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Rough set methodology in meta-analysis - a comparative and exploratory analysis

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Author Info
Thomas Rupp () (Institut für Volkswirtschaftslehre (Department of Economics), Technische Universität Darmstadt (Darmstadt University of Technology))
Abstract

We study the applicability of the pattern recognition methodology "rough set data analysis" (RSDA) in the field of meta analysis. We give a summary of the mathematical and statistical background and then proceed to an application of the theory to a meta analysis of empirical studies dealing with the deterrent effect introduced by Becker and Ehrlich. Results are compared with a previously devised meta regression analysis. We find that the RSDA can be used to discover information overlooked by other methods, to preprocess the data for further studying and to strengthen results previously found by other methods.

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Publisher Info
Paper provided by Institut für Volkswirtschaftslehre (Department of Economics), Technische Universität Darmstadt (Darmstadt University of Technology) in its series Darmstadt Discussion Papers in Economics with number 157.

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Length: 43 pages
Date of creation: Nov 2005
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Handle: RePEc:tud:ddpiec:157

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Related research
Keywords: Rough Data Set; RSDA; Meta Analysis; Data Mining; Pattern Recognition; Deterrence; Criminometrics;

Find related papers by JEL classification:
K14 - Law and Economics - - Basic Areas of Law - - - Criminal Law
K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law
C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other

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