ERIC Number: EJ1032619
Record Type: Journal
Publication Date: 2014
Abstractor: As Provided
Reference Count: 32
Working with Missing Data in Higher Education Research: A Primer and Real-World Example
Cox, Bradley E.; McIntosh, Kadian; Reason, Robert D.; Terenzini, Patrick T.
Review of Higher Education, v37 n3 p377-402 Spr 2014
Nearly all quantitative analyses in higher education draw from incomplete datasets-a common problem with no universal solution. In the first part of this paper, we explain why missing data matter and outline the advantages and disadvantages of six common methods for handling missing data. Next, we analyze real-world data from 5,905 students across 33 institutions to document how one's approach to handling missing data can substantially affect statistical conclusions, researcher interpretations, and subsequent implications for policy and practice. We conclude with straightforward suggestions for higher education researchers looking to select an appropriate method for handling missing data.
Descriptors: Data Analysis, Statistical Inference, Research Problems, Computation, Error of Measurement, Multivariate Analysis, College Students, Colleges, Higher Education, Educational Research, Researchers, Predictor Variables, Maximum Likelihood Statistics, Research Methodology, Regression (Statistics)
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Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Authoring Institution: N/A