Questions tagged [logistic]

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

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Errors if running multiple logistic models with same predictors but different dependent variables?

I have a number of predictors and dependent variables that I intend to run with logistic regression. The DVs are binary and IVs are binary and ordinal. My question is, if I run multiple models with ...
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Dealing with colinearity and if and how interaction terms could improve regression model

In the last months, I'm working on estimating a logistic and multinomial regression model to analyze the relationship of students characteristics and the chances to dropout of school. For example, I'm ...
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Retrospective Sampling - Intercept Correction in the Logit Model

In a credit scoring context, I have fitted a logit model to describe the state of activity of different firms. Now, with a new validation set, I would like to use the previous model as score function....
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Imbalanced data classification with GLM giving very poor results

I have a loan defaulters dataset and it is highly imbalanced as shown below: 0 1 33108 673 I have tried SMOTE to balance the dataset, as shown below: ...
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Output significance for simple logistic regression in R

I am struggling with logistic regression in R. I have a rather complex data frame (with 15.550 observations) and try to do a logistic regression where results are very much unexpected and also ...
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Simulating population-level logistic regression model with pre-specified prevalence

I'm interested in simulating the following prospective, population-based model for binary outcome $Y_i$, and independent subjects $i=1,\dots,N$: $$ \Pr(Y_i=1\mid X_i,G_i)=\frac{1}{1+\exp(-(\alpha_0 + ...
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Calculation of AIC in finite mixture modeling

I have a question about calculation the AIC to find my optimal amount of clusters. I am applying mixture modeling with the EM algorithm. I know the formula AIC = -2ln(log-lik) + 2k. These are my log-...
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transformations of empirical distributions for multi class logistic regression

I am working on a multiclass logistic classification problem where two of the predictors (features) have highly skewed distributions. One is visibility (in m), which looks something like this: ...
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Regression analysis of spares consumption of aviation sector [closed]

I want to do a regression analysis. The data I have includes one independent variable (flying hours of aircraft) and one dependent variable (consumption of item). I want to run this regression for ...
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Can we use hypothesis testing for Logistic regression? [closed]

To put it down in a simple manner: can we use the same procedure as for the H0 and Ha, for the logistic regression. If not, what other types of testing we use to make decisions when performing a ...
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Multinomial Logistic Regression with Likert, Count and Categorical data

I want to predict a variable that has a likert format (satisfaction 1 to 4). However, the independent variables available to me are a series of count variables (e.g. counting frequency up to 6 ...
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Multilayer Perceptron with XOR Dataset

so I got this working code for a multilayer perceptron class, which I'm training on a XOR dataset (plot 1). As activation I'm using the hyperbolic tangent. After 50000 training epochs using SGD, my ...
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Categorization of continuous predictor in logistic regression

I have one continuous variable GENETIC SCORE and one binary variable HEALTH (case vs control i.e. 0/1). I want to fit a log regression model to this data to get the odds ratio for different percentile ...
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Does the inclusion of a model offset convert predictor variables from counts to rates?

Does the inclusion of a model offset in Poisson or logistic regression convert predictor variables from counts to rates? Or does it only convert response variables from counts to rates? I understand ...
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Can logistic regression output a non linear curve?

I have a doubt regarding logistic regression.I know that it separates the data into 2 parts.Is it possible that it leads to a curve as shown in the example of underfitting and overfitting What i know ...
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What does it mean “to leave predictors out of each batch of indicators?”

I've currently started reading the book "Data Analysis using Regression and Multilevel/Hierarchical Models" by Gelman and Hill. On page 5, there is a line saying "In addition, it would be necessary to ...
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Assumptions of Logistic Regression and Naive Bayes Classification Problems

Am trying to understand the difference between assumptions to follow for Logistic Regression and Naive Bayes. As per my knowledge both Naive Bayes and Logistic Regression should have features that go ...
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Should I use a linear transformation for my logistic regression model?

I am testing to see whether the only continuous variable in my logistic regression model upholds the linearity assumption. In your opinion, does my model require a transformation based on this partial ...
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Score test for binomial data

I am trying to derive the score test for a logistic regression and I read on Wikipedia that the score test for binomial data (which is used in logistic regression) is the same as the Pearson $\chi^2$-...
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Logistic regression threshold of independent variable [closed]

I have a logistic regression model for atmosphere toxicity where the dependent variable is toxic (1) if the atmosphere of a country is toxic and non toxic (0) and the independent variable is the ...
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27 views

Unusual distribution of predictors in conditional logistic regression

I'm using conditional logistic regression to model the case-control status of a disease with measurements of from measurements of certain blood compounds as the main predictors of interest. The ...
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Logistic Regression Residual Analysis in R (replicate influence command from SAS)

I'm looking for a quick reference on how to do some residual analysis for logistic regression in R. Oddly enough, this has not been easy to find. The data set I am working with is the Add.dat which ...
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How to perform multiple tests of contingency tables with more power: Fisher's / Barnard's test vs Logistic regression

I have a sample of answers to Yes / No questions: \begin{array} {c | c c c c} \hline \text{Case} & X_1 & X_2 & X_3 & X_4 \\ \hline 1 & 1 & 1 & 1 & 1 \\ 2 & 0 & ...
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What is a unit increase in logistic regression on standardized data?

