Using Hierarchical Linear Modeling to Study Social Contexts: The Case of School Effects
Abstract
This article focuses on a particular educational context, the school, and how characteristics of the structure and organization of high schools influence students' academic development. The emphasis is on a type of quantitative inquiry called school effects research. It describes a methodology that is most appropriate for conducting studies of school effects in particular and educational contexts in general: hierarchical linear modeling (HLM). Two previously published studies are used as heuristic examples of school effects studies conducted with HLM methods. Both studies use large and nationally representative longitudinal data from the National Education Longitudinal Study of 1988 to explore school effects on learning and its social distribution by student socioeconomic status. Study 1 focuses on the effects of high school size on learning. Study 2 focuses on how teachers' attitudes, taken as a collective property of the social organization of schools, influence both learning and its social distribution. Implications for both policy and research are discussed.
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Intraclass correlation values for all measures between time points were >0.10, indicating sufficient nesting of observations within individuals for mixed model fitting.
“All values are Ͼ0.10, which indicates sufficient nesting of observations within individuals, necessary for mixed model fitting procedures (Lee, 2000;Ordaz et al., 2013).”
From Longitudinal Changes in Adolescent Risk-Taking: A Comprehensive Study of Neural Responses to Rewards, Pubertal Development, and Risk-Taking Behavior (2015) · cites this paper as Lee, 2000
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“Despite the controversy and research that study sparked among psychologists about the effects of teacher expectations on student outcomes, its conclusions have been confirmed (e.g., Brophy, 1983; Cooper, Findley, & Good, 1982; Cooper & Tom, 1984; Raudenbush, 1984; Weinstein, Madison, & Kuklinski, 1995).”
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Schools as Developmental Contexts During Adolescence
Eccles, J. S., & Roeser, R. W. (2011) · Journal of Research on Adolescence · doi:10.1111/j.1532-7795.2010.00725.x · Cited by 1,629 · see citing works
Skiba, R. J., Chung, C.-G., Trachok, M., Baker, T. L., Sheya, A., & Hughes, R. L. (2014) · American Educational Research Journal · doi:10.3102/0002831214541670 · Cited by 691 · see citing works
Braams, B. R., van Duijvenvoorde, A. C. K., Peper, J. S., & Crone, E. A. (2015) · The Journal of Neuroscience · doi:10.1523/jneurosci.4764-14.2015 · Cited by 617 · see citing works
“10, which indicates sufficient nesting of observations within individuals, necessary for mixed model fitting procedures (Lee, 2000; Ordaz et al., 2013).”
Longitudinal Growth Curves of Brain Function Underlying Inhibitory Control through Adolescence
Ordaz, S. J., Foran, W., Velanova, K., & Luna, B. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.1741-13.2013 · Cited by 302 · see citing works
The Effectiveness of the Learning to BREATHE Program on Adolescent Emotion Regulation
Metz, S. M., Frank, J. L., Reibel, D., Cantrell, T., Sanders, R., & Broderick, P. C. (2013) · Research in Human Development · doi:10.1080/15427609.2013.818488 · Cited by 269 · see citing works
Early Childhood Mental Health Consultation: Results of a Statewide Random-Controlled Evaluation
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- Authors
- Lee, V. E.
- Affiliations
- University of Michigan (US)
- Corresponding author
- Lee, Valerie E.
- Venue
- Educational Psychologist
- Publisher
- Informa UK Limited
- Published
- 2000-06-01
- Volume
- 35
- Issue
- 2
- Pages
- 125-141
- ISSN
- 0046-1520 (ISSN-L)
- 1532-6985
- OpenAlex
- W2008585658
- Cited by
- 580
- References
- 2
- Citations by year
- 2026: 23 · 2025: 20 · 2024: 27 · 2023: 37 · 2022: 24 · 2021: 32 · 2020: 21 · 2019: 36 · 2018: 18 · 2017: 28 · 2016: 26 · 2015: 33 · 2014: 29 · 2013: 29 · 2012: 27
- FWCI
- 25.49
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Educational Psychologist (publishedVersion)
- Topics
- Social Sciences › Education › School Choice and Performance
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Social Sciences › Decision Sciences › Information Systems and Management › Educational Assessment and Improvement
- Keywords
- school influence, multilevel analysis, high school size, teacher attitudes, academic performance, socioeconomic status, school organization, National Education Longitudinal Study of 1988, education policy
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