This is the syntax for accounting for missing data/imputing data with large scale assessments (without plausible values). This is Appendix A and accompanies the article: Huang, F., & Keller, B. (2025). Working with missing data in large-scale assessments. Large-scale Assessments in Education. doi: 10.1186/s40536-025-00248-9
Apr 17, 2025
This is the syntax for accounting for missing data/imputing data with large scale assessments (with plausible values). This accompanies the article: Huang, F., & Keller, B. (2025). Working with missing data in large-scale assessments. Large-scale Assessments in Education. doi: 10.1186/s40536-025-00248-9
Apr 17, 2025
The article is open access. Additional syntax can also be seen here. An updated, corrected version of the article can be accessed here.
Apr 16, 2025
Mar 28, 2025
Feb 1, 2025
Article is open access. The mixPV function can now be accessed by installing the MLMusingR package.
Mar 1, 2024
CR2 plug in for SPSS can be downloaded from: https://github.com/flh3/CR2
Jan 1, 2023
Check out the latest info on the book here sample chapters additional code and an online appendix errata Some reviews: A major strength of this book is its accessibility. Huang effortlessly bridges the divide between the sometimes-abstruse literature on advanced statistics and the needs of applied researchers who lack extensive quantitative training. The result is an approachable text that covers all the basics, but also does not shy away from important advanced topics such as diagnostics, detecting and handling heteroscedasticity, and missing data handling methods. This book would make not only a useful guide to the application of multilevel modeling, but could also serve as an excellent companion text for a course on multilevel modeling. - Kristopher J. Preacher, Vanderbilt University
Jan 1, 2023
Robust standard errors for multilevel models.
Jan 1, 2023
The SPSS version can be accessed here: https://github.com/flh3/CR2/tree/master/SPSS
Jan 1, 2022