442 citations · 446 across the 4 of their papers we have counts for
5 papers
To tune or not to tune, a case study of ridge logistic regression in small or sparse datasets
Hana Šinkovec, Georg Heinze, Rok Blagus +1
For finite samples with binary outcomes penalized logistic regression such as ridge logistic regression (RR) has the potential of achieving smaller mean squared errors (MSE) of coe…
On resampling methods for model assessment in penalized and unpenalized logistic regression
Angelika Geroldinger, Lara Lusa, Mariana Nold +1
Penalized logistic regression methods are frequently used to investigate the relationship between a binary outcome and a set of explanatory variables. The model performance can be…
Firth's logistic regression with rare events: accurate effect estimates AND predictions?
Rainer Puhr, Georg Heinze, Mariana Nold +2
Firth-type logistic regression has become a standard approach for the analysis of binary outcomes with small samples. Whereas it reduces the bias in maximum likelihood estimates of…
Tuning in ridge logistic regression to solve separation
Hana Šinkovec, Angelika Geroldinger, Georg Heinze +1
Separation in logistic regression is a common problem causing failure of the iterative estimation process when finding maximum likelihood estimates. Firth's correction (FC) was pro…
Evaluating methods for Lasso selective inference in biomedical research by a comparative simulation study
Michael Kammer, Daniela Dunkler, Stefan Michiels +1
Variable selection for regression models plays a key role in the analysis of biomedical data. However, inference after selection is not covered by classical statistical frequentist…