Although the mixPV function was introduced as a way to analyze large scale assessments using multiple plausible values (PV), the function only works if the plausible values are used as the outcome (i.e., it is the Y variable or on the left hand side [LHS] of the equation). However, there are times when the PV is the predictor of interest. This still has to be analyzed properly (i.e., just don’t average all the values).
Jun 5, 2025
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
This is an applied example regarding the use of weights in multilevel models when using large scale assessments. This is using the Germany TIMSS dataset. This accompanies the article: Atasever, U., Huang, F., & Rutkowski, L. (2025). Reassessing weights in large-scale assessments and multilevel models. Large-scale Assessments in Education. doi: 10.1186/s40536-025-00245-y
Mar 21, 2025
A common question with the use of large-scale assessments (LSAs) is related to the use of weights. Another issue is how to specify these weights properly. Software such as SAS and Mplus, when specifying weights at two levels, require the use of conditional weights at level 1 if the level-2 weight is specified (or you can just use the level-2 weights alone; see Mang et al., 2021, see bottom part of this post).
Sep 1, 2024
This is an update to: Huang, F. (2024). Using plausible values when fitting multilevel models with large-scale assessment data using R. Large-scale Assessments in Education. There is an update to the mixPV function where it is now available in the MLMusingR package (no need to load it through Github anymore). library(MLMusingR) The function has been updated to be able to use parallel processing or multiple cores of your computer (to make computation faster).
Jun 8, 2024
MLM
Apr 10, 2024
Article is open access. The mixPV function can now be accessed by installing the MLMusingR package.
Mar 1, 2024