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This article provides an introduction to the special issue titled “Using meta-analysis to advance research in human resource management.” It begins by defining meta-analysis and considering the advantages and limitations of using this method in HRM research. For instance, we argued that meta-analysis is a valuable tool because (a) it provides a better estimate of the relation that exists in the population than single studies, (b) the estimates are more precise because there is an increased amount of data and statistical power, (c) hypothesis testing and biases associated with publications can be examined, and (d) it helps resolve inconsistencies in research, and identifies potential moderating or mediating variables. However, we also maintained that there are a number of limitations associated with the method. For example, the results of meta-analysis may be limited by the (a) selection of an incomplete set of studies, (b) inclusion of studies that lack internal, external, construct, and statistical conclusion validity, (c) presence of studies with small sample sizes, and (d) heterogeneity of methods used in studies that may lead to erroneous inferences. Finally, the article presents a brief review of the studies included in the special issue.
4.3. Articles that focus on the methods used to conduct meta-analysis
The next set of four articles focus on the methods used to conduct meta-analysis, and the inferences that can be made from the results. The first article in this set is by Murphy (2017) and is titled “What Inferences Can and Cannot Be Made on the Basis of MetaAnalysis?” The author argued that meta-analysis has both descriptive and inferential uses. He also suggested that if the results of several studies that are asking similar questions are pooled together, the average effect size is likely to be a valuable and important statistic. However, the validity of inferences about what this average means often depends on the extent to which effect size estimates vary from study to study, and the task of making sense of this variability has become central to interpreting metaanalyses. In view of these issues, the author relayed the risks inherent in inferences made from meta-analysis and discussed a Bayesian approach to using meta-analysis to determine if effects vary in important ways. The next article is titled “Realizing the Full Potential of Psychometric Meta-Analysis for a Cumulative Science and Practice of Human Resource Management” by Ones, Viswesvaran, and Schmidt (2017). These authors focus on the issues and potential problems that may threaten the veracity and usefulness of meta-analyses in HRM. They argued that these problems must be correctly tackled for meta-analyses to realize their full potential in advancing HRM science and practice. They addressed the problems of identification and inclusion of all relevant effect sizes, as well as appropriate corrections for unreliability and range restriction. In addition, they offered concrete proposals to enable inclusion of unpublished, practitioner research and data in HRM metaanalyses.