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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 ...
1 vote
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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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### What does error code "outcome = variable_name > 0 predicts data perfectly" indicate when using logistic regression in Stata? [duplicate]

I have a longitudinal dataset and I am trying to create two variables that correspond to two time periods based on specific date ranges (pre- and post-) to be able to analyze the effect of each of ...
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### Will the p value become useless in such case: logistic regression with perfect separation? [duplicate]

I think I understand the perfect separation problem in logistic regression and answered my own question in this post from optimization perspective. Is there any intuitive explanation of why logistic ...
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### Logistic regression - Exp (B) = 0? and sig is 0.999 or 1? [duplicate]

I'm having an issue with binary logistic regression for a project I'm working on. For some of the variables, I'm receiving a significance value of 0.999 and exp(B) of 0. Is this normal?
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### Error message in logistic regression model [duplicate]

I am trying to understand how both temperature (factor: 6 levels - 20, 23, 26, 29, 32, 35 degrees Celsius) and species (factor: 2 levels HA and AP) affects the likelihood of moving from one life stage ...
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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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### 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 ...
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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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### 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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### 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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### 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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### 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 - ...
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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. ...