Logistic Regression in R

Suppose we wanted to produce confidence distributions for data with binary outcomes and where we employ a logistic regression, we would do the following. Here, I use the mtcars dataset for the example and also simulate some very simple binary data. We use suppressMessages() to avoid seeing the long list of profiling messages.

Cite R Packages

Please remember to cite the R packages that you use in your work.

citation("concurve")

## To cite package 'concurve' in publications use:
## 
##   Rafi Z, Vigotsky A (2026). _concurve: Computes and Plots
##   Compatibility (Confidence) Intervals, P-Values, S-Values, &
##   Likelihood Intervals to Form Consonance, Surprisal, & Likelihood
##   Functions_. R package version 3.0.0,
##   <https://CRAN.R-project.org/package=concurve>.
## 
##   Rafi Z, Greenland S (2020). "Semantic and Cognitive Tools to Aid
##   Statistical Science: Replace Confidence and Significance by
##   Compatibility and Surprise." _BMC Medical Research Methodology_,
##   *20*, 244. ISSN 1471-2288. doi:10.1186/s12874-020-01105-9
##   <https://doi.org/10.1186/s12874-020-01105-9>.
##   <https://doi.org/10.1186/s12874-020-01105-9>.
## 
## To see these entries in BibTeX format, use 'print(<citation>,
## bibtex=TRUE)', 'toBibtex(.)', or set
## 'options(citation.bibtex.max=999)'.

citation("cowplot")

## To cite package 'cowplot' in publications use:
## 
##   Wilke C (2025). _cowplot: Streamlined Plot Theme and Plot Annotations
##   for 'ggplot2'_. R package version 1.2.0,
##   <https://wilkelab.org/cowplot/>.
## 
## A BibTeX entry for LaTeX users is
## 
##   @Manual{,
##     title = {cowplot: Streamlined Plot Theme and Plot Annotations for 'ggplot2'},
##     author = {Claus O. Wilke},
##     year = {2025},
##     note = {R package version 1.2.0},
##     url = {https://wilkelab.org/cowplot/},
##   }

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References

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