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

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Interesting Logistic Regression Idea - Problem: Data not currently in 0/1 form. Any solutions?

I am attempting to conduct a logistic regression for a tennis analytics project, endeavoring to predict the probability of a player winning a point in which he is the server. My response variable ...
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10 views

Logistic regression: Include a specific time variable to account for unexplained changes over time?

I am measuring the effect of specific marketing activities on the likelihood to buy a product. The Marketing activities start on a specifc date. All the products sold before this date a marked with a ...
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26 views

Logistic regression in R, basing on which class(0 or 1) in dependent variable the modelling is performed [on hold]

In R and in binomial logistic regression to be specific, is the modelling done based on which class amongst 0 and 1? And if it builds model based on 1 by default then is there a parameter or something ...
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29 views

Logistic regression is appropriate? Forecasting player’s serve point win % as a binary variable, w/ both numeric and categorical independent variables

I effectively want to model the probability of a player winning his service point (a point in which he is the server) based on the values of explanatory variables (namely court surface and opponent ...
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21 views

why in logistic regression the probability mass equal the count

It's said that logistic regression is well calibrated and preserves marginal probability. What does that mean? Thanks.
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307 views

Is it right to build a logistic model for population with 2% of yes and 98% no population with 800k obs and 200 variables

I have a dataset which has has some 800,000 observations data at member level with some 200 features and it has a response flag of 1/0. The proportion of response 1 flag is 2% of entire member ...
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8 views

coding for multinomial logistic regression dv

I have run a multinomial logistic regression. One of the 3 IVs is categorical and has 5 levels and the one DV is categorical and has 6 levels. I coded the levels from 1-5 for the IV and 1-6 for the ...
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6 views

Interpretation of standardized beta coefficient estimates and use within the exponential formula for prediction purposes

I'm working on a data set where I plan to use logistic regression to evaluate non-random habitat selection for a wildlife species. My dependent variable is 1 = used location by an animal and 0 = ...
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35 views

Logistic Regression modeling in R

Consider this model: $Y_i$ ~ Bernoulli($\pi_i$) $X_i$ = 0,1 logit($\pi_i$) = $\lambda^{X_i}$ * $\beta_0$ This model simplifies to logit($\pi_i$) = $\beta_0$ , when $x_i=0$ , and logit($\pi_i$) = ...
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37 views

Comparing mutation frequency between a case and a pool of controls

I"m working in genomics and trying to come up with the appropriate statistical test for my question. To call mutations in a tumor's DNA, we use sequencing that samples from the total population of ...
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27 views

Different ways to produce a confidence interval for odds ratio from logistic regression

I am studying how to construct a 95% confidence interval for odds ratio from the coefficients obtained in the logistic regression. So, considering the logistic regression model, $$ ...
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Visualizing multi-class ROC analysis [duplicate]

I am running a multinomial logistic regression model (with 3 possible outcomes) in R. I am trying to find the best way to assess the predictive power/accuracy of the model, and the best thing I've ...
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1answer
88 views

Nagelkerke value equals 1. Why?

I have run a logistic regression model, which leads to acceptable results (e.g., McFadden's R2 >10%). However, the Nagelkerke value is always 1, which seems like a failure to me (using the comand ...
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1answer
62 views

what's wrong with my data? [on hold]

Sorry,owing to my reputation,I have to delete the above word. Originally I just want to copy this page's method,the author use titanic data to analyze relationship between fare and survivor. And I ...
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26 views

K-fold cross validation [on hold]

I'm working on a data set that contains used (value= 1; animal locations) and random locations (value = 0). I'm using logistic regression to assess non-random habitat selection. I have 6 continuous ...
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14 views

Strange selection results, ridge logistic regression

I'm studying ridge logistic regression with glmnet on R. I have a lot of regressors which are dummies. I'm trying to maximise the AUC (prediction of a binary output). My question is about the graph ...
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12 views

Multinomial logistic regression, how to treat conditions without variance?

Currently I need to conduct a multinomial logistic regression, but my output shows an error message and incomplete results. I expect this is due to the fact that in one of my conditions, all ...
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22 views

mfp implementation in Stata and R [on hold]

I am applying multivariate fractional polynominals on data, which have 30000 (observations) x 20 (variables). Surprisingly, mfp in R is quite fast (10 minutes), but mfp in Stata is very slow (stuck ...
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33 views

Statistical technique to apply in Airline Industry [on hold]

I am working to Airline Industry data where frequency of travelers in a year is up to 1. I need to increase the frequency of the travelers using some predictive modelling approach so that campaign ...
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19 views

Multilevel logistic regression model

I have a dataset in which the DV is a binary choice outcome on a task trial. My IV's include binary stimulus property on the same task trial (e.g., stimulus is blue or red) as well as individual ...
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20 views

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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1answer
44 views

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. Specifically, I.m requesting a hypothesis tests for the significance ...
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43 views

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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1answer
29 views

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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19 views

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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13 views

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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36 views

Inconstant logistic regression coefficients each time algorithm is run [SOLVED] [closed]

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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17 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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1answer
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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25 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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84 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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1answer
26 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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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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83 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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24 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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17 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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1answer
27 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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38 views

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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63 views

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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21 views

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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26 views

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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74 views

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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28 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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31 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 ...