I am confused about the unit increase on a dataset that has been standardized to have mean = 0 and standard deviation = 1. E.g. the temperature went from 0 to 100 deg initially, and from -1.5 top 1.5 ...
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Logistic Regression Coefficient Intrepretation - Impact On Churn

I am using logistic to see the relationship between churn and minute seen. I get something like this ...
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Can the AUC (logistic regression) be used as a measure of quality of the model? [duplicate]

If I have a good measure of the AUC, what does it tell me in relation to the model and its variables?
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ICA with a Laplace distribution

It's pretty common to set up ICA with a logistic distribution, but how would you find the loss and gradient with a Laplace distribution?
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Need help understanding logistic regression output with seemingly contradictory results after swapping reference group

Some background, each of these predictors are 0, 1 one-hot-encoded categories that represent items in a basket (think e-commerce). Each observation can have multiple 1s. For instance, a single ...
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Slopes with opposing signs provided by two methods

I have come across a situation where I am estimating trends in two different ways and the results have opposite signs. Specifically, the R functions emtrends and <...
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Interpretation of proportion dependent variable with beta reg

I'm trying to interpret this, let's say my dependent variable $y$ is the proportion of drinking beer in the last month, and my independent variable is x.1 if you have sleep well during the last week (...
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Ordered Logistic Regression With Data Collected in Multiple Time Periods

I have a dataset with cross-sectional data that was conducted in 8 separate time periods. In each period (roughly 1 year apart in time), roughly 3000 respondents (to be clear, in each time period ...
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Is it possible to draw conclusions on what causes bad results?

I am trying to apply a logistic model to classify some unbalanced data into two classes. However, I do not have many observations and the available features have a hard time making a distinction ...
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Binary logit modelling with R - Issue finding same results

I need your help to figure out something about the estimation of simple binary logit model in R. As nicely explained on the following website (https://stats.idre.ucla.edu/r/dae/logit-regression/) the ...
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Linear Probability Model Instead of Logit in Fixed Effects Regression

In our panel data analysis we estimated a fixed effects linear probability model (LPM) instead of a fixed effects logit regression because our sample size was quite small (600 individuals) and the ...
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Appropriate Model to predict food preference with high number of dependent variables

I am trying to build a model that delivers a prediction for which food a person may like based on information the person has entered into the system beforehand, e.g. they input that they like (beef, ...
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Variance decompostion for logistic regression using deviances?

I have data on the proportion of methylated cytosines in a gene from 13 plant genotypes from replicate experiments at four sites. Each genotype is replicated at each site, so and I would like to ...
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Simple explanation of maximum likelihood estimation

I was watching a video from code emporium, here he describes Maximum Likelihood Estimation (MLE) as to finding weights which maximizes the probability of seeing the training data (D = [X,Y]) $\...
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Strategies for graphing distributions of log-odds estimates and the corresponding odds ratios

I am currently writing up an experiment where we asked people on a 0-10 scale how much they expected three different beverages, water, decaf, and coffee, to reduce their caffeine withdrawal symptoms. ...
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Integrating the confint command to my default logistic regression output [closed]

I would like to hear of possible solutions to the following problem. I want to integrate the confintcommand with the general logistic regression ...
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1answer
37 views

Logistic regression model that has one categorical variable with multiple values

I have the following data: ...
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1answer
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How to test between-level significance in logistic regression

I have a logistic regression model which has one (significant) explanatory term and seven levels. I am trying to work out how to test for significant differences between the levels. It seems I have ...
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How to have better confidence in my logistic regression model

I have been working on a logistic regression model to predict 'yeses' in a yes/no classification problem. The objective of my problem is not necessarily to predict the outcome, but it's rather to just ...
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Comparison of statistical tests exploring co-dependence of two binary variables

Suppose we observe data $(X_i,Y_i)_{i=1,...,n}$ on two binary variables: $X\in\{0,1\}$ and $Y\in\{0,1\}$. We would like to test if $X$ and $Y$ are co-dependent (related). Standard suggestions in ...
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Logistic regression does not seem to maximize model accuracy

I'm using gradient descent to train my logistic regression model for a classification task. However, I notice that the accuracy of my model (using a boundary threshold of 0.5 to classify each sample) ...
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What factors will make a decision tree superior to a logistics regression model, taking into account the following? [closed]

Assume that the lift chart indicates that the decision tree is inferior, the C statistic is superior for the logistics regression also. What other factors will make a decision tree better, even in ...
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How to interpret a significant factor which has no significant levels?

I did a logistic regression with a single explanatory factor (which is ordered, hence I cannot set the reference level - it has 11 levels, hence when I get the Wald tests the first three are linear, ...
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Logistic Regression with independently weighted regularization terms [duplicate]

For a standard logistic regression problem I'm interested in examining the impact of individual weighting of the parameters and in general the impact of regularization for completely separable data. ...
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89 views

Reconstructing a logistic regression model from literature using published coefficients

I have a logistic regression model with the form: logit(p) = alpha + X*beta Where alpha is the intercept, X is the covariate matrix, and beta the corresponding coeffiecient. I want to be able to ...
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28 views

Simple Explanation about Logistic Regression Plot

I was reading an article about logistic regression and I got confused by one of the pictures: https://towardsdatascience.com/introduction-to-logistic-regression-66248243c148 First animated gif from ...
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How many hash buckets should I set with penalized logistic regression over large dataset

I am working with a logistic regression, and one of the predictors I am considering is a truncated ip address--as a proxy for location. I have about 200 million rows in the dataset but there are about ...