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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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Linear separation in higher dimension

I am having a problem comprehending with the relation of kernel, weight and linear separation. I have a case where I am given a kernel $k_1$. that has a corresponding mapping $\phi_1$. And we ...
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Logistic Regression: How to Detect Complete AND Quasi-Separation of Data Points

I have written a logistic regression routine using the Newton-Ralphson algorithm in VBA for use in a class that I teach which uses primarily EXCEL. I want the algorithm to test for complete and quasi-...
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How to calculate if the given dataset is linearly separable or not using the given discriminant function [duplicate]

I am student and learning SVM with radial basis kernel function and want to solve the question manually by hand. but I am unable to calculate the values to find out whether the dataset is linearly ...
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43 views

How to manually calculate if the given dataset is linearly separable or not using the given discriminant function

I am student and learning SVM with radial basis kernel function and want to solve the question manually by hand. but I am unable to calculate the values to find out whether the dataset is linearly ...
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R GLMM: How to deal with separation inflating standard errors in negative binomial regression (count data)

I'm comparing counts of individuals between different localities, and between two seasons (seas_wmo with levels dry and ...
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anomaly detection : check the separability of normal and abnormal data

I'd like to develop an anomaly detection. I have historical data from sensors in the form of time series. The time series can be divided into data of a normal state and data of an abnormal state i.e. ...
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1answer
41 views

Handling quasi-perfect separation in a zero-inflated negative binomial regression in R

I want to run a zero-inflated negative binomial regression in R, but one of my variables exhibits quasi-complete separation and throws errors for both the negative binomial and logistic pieces. I've ...
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1answer
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Dealing with Complete Separation in Logistic Regression when Reporting [duplicate]

I have a question regarding how one would deal with complete separation in logistic regression when reporting the outcome for statistical analysis. For a study, we have group participants into 4 ...
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1answer
671 views

glm.fit: fitted probabilities numerically 0 or 1 occurred however culprit feature is numeric

I've been receiving the warning message in the title and have reviewed posts such as e.g. this one. I would like to understand how this feature has perfect separation with the target variable, since ...
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Dealing with complete separation in Generalized Additive Models

Related to "How to deal with perfect separation in logistic regression?": I am modelling survival using a binomial mixed model (gamm from ...
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Does separation of data matter in Bayesian power calculations with logistic regression models?

I know that, when performing power calculation based on logistic regression model, under the regular frequentist approach, power calculations become unstable if it is based on the model that causes ...
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1answer
33 views

Is there an upper bound on number of logistic regression responses that yield infinite estimates

Suppose a logistic regression problem has N observations of {0, 1} and that there are p parameters. Also assume the design matrix, X, is full rank with p < N. We know that there will be certain ...
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Logistic regression with separation and nested design in R

Data: An item can be in the state 0 or 1 (binary). Each year, it starts in the state 0 and then changes to state 1. I have data of 4 seasons (2010 -2013). Each year I sampled the (same) individuals ...
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229 views

GLMM for count data using square root link in lme4

I have data from a field survey. The objective of the study is to relate number of seedling (respond variable, count data), landform (exploratory variable, categorical variable with 3 levels) and ...
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1answer
75 views

Kullback-Leibler Divergence as the class separation measure

I am trying to use KL divergence as the separation measure between the classes. I have the positive, negative samples for 2 distributions and want to adjust the algorithm parameters to get the best ...
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how to report marginal effects of variables omitted due to perfect separation?

i have a few variables that come up as omitted in a probit model but are necessary for a later heckman model, when i write up my results what is the custom for reporting the missing coefficients in ...
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any problems with Firths Logit model (to deal with separation)

I am performing a Logit Model on binary variable SALE, when running on stata some of my explanatory variables were dropped as they were "perfect predictors". after some reading i believe the problem ...
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1answer
66 views

Zero Centering Data

Does zero centering your data make it more linearly separable or does that not affect the separability? I read that by zero-centering the data, it allows algorithms to train faster because small ...
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1answer
118 views

Can I run a logistic regression with a small sample size and perfect convergence?

I'm hoping someone will be able to help me with my question. I have a dataset with 71 records and 4 variables. Three of the four variables are independent, and one is dependent. All four variables are ...
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1answer
72 views

R/Stata Can I include a categorical variable in a Logistic regression when one of its values perfectly predicts one of the outcomes?

Suppose I have the following data df = data.table('y'= c(1,1,1,1,1,1,1,0,0,0,0), 'x' = c(1,1,1,1,1,1,1,1,1,0,0)) where x = 0 perfectly predicts y = 0. I ...
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1answer
548 views

How to tell which variable is perfectly separated in R [duplicate]

I am running a logistic regression model in R using glm. I received a warning that complete separation occurred. How do I determine which variable is causing this? R doesn't tell you what variable is ...
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1answer
409 views

Why do we sum the cost function in a logistic regression?

I get the intuition behind the loss function for linear regression, which happens to be the MSE function. We have a set of points and we try to fit a line between them so that the line is at a minimum ...
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1answer
436 views

Abnormally high standard error in binary logistic regression

I did a binary logistic regression test on SPSS with a sample size of 24. The study is about the correlation of teenage pregnancy and depressive symptoms. Of the 24, 11 are pregnant teenagers. Of the ...
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1answer
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Issue with complete separation in logistic regression (in R)

I am trying to fit a logistic regression model for business defaults. Apart from the dichotomous variable default, the data set includes some performance ratios. When estimating the model in R, the ...
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When logits are too large in logistic regression, are statistics and p values still interpretable?

