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Handling missing data: analysis of a challenging data set using multiple imputation
2014
International Journal of Research & Method in Education
Missing data is endemic in much educational research. However, practices such as step-wise regression common in the educational research literature have been shown to be dangerous when significant data are missing, and multiple imputation (MI) is generally recommended by statisticians. In this paper, we provide a review of these advances and their implications for educational research. We illustrate the issues with an educational, longitudinal survey in which missing data was significant, but
doi:10.1080/1743727x.2014.979146
fatcat:nva6foos2zcmdhm4mbgdnn2t24