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

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  • Rupp, Thomas

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.

Suggested Citation

  • Rupp, Thomas, 2009. "Rough set methodology in meta-analysis - a comparative and exploratory analysis," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 77404, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    • Handle: RePEc:dar:wpaper:77404
    Note: for complete metadata visit http://tubiblio.ulb.tu-darmstadt.de/77404/
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    Cited by:

    1. Aliye Ahu Akgün & Peter Nijkamp & Tüzin Baycan & Martijn Brons, 2010. "Embeddedness Of Entrepreneurs In Rural Areas: A Comparative Rough Set Data Analysis," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 101(5), pages 538-553, December.
    2. Akgun, A.A. & Baycan Levent, T. & Nijkamp, P., 2011. "The engine of sustainable rural development: Embeddedness of entrepreneurs in rural Turkey," Serie Research Memoranda 0008, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.

    More about this item

    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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