Wemix

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. This is an update to mixPV, load it using this function: source("https://raw.githubusercontent.com/flh3/pubdata/main/mixPV/mixPVv2.R") The function has been updated to be able to use parallel processing or multiple cores of your computer (to make computation faster). Load in the dataset. data(pisa2012, package = 'MLMusingR') The usual mixPV function can be used as normal.

Syntax to accompany the article: Huang, F. (2024). Using plausible values when fitting multilevel models with large-scale assessment data using R. Large-scale Assessments in Education. When fitting multilevel models using large scale assessments such as PISA or TIMSS, it is important to account for: the use of weights at different levels and the presence of multiple plausible values. I am often asked how do you run this analysis in R.