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

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K-fold cross validation dealing with an interaction term

I'm working on a logistic regression analysis and have a data set that contains ~12,000 data values (~6,000 values = 1; ~6,000 values = 0). I would like to use a k-fold cross validation process to ...
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How to extract Type III Fixed effects under the glmer procedure?

I need to extract the Type III fixed effects for reporting in a manuscript but cannot figure out how to extract this information. My R code is as follows: ...
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Random effects--mixed model

I have 2 study sites containing data from a species of wildlife. I am trying to evaluate resource selection use a use vs. availability analysis where used animal locations = 1 and random locations = ...
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GLMER and Model is nearly unidentifiable: very large eigenvalue

I'm working on a logistic regression analysis using the lme4 package and function glmer. I built the following model: ...
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Use Logistic Regression Literature for Logit Discrete Choice Models

I'm currently developing a binary logit Discrete Choice Model (DCM) in the context of my thesis. Obviously, I want to develop the model following academic standards. A few questions have been arising: ...
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Alternate terms, or definition for functional logistic regression

I have recently come upon a paper discussing "functional logistic regression." I could not find literature related to functional logistic regression. Is there a different name for this kind of ...
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Inconstant logistic regression coefficients each time algorithm is run [SOLVED] [on hold]

I'm running a logistic regression to find a relationship between falls and drugs taken by someone. What happens is that every time I re-run the algorithm it gives a different result. The table is ...
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12 views

How to use Weight vector of SVM and logistic regression for feature importance?

I have trained a SVM and logistic regression classifier on my dataset. Both classifier provide a weight vector which is of the size of the number of features. I can use this weight vector to select ...
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14 views

How to derive formula for marginal probability of choosing nest in nested logit model?

I am trying to understand all the details of the nested logit and what confuses me is the formula for marginal probability of choosing the nest. In more details: the joint probability of individual n ...
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23 views

Clarification on the rule of 10 for logistic regression

Been brushing up on my logistic regression and I've seen a couple of things about the one in ten rule. To illustrate my current understanding (or lack thereof) lets consider a case with only two ...
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62 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 ...
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24 views

How do I calculate the odds ratio in a logistic model with an interaction term (categorical)?

In the following logistic regression model, I am trying to model the logit of Y, where Y is a binary variable (Yes or No). Let my model be: logit($Y$) = $\beta_0$ + $\beta_1$*$x_1$+ $\beta_2$*$x_2$+ ...
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125 views

Difference in output between SAS's proc genmod and R's glm

I'm trying to replicate a model fitted in SAS in R but the fit I'm getting gives me slightly different coefficients and standard errors. Data: ...
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Why sigmoid function instead of anything else?

Why is the de-facto standard sigmoid function, $\frac{1}{1+e^{-x}}$, so popular in (non-deep) neural-networks and logistic regression? Why don't we use many of the other derivable functions, with ...
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Is there a way to do logistic regression model selection of up to 5 variables each from a pool of ~70 variables

I'm trying to determine the best logistic regression model to estimate the probability of 0 in streamflow rates. My response for the glm object is one vector of the sum of all the days the recorded ...
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80 views

How to cross validate stepwise logistic regression?

I have a conceptual problem understanding how to cross validate stepwise logistic regression. Every time the training set is divided it is very likely that different features are chosen based on the ...
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23 views

Two groups, 29 Likert scale questions - differences between the groups?

I've two groups of individuals, Group A (13) and Group B (30). Both groups got the same series of 29 questions that can be asked as "unimportant - slightly important - moderately important - very ...
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13 views

Gaze estimation, choosing algorithm and parameters

I am trying to build a program for estimating point of gaze on the computer screen from the x and y coordinates of the pupil centres from webcam video .(x and y coordinates correspond to pixel ...
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Manipulating coefficients in a logistic regression simulation study

I have a very interesting question in a logistic regression simulation study in . I borrowed the example from here How to simulate artificial data for logistic regression? , and modified it a little ...
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25 views

Proportional odds logistic regression with nominal (unordered) categories

Suppose that you've got a logistic regression with multiple nominal outcomes that cannot be ordered in a theoretically meaningful way. Assume further, however, that the proportional odds assumption ...
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Multinomial Logit Interaction Term

i have a multinomial logit model of the form $y= \alpha + young + year + \lambda_i + (young*year)+ \mu $ where $y$ represents three possible labour market states that an individual can be in. ...
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Simulation of logistic regression power analysis - output given

This question is in response to an answer given by @gung in regards to this question I am also wanting to use simulation to conduct a power analysis on a multiple logistic regression. To keep it ...
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Compare logistic models on same customers

I have two logistic models on the same set of customers in telecom. 1. Propensity to convert from fixed line to prepaid line 2. Propensity to convert from fixed line to post-paid line. I have to ...
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Clustering/classification before logistic regression

I have a little question. I am working with datasets in commercial bank, modeling scoring card using logistic regression. The GiINI is about 73-74 percents. I have an assumption that if I separate my ...
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Random Forest - Numeric and Dummy Variables together

I am trying to create a logistic regression model and a random forest model on the same data to predict probability of default. For the logistic regression model, I have created some dummy variables ...
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In logistic regression, what is the expected correlation between prediction and the dependent variable?

