is formed by grouping said items to minimize deviance among items within each said terminal node and maximize deviance among items from different terminal nodes.
6. The method of claim 4, comprising the further step of: forming a plurality of terminal nodes, wherein each said terminal node contains a unique subset of said items, wherein said plurality of terminal nodes is formed by grouping said items to minimize deviance among items within each said terminal node and maximize deviance among items from different terminal nodes. 7. The method of claim 6, comprising the further step of: determining a mean value of item difficulty corresponding to at least one said terminal node based on the items forming said at least one terminal node; and predicting the value of item difficulty for at least one item in said at least one terminal node based on the corresponding mean value of item difficulty.