Questions tagged [logistic]

Refers generally to statistical procedures that utilize the logistic function, most commonly various forms of logistic regression

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178
votes
9answers
175k views

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: ...
325
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10answers
302k views

Difference between logit and probit models

What is the difference between Logit and Probit model? I'm more interested here in knowing when to use logistic regression, and when to use Probit. If there is any literature which defines it using ...
88
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3answers
84k views

Does an unbalanced sample matter when doing logistic regression?

Okay, so I think I have a decent enough sample, taking into account the 20:1 rule of thumb: a fairly large sample (N=374) for a total of 7 candidate predictor variables. My problem is the following: ...
83
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3answers
24k views

Why isn't Logistic Regression called Logistic Classification?

Since Logistic Regression is a statistical classification model dealing with categorical dependent variables, why isn't it called Logistic Classification? Shouldn't the "Regression" name be reserved ...
30
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3answers
26k views

Interpretation of simple predictions to odds ratios in logistic regression

I'm somewhat new to using logistic regression, and a bit confused by a discrepancy between my interpretations of the following values which I thought would be the same: exponentiated beta values ...
60
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7answers
72k views

Which pseudo-$R^2$ measure is the one to report for logistic regression (Cox & Snell or Nagelkerke)?

I have SPSS output for a logistic regression model. The output reports two measures for the model fit, Cox & Snell and ...
39
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2answers
18k views

Simulation of logistic regression power analysis - designed experiments

This question is in response to an answer given by @Greg Snow in regards to a question I asked concerning power analysis with logistic regression and SAS ...
91
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5answers
123k views

How to calculate Area Under the Curve (AUC), or the c-statistic, by hand

I am interested in calculating area under the curve (AUC), or the c-statistic, by hand for a binary logistic regression model. For example, in the validation dataset, I have the true value for the ...
57
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1answer
15k views

Logistic regression in R resulted in perfect separation (Hauck-Donner phenomenon). Now what?

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 ...
44
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1answer
11k views

Why do my p-values differ between logistic regression output, chi-squared test, and the confidence interval for the OR?

I have built a logistic regression where the outcome variable is being cured after receiving treatment (Cure vs. No Cure). All ...
47
votes
4answers
27k views

Regression for an outcome (ratio or fraction) between 0 and 1

I am thinking of building a model predicting a ratio $a/b$, where $a \le b$ and $a > 0$ and $b > 0$. So, the ratio would be between $0$ and $1$. I could use linear regression, although it doesn'...
21
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1answer
7k views

Omitted variable bias in logistic regression vs. omitted variable bias in ordinary least squares regression

I have a question about omitted variable bias in logistic and linear regression. Say I omit some variables from a linear regression model. Pretend that those omitted variables are uncorrelated with ...
28
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6answers
89k views

Sample size for logistic regression?

I want to make a logistic model from my survey data. It is a small survey of four residential colonies in which only 154 respondents were interviewed. My dependent variable is "satisfactory transition ...
35
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1answer
9k views

Does down-sampling change logistic regression coefficients?

If I have a dataset with a very rare positive class, and I down-sample the negative class, then perform a logistic regression, do I need to adjust the regression coefficients to reflect the fact that ...
13
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2answers
18k views

Bayesian logit model - intuitive explanation?

I must confess that I previously haven't heard of that term in any of my classes, undergrad or grad. What does it mean for a logistic regression to be Bayesian? I'm looking for an explanation with a ...
126
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3answers
265k views

What is the difference between linear regression and logistic regression?

What is the difference between linear regression and logistic regression? When would you use each?
16
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2answers
2k views

What is happening here, when I use squared loss in logistic regression setting?

I am trying to use squared loss to do binary classification on a toy data set. I am using mtcars data set, use mile per gallon and weight to predict transmission ...
10
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1answer
4k views

Interpretation of Fixed Effects from Mixed Effect Logistic Regression

I am confused by statements at a UCLA webpage about mixed effects logistic regression. They show a table of fixed effects coefficients from fitting such a model and the first paragraph belows seems to ...
46
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1answer
35k views

Regression: Transforming Variables

When transforming variables, do you have to use all of the same transformation? For example, can I pick and choose differently transformed variables, as in: Let, $x_1,x_2,x_3$ be age, length of ...
11
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2answers
29k views

Significant predictors become non-significant in multiple logistic regression

When I analyze my variables in two separate (univariate) logistic regression models, I get the following: ...
45
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3answers
42k views

Regularization methods for logistic regression

Regularization using methods such as Ridge, Lasso, ElasticNet is quite common for linear regression. I wanted to know the following: Are these methods applicable for logistic regression? If so, are ...
25
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4answers
21k views

What is the relationship between regression and linear discriminant analysis (LDA)?

Is there a relationship between regression and linear discriminant analysis (LDA)? What are their similarities and differences? Does it make any difference if there are two classes or more than two ...
6
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5answers
12k views

Coefficient changes sign when adding a variable in logistic regression

In my logistic regression the sign of coefficients of a variable (location distance of an amenity) changes based on other variables (with time -ve, with travel distance +ve) in the model. When the ...
68
votes
4answers
39k views

What is the difference between a “link function” and a “canonical link function” for GLM

What's the difference between terms 'link function' and 'canonical link function'? Also, are there any (theoretical) advantages of using one over the other? For example, a binary response variable ...
33
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2answers
49k views

Interpretation of plot (glm.model)

Can anyone tell me how to interpret the 'residuals vs fitted', 'normal q-q', 'scale-location', and 'residuals vs leverage' plots? I am fitting a binomial GLM, saving it and then plotting it.
19
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3answers
29k views

How to handle ordinal categorical variable as independent variable

I am using a logit model. My dependent variable is binary. However I have an independent variable which is categorical and contains the responses: ...
20
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2answers
48k views

Significance of categorical predictor in logistic regression

I am having trouble interpreting the z values for categorical variables in logistic regression. In the example below I have a categorical variable with 3 classes and according to the z value, CLASS2 ...
91
votes
4answers
164k views

What is rank deficiency, and how to deal with it?

