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### perfect separation logistic regression [duplicate]

in continuity to the post stepwise logistic regression non significative variables(high p-values) and as demanded by matthew this is a post explaining the data i have and the problem in fact i have a ...
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### How to detect perfect separation of logistic regression? [duplicate]

I have same error message as in this post. However all my coefficients look normal with no inflated value or standard errors. My question is how can I make sure the error message is a sign of perfect ...
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### Logistic regression model does not converge

I've got some data about airline flights (in a data frame called flights) and I would like to see if the flight time has any effect on the probability of a ...
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### Is there any intuitive explanation of why logistic regression will not work for perfect separation case? And why adding regularization will fix it?

We have many good discussions about perfect separation in logistic regression. Such as, Logistic regression in R resulted in perfect separation (Hauck-Donner phenomenon). Now what? and Logistic ...
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### Understanding complete separation for logistic regression [duplicate]

Why does logistic regression not converge for a linearly separable data set? For linear separable data sets the model parameters go to infinity when mimizing the error function (according to ...
1k views

### Unstable logistic regression when data not well separated

There are some good answers discussing convergence issues of logistic regression when the data are well separated here and here. I am wondering what can cause convergence issues when the data are not ...
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### How to describe and present the issue of perfect separation?

Folks who work with logistic regression are familiar with the issue of perfect separation: if you have a variable specific values of which are associated with only one of the two outcomes (say a ...
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### Why one result is so wide in this logistic multiple regession

I am doing multiple logistic regression with data with 24 predictor variables and 193 rows. All predictor variables have values of 0 or 1 and outcome variables (OUTVAR) also has only 2 possibilities. ...
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### Perfect separation error message for glm with binomial but not with quasibinomial family

I am attempting to create a model which looks at the effect that age, supplementary food use, and nest initiation date (converted to Julian days) is having on female reproductive success (success =1 ...
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### Iteratively Reweighted Least squares for logistic regression when features are dependent?

I was solving logistic regression using IRLS (wiki) described in the wiki link. Now I have a doubt, if $X$ has dependent features then $X^TS_kX$ will not have full rank and thus will not be invertible ...
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### Connections between Logistic Regression and Linear Programming

This post Testing for Linear Separability with Linear Programming in R, discusses using linear programming to test if data is linear separable. What's the connection (if there are any) between LP ...
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### If logistic regression is a linear classifier why does it fail on linearly separable data?

Logistic regression is a linear model, decision boundary generated is linear. If the data points are linearly separable, then why does Logistic regression fail? Shouldn't it perform better on data ...
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### Binomial GLM - non-significant difference between 100% opposite groups of observations

What follows is a basic question concerning Binomial GLM's. Suppose we have a set of observations where a binary response was measured in three different treatments, A, C and D - ...