Heyo! I am finally doing a blog post again - was able to update the site with my newest publications, several new packages, and presentations. Check out the research presentation page for updates on presentations given this year, including several workshops (with provided code).
Packages:
- Buchanan, E. M. (2024). visualizemi: Visualization, Effect Size, and Replication of Measurement Invariance for Registered Reports. R package version 0.0.1. https://github.com/doomlab/visualizemi
- Buchanan, E. M. (2024). Visualizing Sensitivity. R package version 0.1.3. doi: 10.32614/CRAN.package.ViSe https://github.com/doomlab/vise
Papers:
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Buchanan, E. M. (2024). visualizemi: Visualization, Effect Size, and Replication of Measurement Invariance for Registered Reports. Assessment, X, XX-XX. doi: 10.1177/10731911241280763 https://osf.io/9hzfe/
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Höfler, M., Pronizius, E., & Buchanan, E. M. (2024). How large must an associational mean difference be to support a causal effect?. Methodology, X, XX–XX. https://doi.org/10.31234/osf.io/5jucg
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Kerschbaumer, S. et al. (2024). VALID: A Checklist-Based Approach for Improving Validity in Psychological Research. Advances in Methods and Practices in Psychological Science, X, XX–XX. doi: 10.1177/25152459241306432/