Questions tagged [separation]
Separation occurs when some classes of a categorical outcome can be perfectly distinguished by a linear combination of other variables.
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How to deal with the "sure probability" (p=1) in logistic regression
The logistic regression model is:
$$\log\bigg(\frac{p}{1-p}\bigg) = \ldots$$
The most interesting case (for me) is the case that we have $p=1$ and $p=0$. But in this case, the ratio $p/(1-p)$ doesn'...
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Probit model: marginal effects cannot be estimated because one dummy variable was dropped for predicting failure perfectly
I have a basic question about the -margins- command in Stata: I was wondering if there was a workaround to run marginal effects for a model where one of the dummy ...
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Large value of exp (B) in binary logistic regression SPSS what is wrong? [duplicate]
I had a very large value for Exp(B) in SPSS binary logistic regression. What is wrong and what should I do?
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Logit model - none of the cases vary on one predictor
What do you do with a categorical predictor (e.g. Black-White-Hispanic) in a logistic model when none of the cases are White, but about half the population studied is? You have to drop this predictor ...
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What is the probability that $n$ random points in $d$ dimensions are linearly separable?
Given $n$ data points, each with $d$ features, $n/2$ are labeled as $0$, the other $n/2$ are labeled as $1$. Each feature takes a value from $[0,1]$ randomly (uniform distribution). What's the ...
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Trained Logistic Regression returns 'NAN' for some out of sample data
I'm using MATLAB R2015a, glmfit function for training and glmval for out of sample ...
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perfect variable separation, determine cutoff via ROCR package in R
I am developing a logistic regression model where perfect variable separation occurs. I want to calculate a cutoff from this data. Interestingly, the length of the slot ...
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Using results of Canonical Discriminant Analysis to get overall variable importance?
I have a dataset with thousands of observations pre-assigned to 18 groups and with measures for 8 different variables. I am using canonical discriminant analysis to see how separable my 18 groups are. ...
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How to deal with separation in logistic regression? [duplicate]
I'm running a binary logistic regression on 15 independent variables for 180 observations in Stata (version 11). This I do for four different groups, i.e. four dependent variables. For three, it works ...
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Binomial glmm with a categorical variable with full successes
I am running a glmm with a binomial response variable and a categorical predictor. The random effect is given by the nested design used for the data collection. The data looks like this:
...
AtiQP
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Mixed logistic model with complete separation [duplicate]
I want am trying to produce a mixed logistic model but certain explanatory variables suffer from complete separation. I am aware that I need to either use exact logistic regression or a firth ...
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2D projection to maximise separability
I have a set of 500 points in 5D. Each point belongs to one of five classes, and the class labels are known.
I’d like to visualise the dataset in 2D such that the classes would be separated as much ...
- 5,461
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1
answer
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High p-values for logistic regression variable that perfectly separates?
I'm using R to run some logistic regression. My variables were continuous, but I used cut to bucket the data. Some particular buckets for these variables always result in dependent variable being ...
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Seeking a Theoretical Understanding of Firth Logistic Regression
I am trying to understand Firth logistic regression (method of handling perfect/complete or quasi-complete separation in logistic regression) so I can explain it to others in simplified terms. Does ...
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Model selection with Firth logistic regression
In a small data set ($n\sim100$ ) that I am working with, several variables give me perfect prediction/separation. I thus use Firth logistic regression to deal with the issue.
If I select the best ...
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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 the analysis of deviance of glm gives df=0 for one covariate?
I am applying a logistic regression on the effect of dose, age, PS, menopausal and pairID on the response variable. The data come from a case-control study where controls were matched/paired based on ...
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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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A categorical variable in glm shows significance from analysis of deviance, but each level is not significant in z-test
I am fitting a generalized linear model (glm). The explanatory variable is categorical with three levels (control, treat1, treat2). The response variable is 0 or 1.
The response rate for each ...
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What causes perfect prediction but no significant predictors in logistic regression?
I want to do a logistic regression with R.
I have 18 continuous covariates and a sample consisting of 100 observations.
When I enter all of the covariates into the ...
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Separation in logistic regression in a complex survey?
Firth's penalized maximum likelihood estimates, exact logistic regression and Bayesian logistic regression (e.g. bayesglm) can account for separation in logistic regression. But how to account for ...
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Enormous coefficients in logistic regression - what does it mean and what to do?
I get enormous coefficients during logistic regression, see coefficients with krajULKV:
...
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CI for logistic regression
What does it means if no CI was given for binary logistic regression analysis in SPSS output?
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Logistic regression in R resulted in perfect separation (Hauck-Donner phenomenon). Now what? [duplicate]
I'm trying to predict a binary outcome using 50 continuous explanatory variables (the range of most of the variables is $-\infty$ to $\infty$). My data set has almost 24,000 rows. When I run ...
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How to deal with quasi-complete separation in a logistic GLMM?
Update: Since I now know that my problem is called quasi-complete separation I updated the question to reflect this (thanks to Aaron).
I have a dataset from an experiment in which 29 human ...
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Suggest an exhaustive procedure that will find a separating vector for linearly separable pattern in a finite number of steps
I read in a pattern classification text, that if we consider weight vectors whose components are integer valued, the perceptron procedure would terminate in a finite number of steps.
What is the ...
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How does one prove that a separating hyper-plane exists for a linearly separable pattern?
How does one prove that a separating hyper-plane that can be represented as a linear combination of the training samples exists for a linearly separable pattern?
Although, it looks pretty obvious ...
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How to deal with perfect separation in logistic regression?
If you have a variable which perfectly separates zeroes and ones in target variable, R will yield the following "perfect or quasi perfect separation" warning message:
...
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Unexpected singularities in the Hessian matrix error in multinomial logistic regression
I have been doing multinomial logistic regression analysis using SPSS 19.
I have encountered the following problem when I run the analysis procedure:
"Unexpected singularities in the
Hessian ...
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2
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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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