# Linked Questions

1answer
14k views

### 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 ...
1answer
2k 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 ...
1answer
4k views

### 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?
1answer
1k 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 ...
0answers
759 views

### Logistic regression in R ; glm.fit: fitted probabilities numerically 0 or 1 occurred [duplicate]

I'm fitting a logistic regression model in R. Following is the structure of my data set. I've used the glm function in R. ...
0answers
378 views

### 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 ...
0answers
256 views

### How to deal with a model that can't be fit due to quasi-complete separation? [duplicate]

I am doing a binary logistic regression analysis. I got one categorical predictor with 7 levels. When I try to do this in Minitab 17 I get an error message: "The model could not be fit. Maximum ...
0answers
239 views

### binomial GLM output hugely affected by a factor level with all zeros [duplicate]

I’m trying to estimate the effects of pest control on rat abundance, but I'm finding that the inclusion of a pest control category that contains all zeros is having huge effects on the results. My ...
0answers
181 views

### Large coefficients in logistic regression [duplicate]

This is from the book The statistical sleuth--A course in methods of Data analysis Chapter 20, Exercise 12(c)-(e). I am using logistic regression to predict carrier with possible predictors ...
0answers
127 views

### logistic regression - complete/quasi-separation [duplicate]

What is the implication if I don't fix a logistic regression that has complete or quasi separation? can I still read the marginal effects or are they not going to be valid? My exercise is actually ...
0answers
113 views

### GLM for proportion data in r - with many zeros (or ones) [duplicate]

My understanding is that generalized linear modeling (GLM) is recommended for proportion data. However, this seems to run into problems when a set of data is full of zeros (or ones). For example, a ...
0answers
68 views

### Logistic Regression Get 100% R-square but no predictors are significant? [duplicate]

How could that be possible? The model is significant too. The null model already predicted 70% correctly. After adding predictors, the model predicts 100%. But no single predictors are significant. I ...
0answers
53 views

### Logistic regression not converging [duplicate]

I run a multivariable logistic regression in SAS using the main effect/independent variable as continuous and categorical. As a continuous variable the confidence intervals of the odds ratios were ...
0answers
49 views

### extremely strange logistic regression results [duplicate]

I am very new to r and statistics so excuse me if the answer to my question is very obvious. I have surveyed 64 people on their Facebook behaviour related to their political participation. One of my ...
1answer
33 views

### 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 ...

15 30 50 per page