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Physical Review Physics Education Research
written by Ben Van Dusen and Jayson M. Nissen
[This paper is part of the Focused Collection on Quantitative Methods in PER: A Critical Examination.] Physics education researchers (PER) often analyze student data with single-level regression models (e.g., linear and logistic regression). However, education datasets can have hierarchical structures, such as students nested within courses, that single-level models fail to account for. The improper use of single-level models to analyze hierarchical datasets can lead to biased findings. Hierarchical models (also known as multilevel models) account for this hierarchical nested structure in the data. In this publication, we outline the theoretical differences between how single-level and multilevel models handle hierarchical datasets. We then present analysis of a dataset from 112 introductory physics courses using both multiple linear regression and hierarchical linear modeling to illustrate the potential impact of using an inappropriate analytical method on PER findings and implications. Research can leverage multi-institutional datasets to improve the field's understanding of how to support student success in physics. There is no post hoc fix, however, if researchers use inappropriate single-level models to analyze multilevel datasets. To continue developing reliable and generalizable knowledge, PER should use hierarchical models when analyzing hierarchical datasets. The Supplemental Material includes a sample dataset, R code to model the building and analysis presented in the paper, and an HTML output from the R code.
Physical Review Physics Education Research: Volume 15, Issue 2, Pages 020108
Subjects Levels Resource Types
Classical Mechanics
- General
Education - Basic Research
- Assessment
= Methods
- Research Design & Methodology
= Data
= Evaluation
= Statistics
= Validity
General Physics
- Physics Education Research
Mathematical Tools
- Statistics
Other Sciences
- Mathematics
- Graduate/Professional
- Reference Material
= Article
PER-Central Type Intended Users Ratings
- PER Literature
- Researchers
- Professional/Practitioners
- Administrators
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text/html
Access Rights:
Free access
License:
This material is released under a Creative Commons Attribution 3.0 license.
Rights Holder:
American Physical Society
DOI:
10.1103/PhysRevPhysEducRes.15.020108
NSF Number:
DUE-1525338
Keywords:
hierarchical linear model, regression models, research based assessment, research-based assessment, simple regression models
Record Creator:
Metadata instance created August 23, 2019 by Sam McKagan
Record Updated:
March 11, 2023 by Caroline Hall
Last Update
when Cataloged:
July 3, 2019
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Record Link
AIP Format
B. Van Dusen and J. Nissen, , Phys. Rev. Phys. Educ. Res. 15 (2), 020108 (2019), WWW Document, (https://doi.org/10.1103/PhysRevPhysEducRes.15.020108).
AJP/PRST-PER
B. Van Dusen and J. Nissen, Modernizing use of regression models in physics education research: A review of hierarchical linear modeling, Phys. Rev. Phys. Educ. Res. 15 (2), 020108 (2019), <https://doi.org/10.1103/PhysRevPhysEducRes.15.020108>.
APA Format
Van Dusen, B., & Nissen, J. (2019, July 3). Modernizing use of regression models in physics education research: A review of hierarchical linear modeling. Phys. Rev. Phys. Educ. Res., 15(2), 020108. Retrieved February 29, 2024, from https://doi.org/10.1103/PhysRevPhysEducRes.15.020108
Chicago Format
Van Dusen, Ben, and Jayson Nissen. "Modernizing use of regression models in physics education research: A review of hierarchical linear modeling." Phys. Rev. Phys. Educ. Res. 15, no. 2, (July 3, 2019): 020108, https://doi.org/10.1103/PhysRevPhysEducRes.15.020108 (accessed 29 February 2024).
MLA Format
Van Dusen, Ben, and Jayson Nissen. "Modernizing use of regression models in physics education research: A review of hierarchical linear modeling." Phys. Rev. Phys. Educ. Res. 15.2 (2019): 020108. 29 Feb. 2024 <https://doi.org/10.1103/PhysRevPhysEducRes.15.020108>.
BibTeX Export Format
@article{ Author = "Ben Van Dusen and Jayson Nissen", Title = {Modernizing use of regression models in physics education research: A review of hierarchical linear modeling}, Journal = {Phys. Rev. Phys. Educ. Res.}, Volume = {15}, Number = {2}, Pages = {020108}, Month = {July}, Year = {2019} }
Refer Export Format

%A Ben Van Dusen %A Jayson Nissen %T Modernizing use of regression models in physics education research: A review of hierarchical linear modeling %J Phys. Rev. Phys. Educ. Res. %V 15 %N 2 %D July 3, 2019 %P 020108 %U https://doi.org/10.1103/PhysRevPhysEducRes.15.020108 %O application/pdf

EndNote Export Format

%0 Journal Article %A Van Dusen, Ben %A Nissen, Jayson %D July 3, 2019 %T Modernizing use of regression models in physics education research: A review of hierarchical linear modeling %J Phys. Rev. Phys. Educ. Res. %V 15 %N 2 %P 020108 %8 July 3, 2019 %U https://doi.org/10.1103/PhysRevPhysEducRes.15.020108


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The AIP Style presented is based on information from the AIP Style Manual.

The AJP/PRST-PER presented is based on the AIP Style with the addition of journal article titles and conference proceeding article titles.

The APA Style presented is based on information from APA Style.org: Electronic References.

The Chicago Style presented is based on information from Examples of Chicago-Style Documentation.

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Modernizing use of regression models in physics education research: A review of hierarchical linear modeling:

Is Part Of Focused Collection of Physical Review PER: Quantitative Methods in PER: A Critical Examination

A link to the full APS juried collection on quantitative methods in PER.

relation by Caroline Hall

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