# 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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### Proportion data with number of trials known (and separation?): GLM or beta regression?

I perform a lot of bioassays in which I score mortality not on individuals, but on groups of individuals as a proportion (the denominator, i.e., number of trials, is known): Sample Data: ...
40 views

### Unexpected weights in Gradient descent algorithm (linear classification) in python

I am attempting to implement a back propagation algorithm that can efficevley read from a file of features and there targets and predict there outputs correctly, however for sake of testing I am hard ...
85 views

### Hauck-Donner effect in ordinal generalized regression

I am running a series of ordinal regressions on a rather large data set (n=3640). With some predictors I had issues with violations of parallel lines assumptions, so I decided to run those with a ...
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1 vote
19 views

### Pooling Profile Penalised LTRs in multiple imputation

I am analysizing data from a clinical trial. I used multiple imputation to impute the (binary) outcome variable, which is the only variable with missing data. All of the covariates are categorical and ...
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1 vote
80 views

### Binomial (1/0) response, Factor explanatory variable: why can't GLM estimate effect when one factor level has all 1s in response?

I have a dataset with a binomial response variable (1/0) and a single explanatory categorical variable with 2 levels. For one level, the response is all 1s and no 0s (e.g. ...
• 202
41 views

### Is there quasi-seperation here (glmm, logistic regression), and how to take care of it?

I am running a mixed model (logistic regression) using the glmer function of lme4. I have a binary response variable "Germination", one categorical variable "Habitat" with 4 levels ...
• 1
168 views

### For the Logistic model, why is the objective function unbounded below if two sets are linearly seperated?

I am reading Approximate linear discrimination via logistic modeling in the Section 8.6.1 of B & V's Convex Optimization book. On Page 428, $$\operatorname{minimize} \ -l(a, b) \tag{8.27}$$ ...
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66 views

### Why PCA is not considered in the taxonomy of blind source separation approaches?

Blind source separation (BSS) approaches are divided in the literature into four methods, including independent component analysis (ICA), sparse component analysis (SCA), and non-negative matrix ...
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41 views

### feature engineering for linear separability and curse of dimensionality

A common method to make otherwise not linear separable datasets separable, is feature engineering - e.g. squaring original feature as show here: Taken from here. Ultimately, a dataset with more ...
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21 views

### How to test (overall) significance of categorical variable(with multiple levels) in bias-reduced binomial-response GLM(brglm package), & posthoc-test?

I have a dataset that has quasi-separation. My dependent variable is 'Yes' or 'No', and I have two fixed effects and one random effect. The fixed effect 'Treatment' is a categorical variable and has ...
1 vote
18 views

### Cold Start and First Price Auctions

I have the following contrived scenario... I've participated on various auction platforms where I bid on widgets. Assume that win/loss outcomes on individual platforms are well-separated such that for ...
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1 vote
50 views

### Is the sum of 3 bits a linearly separable task?

In other words can a linear classifier learn to correctly assign a class (label 0 to 3) for an input of 3 bits? Intuitively this cannot work, since the half-adder circuit contains an XOR block, which ...
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152 views

### Hidden vs Firth vs Shen-Gao logistic regression: dealing with the Hauck-Donner effect

In 1993 a version of penalized logistic regression was introduced by Firth in order to reduce the bias due to outliers and/or (quasi-)perfect prediction in logistic regression: Bias Reduction of ...
22 views

### On the use of the sampling year as fixed-effect

I have my database in temporal blocks (so I have my occurrence sites into the year of sampling of a few years with maximum 7 years). In order to fix the complete separation problem that I also have, ...
• 135
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### Is there any impact on the results of random forest if we have perfect separation in the database?

I'm having a perfect separation in my database. One of the solutions is to switch randomly some of the values of the dependent variable to the opposite for the variables that cause the problem this ...
• 135
240 views

### Dealing with quasi-complete separation in General Additive Model?

I am modelling influence of fire on occurrence of certain bird species (count response variable) in Before/after control/impact experiment design. I've got intact and burned sites and count data both ...
1 vote
56 views

### How many percentage to randomize and how many iterations in a "what-if analysis"?

I've got complete separated data as such: ...
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53 views

1 vote
64 views

### 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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