Demonstrates the impact of plausible values on statistical analyses in large-scale assessments, indicating important implications for data interpretation.
Plausible values are typically used in large-scale assessment studies, in particular, in the Trends in International Mathematics and Science Study and the Programme for International Student Assessment. Despite its large spread, there are still some questions regarding the use of plausible values and how such use affects statistical analyses. The aim of this paper is to demonstrate the role of plausible values in large-scale assessment surveys when multilevel modeling is used. Different user strategies concerning plausible values for multilevel models as well as means and variances are examined. The results show that some commonly used user strategies give incorrect results while others give reasonable estimates but incorrect standard errors. These findings are important for anyone wishing to make secondary analyses of large-scale assessment data, especially those interested in using multilevel models to analyze the data.
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Laukaityte et al. (2016) studied this question.
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