Literaturnachweis - Detailanzeige
| Autor/inn/en | Gemici, Sinan; Bednarz, Alice; Lim, Patrick |
|---|---|
| Titel | A Primer for Handling Missing Values in the Analysis of Education and Training Data |
| Quelle | In: International Journal of Training Research, 10 (2012) 3, S.233-250 (18 Seiten)Infoseite zur Zeitschrift
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| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
| ISSN | 1448-0220 |
| DOI | 10.5172/ijtr.2012.10.3.233 |
| Schlagwörter | Vocational Education; Educational Research; Data; Statistical Analysis; Research Problems; Computation; Maximum Likelihood Statistics; Simulation; Regression (Statistics); Error of Measurement; National Surveys; Longitudinal Studies; Foreign Countries; Longitudinal Surveys of Australian Youth |
| Abstract | 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 this backdrop, we: (1) provide a primer on the use of appropriate missing data methods for quantitative VET research; and (2) illustrate the detrimental effects of inefficient methods on research results via a simulation study using real-world education and training data from the Longitudinal Surveys of Australian Youth (LSAY). (Contains 4 figures and 7 tables.) (As Provided). |
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| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2017/4/10 |
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