Using plausible values when fitting multilevel models with large-scale assessment data using R
Francis L. Huang
Abstract
Abstract The use of large-scale assessments (LSAs) in education has grown in the past decade though analysis of LSAs using multilevel models (MLMs) using R has been limited. A reason for its limited use may be due to the complexity of incorporating both plausible values and weighted analyses in the multilevel analyses of LSA data. We provide additional functions in R that extend the functionality of the WeMix (Bailey et al., 2023) package to allow for the automatic pooling of plausible values. In addition, functions for model comparisons using plausible values and the ability to export output to different formats (e.g., Word, html) are also provided.
Topics & Concepts
Scale (ratio)Multilevel modelComputer scienceStatisticsMathematicsMachine learningCartographyGeographyStatistical Methods and Bayesian InferenceAdvanced Causal Inference TechniquesGenetic and phenotypic traits in livestock