I am using glmer() in r to run a mixed logistic regression with 3 categorical (dichotomous) predictors. The outcome measure is whether or not a participant responded correctly to a memory check. This ...
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1answer
1k views

fitted probabilities in logistic regression [closed]

Is the only reason why fitted probabilities of 0 or 1 occur is that some of your predicting variables(x) are perfect linear combinations of the target(y) variable? Is there any other reason?
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1answer
116 views

How do I deal with a perfect fitted model?

I have a data set where one independent variable perfectly predicts the outcome. Specifically, age will perfectly predict if the user will buy the product. However, I also have a number of other ...
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2answers
276 views

How does perfect separation in logistic regression affect the AUC?

I have been working with perfect separation in logistic regression, and I have been assessing models with the AUC statistic. I was wondering what effect perfect separation has on the AUC. My own ...
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How to calculate a perfect separation in a d dimensional space between n class?

Assuming in a d-dimensional space, we have samples from n class. The best way of separating samples of each class from each other is to have the samples from each class as far as possible from every ...
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1answer
1k views

I think my logistic model is overfitted even with Lasso? R gives me a perfect separation warning message

I have a survey with 25 variables (160 observations for each var). Most are categorical, some are continuous. The variable of interest is categorical (binomial). If I do: ...
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2answers
596 views

How to identify linearly separable datasets

Usually, when I am given a dataset of $d\le 3$, I just plot the data and observe if linearly separable behaviour exists. When the dataset is of high dimensionality, I always follow a simple trick to ...
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0answers
141 views

Does SVM suffer from Quasi-complete separation or perfect separation?

Are SVMs, which use the hinge loss, suffer from Quasi-complete separation or perfect separation? Why or why not? Could you please give mathematical justification?
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2answers
66 views

Clustering Separable but Unequally Sized Clusters

I am trying to cluster the data shown below. The clusters are clearly separable. I've tried k-means and EM clustering (Gaussian mixture), however, both techniques divide the large main cluster into ...
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1answer
821 views

Logistic Regression: p values all '1', yet model fits perfectly [duplicate]

I was trying to help a student and was foxed by this Logistic Regression problem and seek your explanation. Here's some economic data. All we have to do is create a model to predict whether the ...
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2answers
2k views

Logistic Regression is a Convex Problem but my results show otherwise?

I know that logistic regression is a convex problem. Furthermore, from Lemma 1.17 in these optimization lecture notes, if a function $f : \mathbb{R}^n \rightarrow \mathbb{R}$ is convex, then the ...
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Why is it desirable to have linear separability in SVM?

Ref to above image, clearly a circle can separate the two classes(left image). Why then take so much pain to map it to a function to make it linearly separable (right image) ? Can anyone please ...
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337 views

Handling errors: “fitted probabilities numerically 0 or 1 occurred”, can these be ignored/averaged out in a simulation with many trials?

I have been getting the following errors in R because of trying to fit propensity scores that are well-stratified. I am currently looping over a model simulation ...
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1answer
305 views

How can a logistic regression model have predictors that are highly insignificant and still perform excellently in the test dataset?

I have built a classification model using a highly imbalanced dataset to be found in the ROSE package of R called hacide, containing 1,000 observations of which only 2% are positive. My model ...
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2answers
1k views

Is it possible to simulate logistic regression without randomness?

We can simulate linear regression without randomness, which means we make $y=X\beta$ instead of $y=X\beta+\epsilon$. Then if we fit a linear model the coefficients will be identical to the "ground ...
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248 views

A mixed effect regression tool based on bayesian priors like bayesglm

I use extensively Gelman's bayesglm for the every day use due to the great stability of the estimates especially in the case of separation. Unfortunately I could not find an equivalent of empirical ...
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1answer
74 views

Using *EDIT* non-informative priors to account for perfect separation in logistic regression?

In generating logistic regressions for treatment-survival data, perfect separation is a problem in a few of my data sets. I've decided to use a Bayesian approach to account for the perfect separation ...
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1answer
2k views

Is it possible to get fitted values 0 or 1 in logistic regression when the fitting algorithm converges?

We have comprehensive coverage on the topic of perfect separation in logistic regression. When it happens in R we usually see two warnings: Warning messages: 1: glm.fit: algorithm did not ...
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1answer
80 views

How to use propensity scores that exhibit separation

I am using probability scoring on a data set where one variable has very small area of common support between treated and control (a small area in the middle exists). When I run a logit regression in ...
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3answers
2k views

Intuition for Support Vector Machines and the hyperplane

In my project I want to create a logistic regression model for predicting binary classification (1 or 0). I have 15 variables, 2 of which are categorical, while the rest are a mixture of continuous ...
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2answers
125 views

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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1answer
2k views

Multicollinearity and perfect separation in logistic regression: what should I do?

I have a dataset composed of 61 variables a qualitative one y=(0 or 1) and 60 other quantitative variables and 40000 observations. I want to do logistic regression,...
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2answers
212 views

Normally distributed estimated parameters in logistic regression

I was reading the book Introduction to Statistical learning, where in z statistic was used to for hypothesis testing for parameters, so my doubt is that as response variable is not normally ...
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1answer
446 views

Does (quasi) complete separation harm prediction in logistic regression?

A client has classified geographical areas into groups. He has done this in various ways, based on substantive concerns, so there is a 2 group division, a 3 group division and so on. He has also ...
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1answer
495 views

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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1answer
208 views

Complete separation in logistic regression with only one direction

In this paper Dealing with Separation in Logistic Regression Models some various types of complete separation are discussed: direction of the separation is positive if and only if $s_i = 1 \...