By Noel A. Card PhD
Offering pragmatic assistance for making plans and carrying out a meta-analytic evaluation, this publication is written in an attractive, nontechnical variety that makes it excellent for graduate path use or self-study. the writer exhibits how you can determine questions that may be spoke back utilizing meta-analysis, retrieve either released and unpublished stories, create a coding handbook, use conventional and special impact measurement indices, and write a meta-analytic evaluate. An ongoing instance illustrates meta-analytic suggestions. as well as the basics, the publication discusses extra complicated themes, resembling artifact correction, random- and mixed-effects types, structural equation representations, and multivariate methods. hassle-free positive factors comprise annotated equations; discussions of different methods; and "Practical issues" sections that supply suggestion on subject matters infrequently mentioned in different books, similar to linking meta-analytic effects with thought and the software of meta-analysis software program programs.
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Additional info for Applied Meta-Analysis for Social Science Research
The controversial nature of this meta-analysis drew criticisms, both of the particular paper and of the process of meta-analysis itself. Although these criticisms were likely motivated more by dissatisfaction with the results than the approach, there has been some persistence of these criticisms toward meta-analysis since its early years. The result of this extensive criticism, and efforts to address these critiques, is that meta-analysis as a scientific process of reviewing empirical literature has a deeper appreciation of its own limits; so this criticism was in the end fruitful.
4 Limits of Statistical Power Statistical power refers to the probability of concluding that an effect exists when it truly does. The converse of statistical power is type II error, or fail- 22 PLANNING AND PREPARING A META-ANALYTIC REVIEW ing to conclude that an effect exists when it does. , low statistical power leads to large confidence intervals). , a) set by the researcher, the type of analysis performed, and the magnitude of the effect size within the population. However, because these other factors are typically out of the researcher’s control,3 statistical power is dictated primarily by sample size, where larger sample sizes yield greater statistical power.
Furthermore, the process of presenting your findings to colleagues— through either conference presentations or the peer review process—is likely to generate further refinement and creation of research questions. 5 Summary As with any research endeavor, it is important to identify the research questions you wish to answer when you are planning your meta-analysis. To facilitate generating and shaping these questions, I have described the primary methods of meta-analysis as combination and comparison across studies, with the focus being on one of a variety of effect sizes.
Applied Meta-Analysis for Social Science Research by Noel A. Card PhD