By Noel A. Card PhD
Offering pragmatic counsel for making plans and carrying out a meta-analytic assessment, this booklet is written in an interesting, nontechnical sort that makes it excellent for graduate direction use or self-study. the writer exhibits the way to establish questions that may be replied utilizing meta-analysis, retrieve either released and unpublished stories, create a coding guide, use conventional and distinctive impact measurement indices, and write a meta-analytic evaluate. An ongoing instance illustrates meta-analytic innovations. as well as the basics, the publication discusses extra complex subject matters, comparable to artifact correction, random- and mixed-effects types, structural equation representations, and multivariate tactics. common beneficial properties comprise annotated equations; discussions of different methods; and "Practical issues" sections that provide suggestion on issues hardly ever mentioned in different books, equivalent to linking meta-analytic effects with thought and the application of meta-analysis software program programs.
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Extra resources for Applied Meta-Analysis for Social Science Research
3 Limits of Methodological Artifacts Researchers planning and conducting primary studies do not intentionally impose methodological artifacts, but these often arise. , artificial dichotomization of continuous variables). These artifacts typically2 attentuate, or diminish, the effect sizes estimated in primary studies. This attenuation leads to lower statistical power (higher rates of type II error) and underestimation of the magnitude—and potentially the importance—of the results. These artifacts can be corrected in the sense that it is possible to estimate the magnitude of “true” effect sizes disattenuated for these artifacts.
I do not describe these software options because, as I state later in this book, I do not necessarily recommend them for the beginning metaanalyst. , meta-analyses with many studies and multiple effect sizes per study) for some more complex analyses. However, the danger of relying on them exclusively—especially when you are first learning to conduct meta-analyses—is that they may encourage erroneous use when you are not adequately familiar with the techniques. 7 Summary In this chapter, I have introduced meta-analysis as a valuable tool for synthesizing research, specifically for synthesizing research outcomes using quantitative analyses.
However, both approaches to creating new research questions are valuable, as long as you are upfront about their source when presenting and drawing conclusions from your metaanalysis (see Chapter 13). As is true of analyzing the data, the process of writing your results may lead to refinement of research questions or even the development of new ones. 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.