Corpus ID: 51853906

Correcting the Quasi-complete Separation Issue in Logistic Regression Models

@inproceedings{Lu2016CorrectingTQ,
  title={Correcting the Quasi-complete Separation Issue in Logistic Regression Models},
  author={X. Lu and AmeriHealth Caritas},
  year={2016}
}

X. Lu, AmeriHealth Caritas

Published 2016

Quasi-complete separation is a commonly detected issue in logit/probit models. Quasi-complete separation occurs when the dependent variable separates an independent variable or a combination of several independent variables to a certain degree. In other words, levels in a categorical variable or values in numeric variable are separated by groups in a discrete outcome variable. Most of the time, it happens in categorical independent variable(s). Quasi-complete separation can cause convergence… CONTINUE READING

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