Fitting a logistic regression using lme4 ends with Error in mer_finalize(ans) : Downdated X'X is not positive definite. A likely cause of this error is ...
44
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3answers
33k views

Multinomial logistic regression vs one-vs-rest binary logistic regression

Lets say we have a dependent variable $Y$ with few categories and set of independent variables. What are the advantages of multinomial logistic regression over set of binary logistic regressions (i....
5
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3answers
8k views

Multiple logistic regression power analysis

I have a logistic regression model and output an $R^2$ value. I then go and add another predictor variable to fit a second model. I can output a new $R^2$ value associated with the second model. When ...
40
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4answers
33k views

Logistic Regression - Error Term and its Distribution

On whether an error term exists in logistic regression (and its assumed distribution), I have read in various places that: no error term exists the error term has a binomial distribution (in ...
41
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2answers
95k views

Interpretation of R's output for binomial regression

I'm quite new on this with binomial data tests, but needed to do one and now I´m not sure how to interpret the outcome. The y-variable, the response variable, is binomial and the explanatory factors ...
32
votes
2answers
16k views

When is logistic regression solved in closed form?

Take $x \in \{0,1\}^d$ and $y \in \{0,1\}$ and suppose we model the task of predicting y given x using logistic regression. When can logistic regression coefficients be written in closed form? One ...
35
votes
4answers
11k views

Why does logistic regression become unstable when classes are well-separated?

Why is it that logistic regression becomes unstable when classes are well-separated? What does well-separated classes mean? I would really appreciate if someone can explain with an example.
8
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1answer
3k views

interpretation of betareg coef

I have a data that where the outcome is the proportion of a species observed in an area by a machine on 2 separate days. Since the outcome is a proportion and does not include 0 or 1 I used a beta ...
7
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2answers
4k views

How to use boxplots to find the point where values are more likely to come from different conditions?

I have plotted some data using box plots. I am comparing Condition 1 (left) and Condition 2 (Right) values. My aim is to find a point at which we make a decision where the value changes from point ...
26
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3answers
20k views

How to do logistic regression in R when outcome is fractional (a ratio of two counts)?

I'm reviewing a paper which has the following biological experiment. A device is used to expose cells to varying amounts of fluid shear stress. As greater shear stress is applied to the cells, more of ...
74
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3answers
34k views

Diagnostics for logistic regression?

For linear regression, we can check the diagnostic plots (residuals plots, Normal QQ plots, etc) to check if the assumptions of linear regression are violated. For logistic regression, I am having ...
52
votes
1answer
56k views

Obtaining predicted values (Y=1 or 0) from a logistic regression model fit

Let's say that I have an object of class glm (corresponding to a logistic regression model) and I'd like to turn the predicted probabilities given by ...
46
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2answers
116k views

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 ...
48
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2answers
44k views

How to simulate artificial data for logistic regression?

I know I'm missing something in my understanding of logistic regression, and would really appreciate any help. As far as I understand it, the logistic regression assumes that the probability of a '1' ...
20
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1answer
25k views

Help me understand adjusted odds ratio in logistic regression

I've been having a hard time trying to understand the use of logistic regression in a paper. The paper available here uses logistic regression to predict probability of complications during cataract ...
17
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1answer
3k views

Properties of logistic regressions

We're working with some logistic regressions and we have realized that the average estimated probability always equals the proportion of ones in the sample; that is, the average of fitted values ...
25
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3answers
47k views

Interpreting interaction terms in logit regression with categorical variables

I have data from a survey experiment in which respondents were randomly assigned to one of four groups: ...
28
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1answer
22k views

What is the difference between generalized estimating equations and GLMM?

I'm running a GEE on 3-level unbalanced data, using a logit link. How does this differ (in terms of the conclusions I can draw and the meaning of the coefficients) from a GLM with mixed effects (GLMM)...
13
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3answers
12k views

Model Selection: Logistic Regression

Suppose we have $n$ covariates $x_1, \dots, x_n$ and a binary outcome variable $y$. Some of these covariates are categorical with multiple levels. Others are continuous. How would you choose the "best"...
10
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2answers
16k views

Logistic regression and ordinal independent variables

I have found this post: Yes. The coefficient reflects the change in log odds for each increment of change in the ordinal predictor. This (very common) model specification assumes the the predictor ...
4
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1answer
2k views

How can logistic regression have a factorial predictor and no intercept?

I tried a regression in the form ${\rm logit}(Y) = {\rm coefficient}\times X + 0 + e$, where $Y$ is a binomial variable and $X$ is a factor variable with $n$ levels. I noticed that removing the ...
1
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2answers
1k views

Logistic Regression — Use of real values between 0 and 1[as opposed to two classes as negative:0 and positive:1]

I just wanted to confirm if this was correct :) For logistic regressions, do the outputs in the training set are actually no different than the outputs that we get as predictions? Is the only reason ...
1
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3answers
834 views

Logistic Regression: How to call the output

I'm currently working on a scientific paper and I'm struggle to answer the following question: What is the right term for the output (ranging from 0 to 1) of a logistic regression? Neither of these ...

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