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The Use and Interpretation of Logistic Regression in Higher Education Journals: 1988–1999

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Abstract

This article examines the use and interpretation of logistic regression in three leading higher education research journals from 1988 to 1999. The journals were selected because of their emphasis on research, relevance to higher education issues, broad coverage of research topics, and reputable editorial policies. The term “logistic regression” encompasses logit modeling, probit modeling, and tobit modeling and the significance tests of their estimates. A total of 52 articles were identified as using logistic regression. Our review uncovered an increasingly sophisticated use of logistic regression for a wide range of topics. At the same time, there continues to be confusion over terminology. The sample sizes used did not always achieve a desired level of stability in the parameters estimated. Discussion of results in terms of delta-Ps and marginal probabilities was not always cautionary, according to definitions. The review is concluded with recommendations for journal editors and researchers in formulating appropriate editorial policies and practice for applying the versatile logistic regression technique and in communicating its results with readers of higher education research.

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Authors and Affiliations

  1. Department of Counseling and Educational Psychology, school of Education, Indiana University, Room 4050, 201 N. Rose Ave., Bloomington, IN 47405-1006

    Chao-Ying Joanne Peng

  2. Indiana University–Bloomington, USA

    Tak-Shing Harry So & Edward P. St. John

  3. New York University, USA

    Frances K. Stage

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  1. Chao-Ying Joanne Peng
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  2. Tak-Shing Harry So
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  3. Frances K. Stage
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  4. Edward P. St. John
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Correspondence to Chao-Ying Joanne Peng.

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Peng, CY.J., So, TS.H., Stage, F.K. et al. The Use and Interpretation of Logistic Regression in Higher Education Journals: 1988–1999. Research in Higher Education 43, 259–293 (2002). https://doi.org/10.1023/A:1014858517172

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