Difference-based meta-analytic procedures for between-participant and/or within-participant designs : a tutorial review for sports and exercise scientists

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Deutscher übersetzter Titel:Unterschiedsbasierte Metaanalysenprozedur für Studiendesigns mit ungleichen und/oder gleichen Stichproben : ein "tutorial review" für Sport- und Bewegungswissenschaftler
Autor:Ashford, Derek; Davids, Keith; Bennett, Simon J.
Erschienen in:Journal of sports sciences
Veröffentlicht:27 (2009), 3, S. 237-255, Lit.
Format: Literatur (SPOLIT)
Publikationstyp: Zeitschriftenartikel
Medienart: Elektronische Ressource (online) Gedruckte Ressource
Sprache:Englisch
ISSN:0264-0414, 1466-447X
DOI:10.1080/02640410802482409
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Erfassungsnummer:PU201408007666
Quelle:BISp

Abstract

The aim of this paper is to provide a contemporary summary of statistical and non-statistical meta-analytic procedures that have relevance to the type of experimental designs often used by sport scientists when examining differences/change in dependent measure(s) as a result of one or more independent manipulation(s). Using worked examples from studies on observational learning in the motor behaviour literature, we adopt a random effects model and give a detailed explanation of the statistical procedures for the three types of raw score difference-based analyses applicable to between-participant, within-participant, and mixed-participant designs. Major merits and concerns associated with these quantitative procedures are identified and agreed methods are reported for minimizing biased outcomes, such as those for dealing with multiple dependent measures from single studies, design variation across studies, different metrics (i.e. raw scores and difference scores), and variations in sample size. To complement the worked examples, we summarize the general considerations required when conducting and reporting a meta-analysis, including how to deal with publication bias, what information to present regarding the primary studies, and approaches for dealing with outliers. By bringing together these statistical and non-statistical meta-analytic procedures, we provide the tools required to clarify understanding of key concepts and principles. Verf.-Referat