Questions tagged [logistic]

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

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13
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714 views

How can I measure model performance with weighted logistic regression?

I am working with some survey data that uses probability weights. A number of sources explain that likelihood-based tests and fit statistics like likelihood-ratio, AIC, and BIC are not valid in the ...
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1answer
405 views

Interpreting regression coefficients based on Andrew Gelman's re-scaling method

I have two predictors in a binary logistic regression model: One binary and one continuous. My primary goal is to compare the coefficients of the two predictors within the same model. I have come ...
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1answer
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Why decision boundary differs between multinomial (softmax) and One-vs-Rest Logistic Regression for multiclass classification

Can someone please explain why the decision boundary differs between multinomial (softmax) and One-vs-Rest Logistic Regression for multiclass classification. Example shown below http://scikit-learn....
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“Brute force” expected deviance for logistic regression?

A commonly used goodness of fit statistic for logistic regression is the deviance. This is also known as the likelihood ratio chi-square statistic. It is defined as: $$D=\sum_{i=1}^{N}d_i^2$$ $$d_i^...
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Logistic regression for classification: are there any analytical solutions for the out-of-sample accuracy?

I run a binary logistic regression, with a binary dependent variable and a continuous independent one. Now I want to evaluate the out-of-sample performance of the classification algorithm so obtained. ...
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1answer
292 views

Logistic Regression with (Normal) Distributions for Independent Variables

Consider the logistic regression where $Y_i \in {0,1}$ are dependent variable observations and $X_i \in \mathbb{R}$ are the independent variables. However we do not observe the $X_i$ themselves. ...
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173 views

Including feature-dependent priors on output class, in bayesian logistic regression

When doing logistic regression with data $D_N = \{(x_i, y_i)\}_i^N$ with $x_i \in \mathbf{X}^N$ (each data point has N features) and $y_i \in \mathbf{Y}$ being assigned output classes, in a Bayesian ...
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987 views

Signatures of underfitting and overfitting in logistic regression calibration curves

My confusion stems from reading the following paper http://www.bmj.com/content/351/bmj.h3868 It states in its abstract (and they later show an empirical study that conforms to the claim) - "...
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1k views

How to test a linear relationship between log odds and predictors before performing logistic regression?

In case of a linear regression, it's easy to test a linear relationship between a continuous dependent variable and each independent variable. For example, I can plot a scatter plot between the ...
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2k views

How to deal with underdispersion with binomial data

I'm working with a pretty large dataset (n = 4,500) where 10% of my points (pixels in a GIS landscape) are 1s and the rest are 0s. The full model for my data looks something like this: ...
6
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2k views

Frequency weights, rare events and logistic regression

I'm working on a model that requires me to look for predictors for a rare event (less than 0.5% of the total of my observations). My total sample is a significant part of the total population (50,000 ...
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1k views

Logistic regression and maximum entropy

I have read (e.g. here) that a (multinomial) logistic regressor corresponds to a maximum entropy classifier. My question is, how does one end up with the formula for logistic regression starting with ...
6
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564 views

Calculate goodness-of-fit (with deviance) to compare averaged models?

I need to compare the goodness of fit of several averaged logistic regression models by calculating the deviance explained. I'm using the MuMIn package in R to ...
6
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307 views

Numerical properties of the logistic growth model for non-linear regression

I am using the nls procedure in R to fit a logistic growth model. In their SSlogis function, José Pinheiro and Douglas Bates chose the formulation ...
6
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284 views

Making new variable instead of correcting for temporal autocorrelation in a GLMM. Is it a valid alternative?

I am doing some forest disturbance research, in which the aim is to predict the probabilities of wind damage occurrence in forest stands of different site (altitude, slope steepness) and stand ...
6
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2k views

Maximum entropy classifier and sentiment analysis

I am doing a project work in sentiment analysis (on Twitter data) using machine learning approach. In order to find the 'best' way to this I have experimented with naive Bayesian and maximum entropy ...
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2answers
632 views

How to subset alternatives in nested multinomial logistic regression?

I am trying to predict whether or not captains in a particular groundfish fishery choose to fish on any given day and what variables may influence that decision. Originally I had planned on using ...
5
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1answer
278 views

How to estimate confidence intervals for LC50

This is my first question, so I hope the question is properly done (my apologies if it's not...) I am using a binomial GLM model (logit) for some toxicology data investigating the effects of a ...
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51 views

“Return values” of univariate logistic regression

I read an interesting article on an approach to calibrate probabilistic classifiers (Kull et al. 2017, "Beyond sigmoids: How to obtain well-calibrated probabilities from binary classifiers with beta ...
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146 views

What are the pros and cons of different metrics for evaluating a logistic regression model?

In the data science world, I have always evaluated the performance of logistic regression models simply using ROC/AUC. However recently, I've read from some traditional statistics source about some ...
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218 views

Mathematically Describing PCA chained with Logistic Regression

Python's scikit-learn package has a convenient pipe function that can combine machine learning techniques into one model with ...
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160 views

Which approach can be used to regress sleep time on brain mass, in this data set?