In multiple logistic regression: what is the expected covariance between the dependant variable $Y_i$ and prediction $expit(X_i\hat{\beta})$? what is the expected covariance between the dependant ...
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Multiple Logistic Regression power analysis

So I have a logistic regression model and output an R² value. I then go and add another predictor variable to a second model. I can output a new R² value associated with the second model. When I run ...
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What's the difference between logistic regression and perceptron?

I'm going through Andrew Ng's lecture notes on Machine Learning. The notes introduce us to logistic regression and then to perceptron. While describing Perceptron, the notes say that we just change ...
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How to specify logistic regression as transformed linear regression?

I am trying to reproduce the following example of logistic regression with a transformed linear regression: ...
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27 views

Sample size for logistic regression with a random effect

I wish to dig out a sample size (or to do a power analysis for a given sample size) for a logistic regression model with a random effect. To simplify, let's say I have a binary dependent variable Y ...
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29 views

Binary Classification vs Multi-class Classification

In the scenario that I have a binary classification problem, and use a binary classifier to train and test my model, assuming everything else is constant, would using a multi-class classifier with 2 ...
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Logistic Regression as Data Transform?

I'm analyzing medical research data with a small sample size that is not easy to replicate because the data were collected on an invasive procedure. The outcome variable is binary. There are two ...
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23 views

Confidence interval for the odds ratio in a finite population

Does it make sense to estimate a confidence interval for the odds ratio / logistic regression model when the sample size is nearly equal to population size? For example, if the sample size is 50 and ...
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Reference for Two-level Logistic Regression

I am an undergraduate student . In this level , we aren't taught Multilevel Logistic Regression. But my project topic is Multilevel Logistic Regression and I am ...
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51 views

Relating parameters to a measured variable

I have an ordinary differential equation based model for a system which depends on 16 parameters (all continuous and positive). I have 10000 random sets of parameters where each set has 12 elements. ...
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60 views

logistic regression question

I have two populations; population A of 1000 subjects and B of 1500 subjects. Among population A, 70 are men and 20 are women; also among population B, 68 are men and 16 are women. I want to know if ...
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How to compute the residual standard deviation from `glmer()` function in R?

I want to extract standard deviation of residual from glmer() function in R . So I wrote : ...
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Logistic Regression - Dummy and Numeric variables together

I am trying to build a logistic regression model. I have some categorical variables for which I have created dummy variables (eg. Department). I also have some numeric variables like Age and Tenure. ...
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Getting a specific X from a logistic curve

I have data that can be fit, more or less, by logistic growth functions. Hence I used this tutorial to do this. Now I want to get an x value for a specific y value from the model. Maybe this is too ...
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Use Linear Regression to Estimate Conditional Probability for Bayes Net?

When reading and watching video regarding building and using Bayes Nets, the examples typically use binary outcomes for the nodes. 'Probability of it raining', 'Probability of x disease', ect... ...
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(logistic regression with imbalanced data) Does high polynomial degree in combination with rebalancing negatively affect accuracy?

Data Set: https://www.kaggle.com/c/GiveMeSomeCredit/data (cs-training.csv) Training Tool: Weka Data Processing Tool: Python (for higher polynomial degree) Question: Balancing data (by down sampling ...
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How to compute Deviance Statistic for a simple Logistic Regression Model in the case that any $n_i = y_i$?

I am working on example 7.3.1 from the Second Edition of the book An Introduction to Generalized Linear Models in section 7.3 Dose response models. This example fits a simple logistic regression model ...
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What is the difference between logistic regression and bayesian logistic regression?

I'm a bit confused whether these two are the same concept. If they are different what's the difference? Thanks!
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Proportion Predictive Model with Bi-modal distribution

I am building a model that predicts a proportion: $y_i \sim f(x_{1,i}, x_{2,i},.., x_{n,i})$, where $y_i \in [0,1]$. One thing I find is that 40% of the observations have $y_i=0$. For the remaining ...
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Odds or Odds Ratio terminology?

I am having a bit of a tough time with some logistic regression terminology. I have performed a multivariable logistic regression analysis where I have regressed a binary variable (death, where 1 = ...
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Spatial Autoregressive model with ordinal dependent variable

I am trying to find out if there is a R/Stata package that allows one to do SAR model like mentioned in the LePage book with ordinal dependent variable. I am aware that there is a package called svdep ...
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Classification Model on Single Feature?

this is my first time using StackExchange so forgive me if I commit any faux paus with this question, and it has only been a few months since I first started learning machine learning. In my ...
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57 views

Ensembling Logistic Regressions Fit on Different Datasets

I would like to predict a binary response variable $Y_i$ using sets of predictors $\textbf{X}_{1i}, \textbf{X}_{2i}, \textbf{X}_{3i}$ for $i=1,\dots,n$. Each $\textbf{X}$ contains a few dozen ...
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Multi-label multinomial logistic regression

I have stock data with about 50000 features and 20 labels. Each of the label can take one of three values: -1, 0, 1. I've divided the data in 9:1 ratio so that nine tenth of the data is used to ...
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Vowpal Wabbit Logistic Regression Prediction

I have given vowpal wabbit a dataset with two labels and performed logistic regression with it. The problem is, it is returning real numbers varying from positive to negative as prediction. Now if I ...