A primer for handling missing values in the analysis of education and training data
Quantitative research in vocational education and training (VET) is routinely affected by missing or incomplete information. However, the handling of missing data in published VET research is often sub-optimal, leading to a real risk of generating results that can range from being slightly biased to being plain wrong. Given that the growing availability of data from large-scale surveys and administrative collections offers exciting new opportunities for quantitative VET research, it is important that researchers follow best-practice approaches when using such data in their own work. Against th ... Show more
Authors: Gemici, Sinan; Bednarz, Alice; Lim, Patrick
Published: Maleny, Queensland, e-Content Management, 2012
Resource type: Article
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