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

被引:47
作者
Astin, Alexander W. [1 ]
Denson, Nida [2 ]
机构
[1] Univ Calif Los Angeles, Higher Educ Res Inst, Los Angeles, CA 90095 USA
[2] Univ New S Wales, Learning & Teaching UNSW, Sydney, NSW 2052, Australia
关键词
Ordinary least squares; Hierarchical linear modeling; Methodology; College effects; Stepwise regression; MODEL;
D O I
10.1007/s11162-009-9121-3
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
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.
引用
收藏
页码:354 / 367
页数:14
相关论文
共 22 条
[1]  
[Anonymous], 1997, Higher Education Handbook of Theory and Research
[2]  
Astin A.W., 1991, ASSESSMENT EXCELLENC
[3]  
Astin A.W., 1994, AM FRESHMAN NATL NOR
[4]   A decade of changes in undergraduate education: A national study of system "transformation" [J].
Astin, AW ;
Keup, JR ;
Lindholm, JA .
REVIEW OF HIGHER EDUCATION, 2002, 25 (02) :141-+
[5]  
ASTIN AW, 1996, CAUSAL ANAL MODELING
[6]  
ASTIN AW, 2007, LONG TERM EFFECTS CO
[7]  
Bohrnstedt G. W., 1971, Sociological Methodology, V3, P118, DOI DOI 10.2307/270820
[8]  
BRAUN HI, 1983, PSYCOMETRIKA, V489, P171
[9]  
Bryk Anthony S., 1992, Hierarchical linear models: Applications and data analysis methods
[10]  
Burstein L., 1980, Review of Research in Education, V8