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Effect Displays in R for Multinomial and Proportional-Odds Logit Models: Extensions to the effects Package
Open accessAbstract
Based on recent work by Fox and Andersen (2006), this paper describes substantial extensions to the effects package for R to construct effect displays for multinomial and proportional-odds logit models. The package previously was limited to linear and generalized linear models. Effect displays are tabular and graphical representations of terms — typically high-order terms — in a statistical model. For polytomous logit models, effect displays depict fitted category probabilities under the model, and can include point-wise confidence envelopes for the effects. The construction of effect displays by functions in the effects package is essentially automatic. The package provides several kinds of displays for polytomous logit models.
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Citations
Cited by
Heiss, R., & Matthes, J. (2020) · Political Communication · doi:10.1080/10584609.2019.1661890 · Cited by 104
“To graphically depict the effects, we plotted predicted probabilities with 95% confidence intervals (CI) while setting all covariates to their mean values (see Fox & Hong, 2009).”
MethodLorenzo-Luaces, L., Wasil, A., Kacmarek, C. N., & DeRubeis, R. (2024) · JMIR Formative Research · doi:10.2196/49780 · Cited by 13
Graham‐Schmidt, K. T., Martin‐Iverson, M. T., & Waters, F. A. V. (2019) · PsyCh Journal · doi:10.1002/pchj.274 · Cited by 11
Metadata
- Authors
- Fox, J., & Hong, J.
- Venue
- Journal of Statistical Software
- Publisher
- Foundation for Open Access Statistic
- Published
- 2009
- Volume
- 32
- Issue
- 1
- ISSN
- 1548-7660 (ISSN-L)
- OpenAlex
- W1876961961
- Cited by
- 372
- References
- 0
- FWCI
- 5.78
- Type
- journal article
- Language
- en
- Open access
- diamond
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- CoChat. (2026). Citation check: Effect Displays in R for Multinomial and Proportional-Odds Logit Models: Extensions to the effects Package. https://app.cochat.ai/papers/10.18637/jss.v032.i01
- The paper
- Fox, J., & Hong, J. (2009). Effect Displays in R for Multinomial and Proportional-Odds Logit Models: Extensions to the effects Package. Journal of Statistical Software. https://doi.org/10.18637/jss.v032.i01
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
