A Multilevel Multivariate Analysis of Academic Performances in College Based on NCAA Student-Athletes

Autor/inn/en	McArdle, John J.; Paskus, Thomas S.; Boker, Steven M.
Titel	A Multilevel Multivariate Analysis of Academic Performances in College Based on NCAA Student-Athletes
Quelle	In: Multivariate Behavioral Research, 48 (2013) 1, S.57-95 (39 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0027-3171
DOI	10.1080/00273171.2012.715836
Schlagwörter	Multivariate Analysis; Multiple Regression Analysis; Hierarchical Linear Modeling; College Athletics; Athletes; College Freshmen; Prediction; Academic Achievement; Grade Point Average; Predictor Variables; High School Students; College Entrance Examinations; Scores; Credits; Graduation Rate; Computer Software; Longitudinal Studies; ACT Assessment; SAT (College Admission Test) + Suchen Sie Ihr Suchwort? Multivariate Analyse; College athletes; Collegesport; Hochschulsport; Athlet; Studienanfänger; Vorhersage; Schulleistung; Prädiktor; High school; High schools; Student; Students; Oberschule; Schüler; Schülerin; Studentin; Aufnahmeprüfung; Longitudinal study; Longitudinal method; Longitudinal methods; Längsschnittuntersuchung; Assessment; Eignungsprüfung; Eignungstest; Hochschulzulassung
Abstract	This is an application of contemporary multilevel regression modeling to the prediction of academic performances of 1st-year college students. At a first level of analysis, the data come from N greater than 16,000 students who were college freshman in 1994-1995 and who were also participants in high-level college athletics. At a second level of analysis, the student data were related to the different characteristics of the C = 267 colleges in Division I of the NCAA. The analyses presented here initially focus on the prediction of freshman GPA from a variety of high school academic variables. The models used are standard multilevel regression models, but we examine nonlinear prediction within these multilevel models, and additional outcome variables are considered. The multilevel results show that (a) high school grades are the best available predictors of freshman college grades, (b) the ACT and SAT test scores are the next best predictors available, (c) the number of high school core units taken does not add to this prediction but does predict credits attained, (d) college graduation rate has a second-level effect of a small negative outcome on the average grades, and (e) nonlinear models indicate stronger effects for students at higher levels of the academic variables. These results show that standard multilevel models are practically useful for standard validation studies. Some difficulties were found with more advanced uses and interpretations of these techniques, and these problems lead to suggestions for further research. (Contains 6 tables and 6 figures.) (As Provided).
Anmerkungen	Psychology Press. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10