442 citations · 444 across the 3 of their papers we have counts for
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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…