References

Bandalos, Deborah L, and Phillip Gagné. 2012. “The Use of Monte Carlo Studies in Structural Equation Modeling Research.” In Handbook of Structural Equation Modeling, edited by Rick H. Hoyle, 92–108. New York: Guilford Press.

Burton, Andrea, Douglas G Altman, Patrick Royston, and Roger L Holder. 2006. “The Design of Simulation Studies in Medical Statistics.” Statistics in Medicine 25 (24): 4279–92.

Fan, Xitao. 2012. “Designing Simulation Studies.” In APA Handbook of Research Methods in Psychology, Vol. 2: Research Designs, edited by Harris Cooper, 427–44. Washington, DC: American Psychological Association.

Foldnes, Njål, and Steffen Grønneberg. 2017. “A Simple Simulation Technique for Nonnormal Data with Prespecified Skewness, Kurtosis, and Covariance Matrix.” Multivariate Behavioral Research 52 (4): 524–35.

Fox, John. 2016. Applied Regression Analysis and Generalized Linear Models. Third edition. Los Angeles: SAGE Publications, Inc.

Gagné, Phillip, and Carolyn F Furlow. 2009. “Misspecification in Structural Equation Modeling: The Effect of Ignoring Latent Variable Interactions on Manifest Variable Interactions.” Multivariate Behavioral Research 44 (4): 545–69.

Gonzalez, Oscar, Holly P O’Rourke, Ingrid C Wurpts, and Kevin J Grimm. 2017. “A New Approach for Identifying Complex Factor Structure Under Conditions That Violate the Assumption of Multivariate Normality.” Psychological Methods 22 (3): 545–61.

Gorman, James. 2025. “Nobel Prize Winners Show Why Immigration Is Vital to Science.” The New York Times. https://www.nytimes.com/2025/12/10/science/nobel-prize-immigrants-science.html.

Hallquist, Michael N, and Joshua F Wiley. 2018. “An Introduction to Integrating Structural Equation Models with Item Response Theory Using the Mirt Package in r.” Multivariate Behavioral Research 53 (3): 345–66.

Harwell, Michael R, Elaine N Rubinstein, William S Hayes, and Cynthia C Olds. 1992. “Summarizing Monte Carlo Results in Methodological Research: The One- and Two-Factor Fixed Effects ANOVA Cases.” Journal of Educational Statistics 17 (4): 315–39.

Hunt, David L, and Jeremy Miles. 2015. “Evaluating the Efficacy of r Packages for the Analysis of Count Data.” The R Journal 7 (2): 6–19.

Lin, Chujun. 2022. “The Power of Data Visualization.” https://doi.org/10.31234/osf.io/dnr9s.

Muthén, Linda K, and Bengt O Muthén. 2002. “How to Use a Monte Carlo Study to Decide on Sample Size and Determine Power.” Structural Equation Modeling 9 (4): 599–620.

Schoemann, Alexander M, Patrick Miller, Sunthud Pornprasertmanit, and Wei Wu. 2014. “Using Monte Carlo Simulations to Determine Power and Sample Size for Planned Missing Designs.” International Journal of Behavioral Development 38 (5): 471–79.

Skrondal, Anders. 2000. “Design and Analysis of Monte Carlo Experiments: Attacking the Conventional Wisdom.” Multivariate Behavioral Research 35 (2): 137–67.

Spector, P. 2008. Data Manipulation with r. Use r! Springer. https://books.google.com/books?id=grfuq1twFe4C.

White, Ethan P., Elita Baldridge, Zachary T. Brym, Kenneth J. Locey, Daniel J. McGlinn, and Sarah R. Supp. 2013. “Nine Simple Ways to Make It Easier to (Re)use Your Data.” PeerJ PrePrints 1 (July): e7v2. https://doi.org/10.7287/peerj.preprints.7v2.

Wickham, H. 2015. Advanced r. Chapman & Hall/CRC the r Series. CRC Press. https://books.google.com/books?id=FfsYCwAAQBAJ.

Wickham, Hadley. 2011a. “Testthat: Get Started with Testing.” The R Journal 3 (1): 5–10.

———. 2011b. “The Split-Apply-Combine Strategy for Data Analysis.” Journal of Statistical Software, Articles 40 (1): 1–29. https://doi.org/10.18637/jss.v040.i01.

———. 2014. “Tidy Data.” Journal of Statistical Software, Articles 59 (10): 1–23. https://doi.org/10.18637/jss.v059.i10.

Wickham, Hadley, and Jenny Bryan. In progress. R Packages. 2nd ed. https://r-pkgs.org.

Wickham, Hadley, and Garrett Grolemund. 2016. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. O’Reilly Media. https://books.google.com/books?id=vfi3DQAAQBAJ.