references.bib

@article{Wilkinson1999Statistical,
title={Statistical Methods in Psychology Journals: Guidelines and Explanations},
author={Leland Wilkinson},
journal={American Psychologist},
year={1999},
volume={54},
pages={594-604},
doi={10.1037/0003-066X.54.8.594}}

@article{Dunlap1998Interpretations,title={Interpretations of Multiple Regression Borrowed From Factor Analysis and Canonical Correlation},
author={W. Dunlap and R. Landis},
journal={Journal of General Psychology},
year={1998},
volume={125},
pages={397-407},
doi={10.1080/00221309809595345}}

@article{Thompson1998,title={Five methodology errors in educational research:Apantheon of statistical significance and other faux pas},
author={B. Thompson},
journal={Advances in social science methodology},
year={1999},
volume={5},
pages={23-86},
url={https://files.eric.ed.gov/fulltext/ED419023.pdf}}

@misc{PSUStat505Bivariate,
  author = {{Pennsylvania State University}},
  title = { Bivariate Normal Distribution},
  year = {2024},
  url = {https://online.stat.psu.edu/stat505/lesson/4/4.2},
  note = {Accessed: 2024-05-13}
}

@article{McCabe2021,
title={Interpreting Interaction Effects in Generalized Linear Models of Nonlinear Probabilities and Counts},
author={Connor J. McCabe and M. Halvorson and K. King and Xiaolin Cao and Dale S Kim},
journal={Multivariate Behavioral Research},
year={2021},
volume={57},
pages={243 - 263},
doi={10.1080/00273171.2020.1868966}}

@book{mccullagh1989,
author = {McCullagh, P. and Nelder, J.A.}, 
isbn = {9780412317606}, 
keywords = {GLM reference statistics},
publisher = {Chapman \& Hall},
series = {Chapman and Hall/CRC Monographs on Statistics and Applied Probability Series},
title = {Generalized Linear Models, Second Edition}, 
year = 1989,
url={https://www.utstat.toronto.edu/~brunner/oldclass/2201s11/readings/glmbook.pdf}} 

@article{Chen2003,
  author = {Chen, J. J.},
  title = {Communicating complex information: the interpretation of statistical interaction in multiple logistic regression analysis},
  journal = {American Journal of Public Health},
  year = {2003},
  month = {Sep},
  volume = {93},
  number = {9},
  pages = {1376-1377},
  note = {Author reply 1377},
  doi = {10.2105/ajph.93.9.1376-a},
  pmid = {12948938},
  pmcid = {PMC1447969}
}

@book{Hastie2015,
author = {Hastie, Trevor and Tibshirani, Robert and Wainwright, Martin},
title = {Statistical Learning with Sparsity: The Lasso and Generalizations},
year = {2015},
isbn = {1498712169},
publisher = {Chapman \& Hall/CRC},
url={https://www.ime.unicamp.br/~dias/SLS.pdf}}

@Manual{R-RegrCoeffsExplorer,
  title        = {RegrCoeffsExplorer: Efficient Visualization of Regression Coefficients for lm(), glm(), and glmnet() Objects},
  author       = {Vadim Tyuryaev and Aleksandr Tsybakin and Jane Heffernan and Hanna Jankowski and Kevin McGregor},
  year         = {2024},
  note         = {R package version 1.1.0},
  doi          = {10.32614/CRAN.package.RegrCoeffsExplorer},
  url          = {https://CRAN.R-project.org/package=RegrCoeffsExplorer},
  abstract     = {The visualization tool offers a nuanced understanding of regression dynamics, going beyond traditional per-unit interpretation of continuous variables versus categorical ones. It highlights the impact of unit changes as well as larger shifts like interquartile changes, acknowledging the distribution of empirical data. Furthermore, it generates visualizations depicting alterations in Odds Ratios for predictors across minimum, first quartile, median, third quartile, and maximum values, aiding in comprehending predictor-outcome interplay within empirical data distributions, particularly in logistic regression frameworks.},
  publisher    = {Comprehensive R Archive Network (CRAN)},
  maintainer   = {Vadim Tyuryaev <vadim.tyuryaev@gmail.com>},
  license      = {MIT + file LICENSE}
}