Data Management in Meta-analytical Procedures: Myths, Realities, and Biases

Abstract

The aim of the present paper is to highlight the importance of correct data management and the preparation of a proper statistical value base in developing a meta-analysis. When dealing with meta-analytical procedures, research studies encounter a wide range of challenges, ranging from classical value losses to more modern coding or sampling biases. The theoretical and practical examples of this paper indicate that a meta-analytical approach is most useful and applicable when related to a clear problem specification, a correct coding scheme, and the use of eligible study reports.