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close this bookClassification and Regression Trees, Cart TM - A user manual for identifying indicators of vulnerability to famine and chronic food insecurity + disk (IFPRI, 1999, 56 p.)
View the document(introduction...)
View the documentPreface
View the documentAcknowledgments
View the document1. Introduction
View the document2. Overview of CART
View the document3. Basic Principles of Cart Methodology
View the document4. Regression Trees: An Overview
View the document5. CART Software and Program Codes
View the document6. Refining CART Analyses
View the document7. Conclusions
Open this folder and view contentsAppendix 1: Condensed Examples of Classification-Tree Output (full output on diskette)
View the documentAppendix 2: A Condensed Example of Regression-Tree Output (full output on diskette)
View the documentReferences
View the documentBack Cover

7. Conclusions

This manual has laid out the fundamental theory underlying Classification and Regression Tree (CART) analytical techniques, and also explained how such techniques can be applied in practice. Concrete examples were presented from research at IFPRI. This research has explored the potential of CART to provide a less subjective framework for the selection of famine risk indicators and determine the relative importance of such indicators in explaining vulnerability across years and regions in Ethiopia.

The theoretical exposition and the results from applied CART analysis suggest that this methodology offers considerable potential for assisting in the analysis of large and complex data sets. CART also offers a transparent, "objective" methodology upon which planners can base their decisions.

That said, CART should be seen as one tool that can be used, in conjunction with others, for analyzing data, assessing risk, and planning development. The technique is extremely data-intensive and, hence, labor-intensive (in terms of the time an analyst spends collating, preparing, and analyzing the data). What is more, there remains a need for further research into the definition of appropriate benchmark indicators (such as the "population in need" figures used here), against which multiple variables can be tested. In the short run, the choice of indicators will most likely be driven by data availability. But in the longer run, such choices should be made as a result of assessments of the reliability and sensitivity of alternatives.

Further exploration of the gains and drawbacks inherent in CART are therefore encouraged, and not just in relation to research on food security. As IFPRI and others have demonstrated, CART can be usefully applied to a wide range of uses.