I was reading this blog post: https://htmlpreview.github.io/?https://raw.githubusercontent.com/avehtari/BDA_R_demos/master/demos_rstan/sleep.html the author describes a model to predict how many ...
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Censored logit transform for (ad hoc) exploratory data analysis

In my work I commonly have to analyze binary composition data, expressed as a fraction $f\in[0,1]$. The data $f[x]$ is spatially distributed ($x\in\mathbb{R}^n$, $n=1,2,3$), and typically comes in the ...
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474 views

Is it possible to get a prediction interval for logistic regression via a latent variable?

carbocation asked how to compute prediction intervals for logistic regression. The answer was that prediction intervals don't make sense for logistic regression because the response variable only ...
5
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534 views

logistic regression prediction: changing interpretation with changing prior

The data include 3 equally sized subsets A, B and C, belonging to two classes: A belongs to class 1. B and C belong to class 2. The prior probabilities of an observation coming from class 1 ...
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789 views

Aggregating Standard Errors for Predicted Probability Estimates

I obtain predicted values from a logistic regression for a certain outcome (e.g., mortality) at the hospital level – the data is at the patient level – and need to compute the average across hospitals....
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How does the RMS package's nomogram calculate points for continuous variables?

I have been reading a number of papers where researchers have created risk scores based on logistic regression models. Often they refer to "Sullivan's method" but I have no access to this paper and ...
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8k views

Mixed effect logistic regression in R: choosing random effects

I conducted an experiment which measured a binary response for each subject. The subjects were in 1 of 3 groups. There were two other fixed factors, each of which were continuums (cont1, cont2) ...
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223 views

Running regularized logistic regressions on very large datasets

I want to run a regularized logistic regression on a dataset with 25 million observations and about a 1000 mostly non-sparse columns with non-ignorable weights. My first choice would be BayesGLM, ...
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282 views

Separation in logistic regression in a complex survey?

Firth's penalized maximum likelihood estimates, exact logistic regression and Bayesian logistic regression (e.g. bayesglm) can account for separation in logistic regression. But how to account for ...
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2k views

Singularity issues in multinomial logit model with differing choice sets

I am estimating a discrete choice model in which individuals choose which schools to attend. I have a large amount of data on individuals and schools. However, each particular school only appears in ...
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5k views

Getting the bootstrap-validated AUC in R

In a paper by Faraklas et al, the researchers create a Necrotizing Soft-Tissue Infection Mortality Risk Calculator. They use logistic regression to create a model with mortality from necrotizing soft-...
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398 views

Confidence interval for proportions

I have some data like this: id pop var 1 593 51 2 592 31 3 346 20 4 1214 70 5 1063 66 6 1370 71 each ...
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2k views

How to assess mediation effect in multinomial logistic regression?

I wonder if it possible to include a mediation effect in multinomial logistic regression. I have a categorical (3 categories) outcome variable and four predictors (all continuous). I expect one of the ...
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1answer
325 views

Interpreting coefficients of ordinal independent variables in logistic regression in R

I have conducted a logistic regression in R ...
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0answers
78 views

Different coefficient estimates from ncvreg and glmnet in logistic regression

I'm trying to compare the results from glmnet and ncvreg in logistic regression. The methods have similar coefficients estimates ...
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0answers
443 views

Can you use regression to predict values if you imputed data using MICE?

I used multiple imputation on a data set that had some missing values (I had to do this as the sample size was low so I couldn't just exclude the NAs). I know you can do ...
4
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1answer
129 views

Proof for asymptotic error in logistic regression

Ng, A.Y., and Jordan, M.I. (2001). On Discriminative vs. Generative classifiers: A comparison of logistic regression and naive Bayes. Advances in Neural Information Processing Systems, 14, pp. 841-8, ...
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126 views

Mixed-effects logistic regression

I'm new to data analysis and I'm trying to perform a mixed-effect logistic regression. My data look like this: ...
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0answers
267 views

Do we have the actual theoretical study of L1/L2 regularization for Logistic regression?

It is very well known that L1 and L2 regularization can help in reducing the generalization error, and their effectiveness has been empirically demonstrated across a large set of machine learning ...
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557 views

Simulate/Generate Data for Multinomial Logistic regression

How to simulate data for Multinomial Logistic regression? For Example i want to generate a high dimensional data set with 90 subjects and 500 independent predictors. The ratio of Classes should given ...
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99 views

3 outcomes: one ordinal regression or two logistic regressions?

Imagine, for example, I am fitting a model with the following data: ...
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260 views

Using Random Forests for modeling discrete choice problems

I am trying to model a discrete choice scenario in which (i) the explanatory variables are both individual- and alternative-specific, and (ii) the number of alternatives varies between individuals. ...
4
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92 views

How does one design a data set from polynomial target function such that logistic regression separates the data perfectly?

I want to design a target function for a classification task of the form: $$ f_{target}(x) = \mathbb{1}_{>0}[\sum^{D^*}_{i=0} w^*_i x^i] = \mathbb{1}_{>0}[ \langle w^*, \Phi(x)\rangle]$$ and ...
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3k views

Influence plot for potential outlier detection from logistic regression in R

I am looking into identifying extreme values from their contribution to a binary outcome model. I have an unbalanced set and some extreme values which are part of the smaller set to predict (i.e ...
4
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2k views

Moran's test using the residuals of logistic regression

I have fitted a logistic regression and I would like to check for spatial autocorrelation in the residuals of the model. Is it statistically correct to implement the Moran's test using the residuals ...
4
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1answer
593 views

Modeling delayed feedback using logistic regression

Suppose we are trying to model the probability of a user clicking on an ad using logistic regression. We will receive only the positive feedback so, we define $Y = 1$ when success was observed, $Y=0$ ...

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