Analyzing Multilevel Data: Comparing Findings from Hierarchical Linear Modeling and Ordinary Least Squares Regression

Autor/in	Rocconi, Louis M.
Titel	Analyzing Multilevel Data: Comparing Findings from Hierarchical Linear Modeling and Ordinary Least Squares Regression
Quelle	In: Higher Education: The International Journal of Higher Education and Educational Planning, 66 (2013) 4, S.439-461 (23 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0018-1560
DOI	10.1007/s10734-013-9615-y
Schlagwörter	Hierarchical Linear Modeling; Least Squares Statistics; Regression (Statistics); Critical Thinking; College Seniors; Institutional Characteristics; Influences; Data Analysis + Suchen Sie Ihr Suchwort? Regression; Regressionsanalyse; Kritisches Denken; College; Colleges; Senior; Hochschule; Fachhochschule; Influence; Einfluss; Einflussfaktor; Auswertung
Abstract	This study examined the differing conclusions one may come to depending upon the type of analysis chosen, hierarchical linear modeling or ordinary least squares (OLS) regression. To illustrate this point, this study examined the influences of seniors' self-reported critical thinking abilities three ways: (1) an OLS regression with the student as the unit of analysis, (2) an OLS regression with the institution as the unit of analysis, and (3) a three-level hierarchical linear model. Overall, results demonstrate that one would come to substantively different conclusions regarding the influences on students' perceived critical thinking ability depending upon the type of analysis chosen, especially in regards to the effects of the institutional characteristics. (As Provided).
Anmerkungen	Springer. 233 Spring Street, New York, NY 10013. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-348-4505; e-mail: service-ny@springer.com; Web site: http://www.springerlink.com
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10