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Comparison of Control Group Generating Methods
Szabolcs Szekér, György Fogarassy, Ágnes Vathy-Fogarassy
311 - 318
10.3233/978-1-61499-759-7-311
Studies in Health Technology and Informatics
Volume 236: Health Informatics Meets eHealth
Abstract

Retrospective studies suffer from drawbacks such as selection bias. As the selection of the control group has a significant impact on the evaluation of the results, it is very important to find the proper method to generate the most appropriate control group. In this paper we suggest two nearest neighbors based control group selection methods that aim to achieve good matching between the individuals of case and control groups. The effectiveness of the proposed methods is evaluated by runtime and accuracy tests and the results are compared to the classical stratified sampling method.

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