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Guidelines for Creating Clusters Using Grade Correspondence Analysis: Practical and Technical Issues

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  • Taylor R

Abstract

This document is intended as a practical guide for researchers using the Grade Correspondence Analysis (GCA) method of clustering data. The purpose of the guide is to highlight facets of GCA that are not immediately apparent or covered in other publications, and to ensure that all aspects of GCA can be exploited. It is based on experience gained and software used in the ESRC Analysis of Large and Complex Datasets project "Data enhancements to improve the scope and reliability of microsimulation models". See Taylor, Gomulka and Sutherland (2000).

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  • Taylor R, 2000. "Guidelines for Creating Clusters Using Grade Correspondence Analysis: Practical and Technical Issues," Microsimulation Unit Research Notes MU/RN/39, Microsimulation Unit at the Institute for Social and Economic Research.
    • Handle: RePEc:ese:msimrn:mu/rn/39
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    File URL: http://www.iser.essex.ac.uk/files/msu/publications/pdf/rn39.pdf
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    1. Taylor R & Sutherland H & Gomulka J, 2001. "Using POLIMOD to evaluate alternative methods of expenditure imputation," Microsimulation Unit Research Notes MU/RN/38, Microsimulation Unit at the Institute for Social and Economic Research.

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