Meta-Analysis (and Systematic Review) Resources

Prof. Johnson’s Online Guide to State-of-the-Science (and -Art) Systematic Reviews

  •  Overviews of the Systematic Review Process
  1. Johnson, B. T. (2021). Toward a more transparent, rigorous, and generative psychology. Psychological Bulletin, 147(1), 1-15. DOI: 10.1037/bul0000317
  2. Johnson, B. T., & Hennessy, E. A. (2019). Systematic reviews and meta-analyses in the health sciences: Best practice methods for research syntheses. Social Science & Medicine, 233, 237-251. DOI: 10.1016/j.socscimed.2019.05.035
  3. Johnson, B. T., & Eagly, A. H. (2014). Meta-analysis of social-personality psychological research. In H. T. Reis & C. M. Judd (Eds.), Handbook of research methods in social and personality psychology (2nd Ed., pp. 675-707). London:  Cambridge University Press. [Download Link]
  4. Overview of meta-analytic reviews (updated version of a talk Blair T. Johnson and Emily A. Hennessy presented at the CDC in April 2021). [Email Prof. Johnson if you want access to this video.]
  • The Meta-Review Phase of Research: Do You Have a Good Topic?
  1. Helpful flow chart (here) for deciding whether a review concept should be pursued.
  2. Overview of meta-reviews (updated version of a talk Emily A. Hennessy and Blair T. Johnson presented at the CDC in May 2021). [Email Prof. Johnson if you want access.]
  3. Hennessy, E. A., Johnson, B. T., & Keenan, C. (2019). Best practice guidelines and essential methodological steps to conduct rigorous and systematic meta‐reviews. Applied Psychology: Health and Well‐Being, 11(3), 353-381. [article]
  4. Hennessy, E. A., & Johnson, B. T. (2020). Examining overlap of included studies in meta‐reviews: Guidance for using the corrected covered area index. Research Synthesis Methods, 11(1), 134-145. [article]
  5. Pescatello, L. S., Hennessy, E. A., Page, W., Craft, L., Katzmarzyk, P., Fish, A., & Johnson, B. T. (2021). Best practices for meta-reviews in physical activity and health research. Journal of Physical Activity & Health. DOI: 10.1123/jpah.2021-0243
  • Literature Search
  1. UConn Librarian Hilary Kraus’s guide to developing and documenting a search strategy
  2. ISSG Search Filters Resource
  3. litsearchr is an R package to facilitate quasi-automatic search strategy development for systematic reviews. There’s a video tutorial here on YouTube (of the first version). The article introducing listsearchr is here. This software can automatically write Boolean search strings in over 50 languages, with stemming support for English.
  4. How many studies will I find? [Email Prof. Johnson if you want access to this video.]
  • Coding Studies
  1. Coding traditional study dimensions. [Email Prof. Johnson if you want access to this video.]
  2. Incorporating spatiotemporal dimensions (e.g., community- or nation-level dimensions).
    • Estimating Effect Sizes
    1. Effect size calculator
    2. Calculating effect sizes, David B. Wilson
    3. Complexities in Effect Size Calculation: Using p-values and deducing pooled standard deviations
    4. Shea B. J., Reeves, B. C., et al. (2017). AMSTAR 2: A critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ
    5. Higgins, J. P., Savović, J., Page, M. J., Elbers, R. G., & Sterne, J. A. (2019). Assessing risk of bias in a randomized trial. Cochrane handbook for systematic reviews of interventions, 6, 205-228. [link]
    • Presentation of Systematic Reviews and Meta-Analyses
    1. Shiny app to create a PRISMA flow diagram
    2. What is the PRISMA guideline and what’s new in the 2020 guideline?
    3. APA’s Meta-Analysis Reporting Standards (MARS)
    • External Resource Lists
    1. HubMeta’s related links
    2. Harvard’s Systematic Reviews and Meta Analysis page

      Notes. Prof. Johnson’s YouTube channel is here. These resources compiled as of Monday, 02 May 2022. Please email suggestions to Prof. Johnson.

      Synonyms and related terms: Meta-analysis. Evidence synthesis. Quantitative review. Meta-synthesis. Meta-review. Meta-regression. Big data. Generalizable knowledge.