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modeldiag  

Comprehensive Diagnostics for Statistical Models
View on CRAN: Click here


Download and install modeldiag package within the R console
Install from CRAN:
install.packages("modeldiag")

Install from Github:
library("remotes")
install_github("cran/modeldiag")

Install by package version:
library("remotes")
install_version("modeldiag", "0.1.0")



Attach the package and use:
library("modeldiag")
Maintained by
Emmanuel Adewuyi
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-05-28
Latest Update: 2026-05-28
Description:
Provides a unified framework for diagnosing common issues in statistical models including linear models, generalized linear models (logistic and Poisson regression), and survival models. Implements tests for multicollinearity, heteroscedasticity, autocorrelation, normality, influential observations, overdispersion, zero-inflation, and proportional hazards assumptions. Includes visualization methods for graphical diagnostics. Methods are based on established approaches including Fox and Monette (1992) <doi:10.1080/01621459.1992.10475190>, Breusch and Pagan (1979) <doi:10.2307/1911963>, and Dean and Lawless (1989) <doi:10.1080/01621459.1989.10478792>.
How to cite:
Emmanuel Adewuyi (2026). modeldiag: Comprehensive Diagnostics for Statistical Models. R package version 0.1.0, https://cran.r-project.org/web/packages/modeldiag. Accessed 17 Jul. 2026.
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