https://orcid.org/0000-0003-2661-8274
References
- DeAyala, R. J. (2009). The theory and practice of item response theory. New York, NY: The Guilford Press.
- Jakobsen, J. C., Gluud, C., Wetterslev, J., & Winkel, P. (2017). When and how should multiple imputation be used for handling missing data in randomised clinical trials–a practical guide with flowcharts. BMC Medical Research Methodology, 17(1), 10. doi:10.1186/s12874-017-0442-1
- Little, R. J. A., & Rubin, D. (2020). Statistical analysis with missing data (3rd ed.). Hoboken, NJ: Wiley.
- McKnight, P. E., McKnight, K. M., Sidani, S., & Figueredo, A. J. (2007). Missing data: A gentle introduction. New York, NY: Guilford Press.
- Myers, T. (2011). Goodbye, listwise deletion: Presenting hot deck imputation as an easy and effective tool for handling missing data. Communication Methods and Measures, 5, 297–310. doi:10.1080/19312458.2011.624490
- Schafer, J. L. (1997). Analysis of incomplete multivariate data. London: Chapman & Hall.
- Scheffer, J. (2002). Dealing with missing data. Research Letters in the Information and Mathematical Sciences, 3, 153–160.
- Sterner, W. R. (2011). What is missing in counseling research? Reporting missing data. Journal of Counseling & Development, 89, 56–62. doi:10.1002/j.1556-6678.2011.tb00060.x
- van Ginkel, J. R., Linting, M., Rippe, R. C., & van der Voort, A. (2019). Rebutting existing misconceptions about multiple imputation as a method for handling missing data. Journal of Personality Assessment, 1–12. doi:10.1080/00223891.2018.1530680
- Wang, J., & Johnson, D. E. (2019). An examination of discrepancies in multiple imputation procedures between SAS and SPSS. The American Statistician, 73(1), 80–88. doi:10.1080/00031305.2018.1437078
- Zhang, Z. (2016). Missing data imputation: Focusing on single imputation. Annals of Translational Medicine, 4(1), 1–8. doi:10.3978/j.issn.2305-5839.2015.12.38