Penalized logistic regression with low prevalence exposures beyond high dimensional settings | PLOS ONE
Frontiers | Bias reduction in the logistic model parameters with the LogF(1,1) penalty under MAR assumption
Firth's logistic regression with rare events: accurate effect estimates and predictions? - Puhr - 2017 - Statistics in Medicine - Wiley Online Library
Logistic Regression for Rare Events | Statistical Horizons
Multivariable logistic regression (Firth correction) with the EASIX... | Download Scientific Diagram
An evaluation of approaches for rare variant association analyses of binary traits in related samples | Scientific Reports
Complete separation in PROC GENMOD - SAS Support Communities
Logistic: Exploring the Theoretical Foundations of Firth Logistic Regression
Logistic regression coefficient estimates obtained by maximum... | Download Scientific Diagram
Firth's Logistic Regression: Classification with Datasets that are Small, Imbalanced or Separated | by Remy Canario | DataDrivenInvestor
Complete separation in PROC GENMOD - SAS Support Communities
Firth's bias correction as a Bayesian model | Random effect
On estimation for accelerated failure time models with small or rare event survival data | BMC Medical Research Methodology | Full Text
New modifications of Firth's penalized logistic regression
Best Practices for Debugging Errors in Logistic Regression with Python | by Gabe Verzino | Towards Data Science
No rationale for 1 variable per 10 events criterion for binary logistic regression analysis | BMC Medical Research Methodology | Full Text
GitHub - cran/logistiX: Exact logistic regression including Firth correction
Firth's bias correction as a Bayesian model | Random effect
Firth's bias correction as a Bayesian model | Random effect
IJERPH | Free Full-Text | Bring More Data!—A Good Advice? Removing Separation in Logistic Regression by Increasing Sample Size
No rationale for 1 variable per 10 events criterion for binary logistic regression analysis | BMC Medical Research Methodology | Full Text
Feature Request]: additional logistic regression procedures (Firth and Heckman · Issue #1577 · jasp-stats/jasp-issues · GitHub
Firth's Logistic Regression: Classification with Datasets that are Small, Imbalanced or Separated | by Remy Canario | DataDrivenInvestor
Mathematics | Free Full-Text | A Double-Penalized Estimator to Combat Separation and Multicollinearity in Logistic Regression
Firth adjusted score function for monotone likelihood in the mixture cure fraction model | Lifetime Data Analysis
Computationally efficient whole-genome regression for quantitative and binary traits | Nature Genetics
A Comparative Study of the Bias Correction Methods for Differential Item Functioning Analysis in Logistic Regression with Rare Events Data
