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

Multivariate Behavioral Research
John J McArdleSteven M Boker

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 > 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 ...Continue Reading

Citations

Oct 1, 2015·International Journal of Law and Psychiatry·Jeffrey L Derevensky, Sally M Gainsbury

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Methods Mentioned

BETA
IEC

Software Mentioned

Mx
LISREL
Plus
Mplus
- MIXED
HLM
- NLMIXED
SAS
GRAT
QUALPTS

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