Literaturnachweis - Detailanzeige
Autor/inn/en | Astin, Alexander W.; Denson, Nida |
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Titel | Multi-Campus Studies of College Impact: Which Statistical Method Is Appropriate? |
Quelle | In: Research in Higher Education, 50 (2009) 4, S.354-367 (14 Seiten)Infoseite zur Zeitschrift
PDF als Volltext |
Sprache | englisch |
Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
ISSN | 0361-0365 |
DOI | 10.1007/s11162-009-9121-3 |
Schlagwörter | Program Effectiveness; Least Squares Statistics; Statistical Analysis; Higher Education; Institutional Research; Research Methodology; Computer Software; Models; Outcomes of Education; Institutional Evaluation |
Abstract | In most multi-campus studies of college impact that have been conducted over the past four decades, investigators have relied on ordinary least squares (OLS) regression as the analytic method of choice. Recently, however, some investigators have advocated the use of Hierarchical Linear Modeling (HLM), a method specifically designed for analyses that involve both individual (student) and aggregate (institutional) level measures. Cross-validation analyses using a national database show that the two methods yield an equally good "fit" with empirical data. Existing OLS software has the advantage of enabling one to perform path analytical causal modeling; HLM has the advantage of yielding a more conservative estimate of the significance of institution-level effects. (As Provided). |
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Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
Update | 2017/4/10 |