Jessica Villiger, Simone A. Schweiger, Artur Baldauf
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Making the Invisible Visible: Guidelines for the Coding Process in Meta-Analyses
This article contributes to the practice of coding in meta-analyses by offering direction and advice for experienced and novice meta-analysts on the “how” of coding. The coding process, the invisible architecture of any meta-analysis, has received comparably little attention in methodological resources, leaving the research community with insufficient guidance on “how” it should be rigorously planned (i.e., cohere with the research objective), conducted (i.e., make reliable and valid coding decisions), and reported (i.e., in a sufficiently transparent manner for readers to comprehend the authors’ decision-making). A lack of rigor in these areas can lead to erroneous results, which is problematic for entire research communities who build their future knowledge upon meta-analyses. Along four steps, the guidelines presented here elucidate “how” the coding process can be performed in a coherent, efficient, and credible manner that enables connectivity with future research, thereby enhancing the reliability and validity of meta-analytic findings. Our recommendations also support editors and reviewers in advising authors on how to improve the rigor of their coding and ultimately establish higher quality standards in meta-analytic research.
期刊介绍:
Organizational Research Methods (ORM) was founded with the aim of introducing pertinent methodological advancements to researchers in organizational sciences. The objective of ORM is to promote the application of current and emerging methodologies to advance both theory and research practices. Articles are expected to be comprehensible to readers with a background consistent with the methodological and statistical training provided in contemporary organizational sciences doctoral programs. The text should be presented in a manner that facilitates accessibility. For instance, highly technical content should be placed in appendices, and authors are encouraged to include example data and computer code when relevant. Additionally, authors should explicitly outline how their contribution has the potential to advance organizational theory and research practice.