Multi-campus studies of college impact : which statistical method is appropriate?

Alexander W. Astin, Nida Denson

    Research output: Contribution to journalArticlepeer-review

    50 Citations (Scopus)

    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.
    Original languageEnglish
    Pages (from-to)354-367
    Number of pages14
    JournalResearch in Higher Education
    Volume50
    Issue number4
    DOIs
    Publication statusPublished - 2009

    Keywords

    • multi-campus universities
    • multilevel models (statistics)
    • statistical methods
    • university students

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