Abstract
Scientists have known for centuries that little can be proven from single studies. The elimination of alternate hypotheses requires the work of many researchers in many studies. Because of the unavoidable presence of sampling error, this problem is magnified when the basic data in the study are statistical. Yet the dominant pattern of review papers in the behavioral and social sciences has been to review each study on an individual basis with little or no attention to the role of sampling error in producing variation in findings between studies. Instead, variation in results from study to study has typically been taken at face value or ascribed to methodological weaknesses in some of the studies. Most reviews conclude that “more research is needed,” although many studies may already be available on the hypothesis in question. The thesis of this chapter is that, in the long run, the only solution to the problem of sampling error inherent in small sample studies is cumulation of results across studies. The subject of the present chapter is methods for conducting such cumulative analyses.
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Hunter, J.E., Schmidt, F.L. (1991). Meta-Analysis. In: Hambleton, R.K., Zaal, J.N. (eds) Advances in Educational and Psychological Testing: Theory and Applications. Evaluation in Education and Human Services Series, vol 28. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-2195-5_6
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DOI: https://doi.org/10.1007/978-94-009-2195-5_6
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-010-7484-1
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