Data utilization through case-wise analysis: Some key interactions

Abstract

An earlier experiment demonstrated that the case-wise form of data analysis and presentation can improve the utilization, assimilation, recall, and recognition of poverty data in a priority setting task. As an alternative to the conventional variable-wise form, the case-wise form defines and identifies qualitatively distinct types of cases through cluster analysis. This paper reports on housing experiments designed to replicate the earlier results. However, the housing experiments unexpectedly dislosed some key interactions among task descriptions, policy preconceptions, and data presentations, including their forms. These interactions qualify and broaden the earlier results but corroborate the underlying theoretical model. They also clarify practical means of increasing the return on the public's investment in data resources to improve policy decisions.