Multi-Campus Studies of College Impact: Which Statistical Method Is Appropriate?

Autor/inn/en	Astin, Alexander W.; Denson, Nida
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 Verfügbarkeit
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 + Suchen Sie Ihr Suchwort? Statistische Analyse; Hochschulbildung; Hochschulsystem; Hochschulwesen; Institutionelle Forschung; Research method; Forschungsmethode; Analogiemodell; Lernleistung; Schulerfolg
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