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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 ...
36 views

### Can a linear and logit model have the same shape?

While I was working on an exercise based this book, I discovered something interesting. When I fit a logit and simple linear probability model on the data (see code below), the predictions are almost ...
2k 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 ...
16 views

### Can visualization help to identify a dataset is linearly separable with polynomial features?

This data set cannot be linearly separable. If the polynomial and interaction features $X_1^2, X_2^2, X_1 \times X_2$ are used, can the data set linearly separable? I wanted to know there is any way ...
38 views

### Visualising Generalised linear models

I read about linear regression where we assume, the response is linear and the noise $\epsilon$, follows $N(0, \sigma^2)$ (Gaussian noise model), this leads us to conclude $E[Y|X] = b^*x$ and that the ...
59 views

### Curved regression lines

I had already asked a similar question here, but I'm experiencing the same problem for a different data-set and for a different family of mixed models. My response variable is a binary outcome of ...
53 views

### Discrete-time survival model as linear probability model

Discrete-time survival (event history) models are typically estimated using a nonlinear transformation such as logit, probit, or completementary log-log. Logit assumes proportional odds, and similarly ...
34 views

21 views

### single categorical DV, single countinuous IV

Background: I have a set of student answers to some questions and also their scores, whether the answer is correct or not (1 - not correct, 2 - somewhat correct, 3 - correct). I also have for each ...
973 views

### Can univariate linear regression be used to identify useful variables for a subsequent multiple logistic regression?

Does the $R^2$ (or some other statistic) from a univariate linear regression tell me anything about how it would work in a logistic model? What if I normalized the data to mean zero? I'm doing ...
2k views

### Big coefficient difference between logit/probit and linear probability model

Setting: Large N, short T panel dataset. Very few 1's (probably 1 percent), most zeroes. I estimate a logistic regression and find a negative significant coefficient on the IV of interest. ...
570 views

### When to take logarithms of a variable such as the Herfindahl Index?

Currently I am skimming through a couple of papers in well established journals! I became curious when I found papers with linear regression models using the Herfindahl index as the dependent ...
2k views

### Inclusion of significant interaction term in logistic regression table versus stratification for data presentation

This is a general question on logistic regression result reporting for a publication. We have an example where two well correlated ($r=0.4, p=0.001$) blood parameters (...
656 views

### How to determine the best relationship (linear, log, etc.) between input predictor variable(s) and output variable for multiple linear regression?

I am trying to determine the most accurate relationship between two variables (each predictor versus the output eventually). I want to know if the relationship is linear, or log-linear, or log-log, or ...