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Pike, Gary R.; Rocconi, Louis M. – New Directions for Institutional Research, 2012
Multilevel modeling provides several advantages over traditional ordinary least squares regression analysis; however, reporting results to stakeholders can be challenging. This article suggests some strategies for presenting complex, multilevel data and statistical results to institutional and higher education decision makers. The article is…
Descriptors: Learner Engagement, Least Squares Statistics, Critical Thinking, Student Characteristics
Luan, Jing; Zhao, Chun-Mei – New Directions for Institutional Research, 2006
As a tour de force, data mining is likely to gain wider use in the next few years. To facilitate this transition, we make several recommendations addressed to both institutional research professionals and the Association of Institutional Research.
Descriptors: Institutional Research, Enrollment Management, Educational Research, Data Analysis
Croninger, Robert G.; Douglas, Karen M. – New Directions for Institutional Research, 2005
Many do not consider the effect that missing data have on their survey results nor do they know how to handle missing data. This chapter offers strategies for handling item-missing data and provides a practical example of how these strategies may affect results. The chapter concludes with recommendations for preventing and dealing with missing…
Descriptors: Institutional Research, Research Methodology, Surveys, Error of Measurement

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